. International Journal of Energy Economics and Policy | Vol 10 • Issue 4 • 2020500 International Journal of Energy Economics and Policy ISSN: 2146-4553 available at http: www.econjournals.com International Journal of Energy Economics and Policy, 2020, 10(4), 500-506. Decomposition of Growth Factors in High-tech Industries and CO2 Emissions: After the World Financial Crisis in 2008 Yu-Chen Yang1, Cheng-Yih Hong2*, Syamsiyatul Muzayyanah3, Rishan Adha3 1Department of Applied Economics, National Chung-Hsing University, Taiwan, 2Faculty of Finance, Chaoyang University of Technology, Taiwan, 3Department of Business Administration, Chaoyang University of Technology, Taiwan. *Email: hcyih@cyut.edu.tw Received: 11 February 2020 Accepted: 06 May 2020 DOI: https://doi.org/10.32479/ijeep.9411 ABSTRACT Taiwan’s economic development faces two problems, one is the imbalance of the economic structure, and the other is that the industrial structure must be upgraded. This is a problem that has existed since the 1990s, but it has not been solved for a long time. The outbreak of the world financial crisis in 2008 severely damaged the international economy and finance, and Taiwan suffered a huge economic shock. In the face of an economic predicament, Taiwan attempts to transform the unbalanced economic system through technological innovation through public investment and the updating of corporate equipment, and sets the goal of sustainable development, of which high-tech industries have become the focus of economic development. This paper takes the financial crisis as the research period, analyzes the growth of the industries and their causes through the economic growth decomposition model, and estimates the CO2 emissions generated, which will help understand Taiwan’s future economic development. The research results show that the growth of high-tech industries after the financial crisis is dominated by semiconductors and power equipment-related industries. The growth factor is innovation of input technology and the improvement of self-sufficiency. At the same time, CO2 emissions are mainly caused by these two factors. Keywords: High-tech Industries, CO2 Emissions, Input Technology, Growth Decomposition Model JEL Classifications: Q43, C6, E2, E210 1. INTRODUCTION From 1981 to 2016, Taiwan underwent liberalization, internationalization, and global economic changes. In the course of economic development during these 35 years, except for the Internet bubble economy in the United States in 2002 and the impact of the global financial crisis in 2009, Taiwan has shown economic growth. After joined the World Trade Organization (WTO) in 2002, Taiwan became a member of the WTO, and expanding international trade has changed the industrial structure. In 1981, the GDP of agriculture, industry, and services accounted for 7.35%, 43.83%, and 48.82% of the overall industry. By 1988, the service industry had exceeded 50%, and the proportion of agricultural output value had dropped significantly. The proportion of primary industries has gradually declined and the proportion of tertiary industries has gradually increased. By 2016, the agricultural, industrial and service industries’ GDP ratios were 1.82%, 35.06% and 63.13%, respectively. In other words, Taiwan’s industrial structure has changed a lot after joining the WTO. After the 1960s, Taiwan’s sustained high growth was through employment creation and economic development through the trade export industry. However, in the 1980s, liberalization and market opening, the pace of industrial innovation could not keep up with competitors’ price strategies, and Taiwan ’s economy could not be as fast as in the past continue to grow. Since import and export trade has become the main economic structure, the volume of trade has become an important factor in the change of industrial structure. Especially after the Plaza Agreement in 1985, the appreciation of the currency led to a substantial increase in trade volume. Imports This Journal is licensed under a Creative Commons Attribution 4.0 International License Yang, et al.: Decomposition of Growth Factors in High-tech Industries and CO2 Emissions: After the World Financial Crisis in 2008 International Journal of Energy Economics and Policy | Vol 10 • Issue 4 • 2020 501 and exports have gradually become an important factor in Taiwan’s economic growth. In 2005, it exceeded 200 billion US dollars, and the value of imports and exports has expanded. The crisis of the world financial tsunami was triggered in September 2008. The export trade volume has fallen sharply from a growth of more than 10% in the first 8 months, and has begun to turn negative growth in the third quarter. By the first quarter of 2009, Taiwan’s exports The decline was expanded to −26.87%. In order to respond to economic losses caused by financial shocks, Taiwan has implemented multiple fiscal policies and expanded public investment so that economic growth can gradually return to stability. Among them, Taiwan attaches great importance to the research and innovation of high-tech industries and plays an important role in economic development. The total value of trade in 2014 was a record high of $ 601.9 billion. Judging from the GDP value of imports and exports, imports and exports accounted for 43.28% and 46.24% each in 1981, and have increased to 43.51% and 52.90% in 2016. The financial crisis has raised Taiwan’s focus on the development of high-tech industries. In addition, energy policies are also adjusted under environmental protection. Taiwan’s investment in renewable energy generation systems attempts to provide more sources of electricity to achieve economic development and environmental protection. In order to achieve research objectives, this paper will analyze the growth factors of high-tech industries after the financial crisis, and discuss the relationship between power consumption and CO2 emissions, which will help to understand the direction of Taiwan’s industrial structure adjustment in the future. In order to obtain more specific data to analyze the research topic of this thesis, a factor decomposition model of the high-tech industry will be established in section 3 to establish two factor decomposition models of CO2 emissions. 2. LITERATURE REVIEW The past literature on the relationship between the economy and the environment can be divided into several stages of research. The early literature focused on the relationship between economic growth and environmental pollutants. The analytical point of view is represented by the Environmental Kuznets Curve (EKC) (Lee and Lee, 2009; Ang, 2007; Saboori et al., 2012). The EKC hypothesis suggests that the level of environmental pollution will increase with the country’s economic development, but will start to decrease as the national income increases beyond the turning point (Dinda, 2004). With the rapid increase of energy consumption caused by economic development, the research focus has gradually shifted to the impact of energy (electricity) use on environmental loads (e.g. Kraft and Kraft, 1978; Payne, 2010a; Payne, 2010b; Ozturk, 2010 Ozturk and Acaravci, 2011; Farhani et al., 2014; Bella et al., 2014; Dogan, 2015; Njoke et al., 2019; Sunde, 2020). In addition, many studies often use Granger causality to analyze the relationship between economic growth and energy consumption, and further analyze the relationship between economic growth, energy consumption and environmental pollution. However, in many studies, the relationship between economic development, energy consumption, and pollution in different countries has different results. Njoke et al. (2019) points out the relationship between Cameroon’s power consumption, carbon emissions and economic growth from 1971 to 2014. The study indicates that there is a significant relationship between CO2 emissions and economic growth, whether short-term or long-term. However, studies have shown different results. For example, Ozturk and Acaravci (2011) pointed out that there is no relationship between electricity consumption and economic growth in most Middle East and North Africa countries. There are also numerous studies analyzing the relationship between energy consumption and environmental damage, such as Yavuz and Yilanci (2013), Presno et al. (2018), and Aydin and Esen (2018). Because economic growth brings changes in the industrial structure, and the relationship between the economy and the environment is often subject to the influence of industrial structure styles, changes in the industrial structure will cause different results. In addition, attention has been paid to the adjustment of power sources. In recent years, there has been an increasing trend in research on renewable energy (Dogan, 2015; Bölük and Mert, 2015). However, with the development of globalized economy, economic growth has indeed caused significant environmental impacts (Dreher, 2006; Managi and Kumar, 2009; Jorgenson and Givens, 2014; Li et al., 2015; Doytch and Uctum, 2016; You and Lv, 2018; Saint Akadiri et al., 2019). Managi and Kumar (2009) research pointed out that trade does have an adverse effect on CO2 emissions, and Doytch and Uctum (2016) also believe that improper investment activities will cause environmental damage. In addition, Dreher (2006) proposed that the global economy should invest in green related industries to improve the environment. 3. METHODOLOGY AND DATA This research model is a factor decomposition model established by I-O Tables (Input-Output Tables) in different periods. It is considered that there are changes in prices and quantities in economic growth in different periods. In addition, the analysis period of this paper is set between 2011 and 2016. Therefore, the establishment of the model of this paper needs to be processed through substantial processes in order to make the two periods industry price benchmarks are consistent. This section uses Fujita and William (1997), Hong et al. (2018), and Hong et al. (2019) to build the following three models. 3.1. The Decomposition Model of High-tech Industries Growth The equilibrium equation of the I-O model of the high-tech industry can be expressed by the quantity equations (1). X I I M A I M F E� � �� ��� �� �� � ��� �� �1 (1) Where, the definition of each variable in the equation is as follows X is a vector representing the total output of the industry (n × 1); A represents the input coefficient matrix (n × n). As matrix A Yang, et al.: Decomposition of Growth Factors in High-tech Industries and CO2 Emissions: After the World Financial Crisis in 2008 International Journal of Energy Economics and Policy | Vol 10 • Issue 4 • 2020502 reflects technology of production, it is usually called technological matrix; F is the domestic final demand vector (n × 1); E is the export vector (n × 1); M is the diagonal determinant of the import coefficient (n × n). t and t + 1 represent the base year and the comparative year. The changes in the two periods can be written as: � X I I M A I M F E I I M A t t t t t t t � � �� ��� �� �� � ��� �� � � �� ��� � � � � � � �1 1 1 1 1 1 �� �� � ��� �� �1 I M F Et t t (2) When I I M A Bt t t� �� ��� �� �� � � �1 1 1 1 � and I I M A Bt t t� �� ��� �� � �1 are substituted into equation (2), resulting in the following modifications: � X B I M F I M Ft t t t t� �� � � �� ��� ��� � � �1 1 1 1 (changes in domestic final demand) � �� �� �B E Et t t1 1 � (changes in exports) � �� � � �� ��� ��� �B I M F I M Ft t t t t1 1 (changes in final goods imports) � �� � �� � ��� ���B B I M F Et t t t1 * (changes in self-sufficiency) � �� � �� � ��� ��B B I M F Et t t t* � (changes in input technology) (3) Where, I I M A Bt t� �� ��� �� �� � 1 1 * .. 3.2. The Decomposition Model of CO2 Emissions Growth This section uses equation (3) to establish a CO2 emissions growth model. This will require an estimation of the industry’s CO2 emissions coefficient. The model building process is shown below. CO2t and CO2t+1 represent CO2 emissions in t years and t+1 years. CO C X C I I M A I M F Et t t t t t t t t2 1 � � � �� ��� �� �� � ��� �� � � � (4) ( ) ( ) 1 2 1 1 1 1 1 1 1 1 ˆ t t t t t t t t CO C X I I M A I M F E − + + + + + + + +  = = − −   − +  (5) CO CO COt t2 1 2 2� � � � (6) Where the emissions coefficient c CO xj j j= 2 , and Ĉ is the diagonal matrix of the elements of the emissions coefficients for various industries. 1 0 0 ˆ n c C c    =            ( ) ( )2 1 1 1 1 1ˆt t t t t tCO C B I M F I M Fδ + + + + + = − − −  (a) ( )1 1 1ˆt t t tC B E E+ + + −+ (b) ( ) ( )1 1 1ˆt t t t t tC B I M F I M F+ + + − −+  −  (c) ( ) ( )*1 1ˆt t t t tC B B I M F E+ +  − − ++  (d) ( ) ( )*1ˆ ˆt t t t t tC B C B I M F E+  − − ++  (e) (a) The CO2 emissions of changes in domestic final demand;(b) The CO2 emissions of changes in exports;(c) The CO2 emissions of changes in final import coefficients;(d) The CO2 emissions of changes in self-sufficiency coefficients;(e) The CO2 emissions of changes in production input technical coefficients. From the five factors (a) to (e), we can estimate the scale of CO2 emissions, which will help promote the future development of the industries. 4. EMPIRICAL RESULTS AND DISCUSSION 4.1. Analysis of Growth Factors of High-tech Industries after the Financial Crisis The growth of the high-tech industry since the 1990s has been the main factor driving Taiwan’s economic development. This section empirically analyzes whether this trend has changed after the financial crisis. At the same time, what factors will change the high-tech industry? On the other hand, does the growth of high-tech industries also change in CO2 emissions? This will also be the focus of this section. Because high-tech industries include a variety of different industries, in order to be able to more fully identify the characteristics of industrial development, this section divides high-tech industries into three major industrial groups according to the nature of the industry, namely “semiconductor related industries,” “computer and electronics related industries,” and “power system related industries.” 4.1.1. Growth factors of semiconductor related industries Table 1 shows the growth scale of “semiconductor related industries” during 2011–2016. From Table 1, we can see that the semiconductors industry has the largest growth, which accounts for 75.04% (NT$ 1,315,252 million) of “semiconductor related industries,” while the passive electronic components sector has the least growth, only NT$ 46,873 million. The biggest factor in the growth of the semiconductors industry comes from the improvement of self-sufficiency, which is increasing the proportion of domestic industrial manufacturing, which means that this sector has improved the integrity of the domestic production chain after the financial crisis. In addition, the improvement of input technology created the semiconductors industry by NT$ 306,952 million, which accounted for 23.34% of the total. On the other hand, the biggest factor driving the growth of “semiconductor related industries” is the technological innovation of input technology, Yang, et al.: Decomposition of Growth Factors in High-tech Industries and CO2 Emissions: After the World Financial Crisis in 2008 International Journal of Energy Economics and Policy | Vol 10 • Issue 4 • 2020 503 which contributed NT$ 638,346 million, which accounted for 36.42% of the total growth (=NT$ 638,346 million/NT$ 1,752,843 million). 4.1.2. Growth factors of computer and electronics related industries The computer and electronics industries are the foundation of high- tech industries. However, after the 1990s, these related industries were largely transferred from Taiwan to Chinese production. From Table 2, we can see that the changes in computer and electronics related industries have shown negative growth (-NT$ 541,763 million). The largest reduction was in the communications industry, which was about NT $ 472,008 million. The biggest factor that caused the reduction of the communication industry was exports (-NT$ 466,976million), followed by domestic final demand (-NT$ 102,949 million). Despite the negative growth of “computer and electronics related industries,” there are also growing industries, which include Computer products, Computer peripherals and Measurement, navigation, control and other industries. The main factor for these growing industries comes from input technology, which shows that technological innovation is still a necessary condition for Taiwan’s industrial development. 4.1.3. Growth factors of power system related industries Taiwan has promoted the transformation of power generation systems from 2017, and it is particularly important to observe the growth and changes of “power system related industries.” Table 3 shows the growth of power system related industries between 2011 and 2016. It can be seen from the table that the growth of other power equipment and transportation related industries is the largest, accounting for about 142.00% and 67.85% of the “power system related industries.” After the financial crisis, innovation in input technology was the biggest factor driving the growth of “power system related industries.” This factor created a total value of NT$ 436,951 million, and self-sufficiency and final goods imports factors also created NT$ 202,381 million, NT$ 78,302 million. The transformation of energy sources requires new technologies and investments, as well as changes in the relevant legal systems of energy supply. This is a major reform project. Therefore, Table 3 shows that the related industries of the power system have improved significantly in terms of technological innovation and self-sufficiency. 4.2. Analysis of CO2-emissions Changes of High-tech Industries after the Financial Crisis Economic growth and increased energy consumption may also lead to more CO2 emissions. This section estimates the scale of CO2 emissions from economic growth in Section 4.1. 4.2.1. The CO2 emissions factors of the semiconductor-related industries Table 4 shows the CO2 emissions increased by “semiconductor related industries” during the period of 2011-2016, and it can be known from the data that this industry group has increased by a total of 5,446,876 tons during the 5-year period. This result is mainly due to the improvement of input technology to increase production. Among them, the growth rate of the Semiconductors industry is the most obvious, with a total increase of CO2 emissions of about 4,087,083 tons. Table 1: Growth factors of semiconductor related industries (2011-2016) Classification of industries Changes in factors (a) Changes in domestic final demand (b) Changes in exports (c) Changes in final goods imports (d) Changes in self‑sufficiency (e) Changes in input technology Semiconductors 248,559 240,202 185,046 334,493 306,952 Passive electronic components 11,836 2,452 8,054 16,208 8,323 Printed circuit board −47,685 30,034 8,788 13,920 54,682 Optoelectronic materials and components −174,725 85,884 12,699 8,958 213,717 Other electronic components 39,179 520 37,031 53,047 54,673 Total 77,163 359,091 251,617 426,626 638,346 Unit: NT$ million Table 2: Growth factors of computer and electronics related industries (2011-2016) Classification of industries Changes in factors (a) Changes in domestic final demand (b) Changes in exports (c) Changes in final goods imports (d) Changes in self‑sufficiency (e) Changes in input technology Computer products 4,260 9,445 3,370 892 13,820 Computer peripherals −14,382 14,055 −3,670 −69 24,649 Communication −102,949 −466,976 3,027 2,124 92,766 Audiovisual electronics −4,770 −26,809 3,155 2,764 4,678 Blank data storage media −14,864 −40,546 −28 634 8,750 Measurement, navigation, control 20,359 −109,974 58,225 29,738 17,551 Radiation and electronic medical equipment, optical instruments −11,788 −114,372 17,971 21,691 15,510 Total −124,134 −735,177 82,050 57,774 177,724 Unit: NT$ million Yang, et al.: Decomposition of Growth Factors in High-tech Industries and CO2 Emissions: After the World Financial Crisis in 2008 International Journal of Energy Economics and Policy | Vol 10 • Issue 4 • 2020504 On the whole, although “semiconductor related industries” can also create industry growth after the financial crisis, CO2 emissions are also showing positive growth from the five factors in the table. 4.2.2. The CO2 emissions factors of computer related industries The performance of CO2 emissions in the “computer and electronics related industries” group is shown in Table 5. It can be seen from the table that the largest increase in CO2 emissions is in the computer-related industries. Among them, Computer products and Computer peripherals increased by 98,777 tons and 63,962 tons respectively. Due to the impact of the financial crisis, the negative wealth effect reduced the demand for domestic final demand and exports, which indirectly contributed to the reduction of CO2 emissions. These two factors reduced CO2 emissions by 385,741tons and 2,284,528 tons, respectively. 4.2.3. The CO2 emissions factors of power system related industries Economic development requires electricity security and stable supply, while also taking into account environmental preservation to improve the quality of life. The analysis period of this paper is only up to 2016, and it does not include the energy transition policies after 2017. Therefore, the growth of “power system related industries” in Table 6 is only reflected in the estimated data under the past power generation system. Due to the reduction of domestic final demand and exports caused by the financial crisis, these two factors have reduced CO2 emissions by 1,142,499 tons and 396,940 tons, of which the professional machinery industry is the most significant. The wires, cables and wiring related industries reduced CO2 emissions by 475,015 tons. On the other hand, the main industries with increased CO2 emissions are other power equipment (980,619 tons) and Transportation related (468,523 tons). Table 3: Growth factors of power system related industries (2011-2016) Classification of industries Changes in factors (a) Changes in domestic final demand (b) Changes in exports (c) Changes in final goods imports (d) Changes in self‑sufficiency (e) Changes in input technology Power generation, transmission and distribution −58,713 −13,213 4,196 474 16,805 Battery −1,257 −599 985 6,733 3,121 Wires, cables and wiring −141,364 −11,499 1,727 −6,537 41,386 Lighting device −10,437 −2,478 −107 167 5,129 Household appliances −6,883 1,008 −1,107 216 7,956 Other power equipment 106,333 −38,276 20,305 172,743 54,465 Professional machinery −250,847 −125,380 71,456 46,963 177,987 Transportation related −4,496 62,699 −19,153 18,378 130,102 Total −367,664 −127,738 78,302 202,381 436,951 Unit: NT$ million Table 4: CO2 emissions factors of the semiconductor-related industries (2011-2016) Classification of industries Changes in factors (a) Changes in domestic final demand (b) Changes in exports (c) Changes in final goods imports (d) Changes in self‑sufficiency (e) Changes in input technology Semiconductors 772,385 746,416 575,022 1,039,421 953,839 Passive electronic components 36,780 7,619 25,027 50,366 25,863 Printed circuit board −148,179 93,329 27,308 43,256 169,922 Optoelectronic materials and components −542,950 266,880 39,462 27,837 664,116 Other electronic components 121,747 1,616 115,072 164,841 169,894 Total 239,780 1,115,858 781,888 1,325,720 1,983,630 Unit: Tons Table 5: CO2 emissions factors of computer related industries (2011-2016) Classification of industries Changes in factors (a) Changes in domestic final demand (b) Changes in exports (c) Changes in final goods imports (d) Changes in self‑sufficiency (e) Changes in input technology Computer products 13,238 29,350 10,472 2,772 42,945 Computer peripherals −44,691 43,675 −11,404 −214 76,596 Communication −319,909 −1,451,106 9,406 6,600 288,266 Audiovisual electronics −14,823 −83,308 9,804 8,589 14,537 Blank data storage media −46,189 −125,995 −87 1,970 27,190 Measurement, navigation, control 63,265 −341,739 180,931 92,409 54,539 Radiation and electronic medical equipment, optical instruments −36,631 −355,406 55,844 67,404 48,197 Total −385,741 −2,284,528 254,967 179,530 552,269 Unit: Tons Yang, et al.: Decomposition of Growth Factors in High-tech Industries and CO2 Emissions: After the World Financial Crisis in 2008 International Journal of Energy Economics and Policy | Vol 10 • Issue 4 • 2020 505 5. CONCLUSIONS AND POLICY IMPLICATIONS Taiwan’s economic development is facing an imbalance between the economic structure and the industrial structure. The world financial crisis in 2008 caused huge economic losses and increased unemployment. In the future, Taiwan’s economic planning will focus on the economic goals of industrial restructuring and sustainable development. The key to accomplishing this economic goal lies in the success of the development of high-tech industries in the future. This research is to analyze the economic and industrial changes after the financial crisis, and to analyze the factors of industrial growth and change with the industry’s composition model. This will help to understand and follow the trend of Taiwan’s economic development, and can provide specific suggestions. From the above empirical results, the following points are summarized. The high-tech industry is centered on machinery-related industries. The growth during the 5 years after the financial crisis (2011-2016) created an increase of NT $ 1,433,312 million, accounting for 27.61% of GDP growth. In the high-tech industry, Semiconductors, power equipment and electronic components-related industries have grown the most. In addition, the growth of high-tech industries is mainly affected by the innovation of input technology and the improvement of self-sufficiency. The former can improve production efficiency and industrial upgrading, while the latter can improve domestic employment opportunities and industrial structure transformation. Therefore, after the financial crisis, although Taiwan’s economy suffered great economic damage, it also stimulated technological innovation and increased the proportion of domestic industrialization. Nevertheless, under the dual goals of environmental protection and economic growth, how to reduce CO2 emissions is an important issue for Taiwan at present. Empirical evidence shows that the high-tech industry is still subject to the financial crisis and has shown significant growth, which has also increased CO2 emissions. Among them, Semiconductors have increased the most, accounting for more than 90% of the total high-tech. REFERENCES Akadiri, S.S., Lasisi, T.T., Uzuner, G., Akadiri, A.C. (2019), Examining the impact of globalization in the environmental Kuznets curve hypothesis: The case of tourist destination states. Environmental Science and Pollution Research, 26, 12605-12615. Ang, J.B. (2007), CO2 emissions, energy consumption, and output in France. Energy Policy, 35, 4772-4778. Aydin, C., Esen, Ö. (2018), Does the level of energy intensity matter in the effect of energy consumption on the growth of transition economies? Evidence from dynamic panel threshold analysis. Energy Economics, 69, 185-195. Bella, G., Massidda, C., Mattana, P. (2014), The relationship among CO2 emissions, electricity power consumption and GDP in OECD. Journal of Policy Modeling, 36, 970-985. Bölük, G., Mert, M. (2015), The renewable energy, growth and environmental Kuznets curve in Turkey: An ARDL approach. Renewable and Sustainable Energy Reviews, 52, 587-595. Dinda, S. (2004), Environmental Kuznets curve hypothesis: A survey. Ecological Economics, 49, 431-55. Dogan, E. (2015), The relationship between economic growth and electricity consumption from renewable and non-renewable sources: A study of Turkey. Renewable and Sustainable Energy Reviews, 52, 534-546. Doytch, N., Uctum, M. (2016), Globalization and the environmental impact of sectoral FDI Economic Systems. Economic Systems, 40(4), 582-594. Dreher, A. (2006), Does globalization affect growth? Evidence from a new index of globalization. Applied Economics, 38(10), 1091-1110. Farhani, S., Chaibi, A., Rault, C. (2014), CO2 emissions, output, energy consumption, and trade in Tunisia. Economic Modelling, 38, 426-434. Fujita, N., William, E.J. (1997), Employment creation and manufactured exports in Indonesia: 1980-90. Bulletin of Indonesian Economic Studies, 33(1), 103-115. Hong, C.Y., Lee, Y.C., Tsai, M.C., Tsai, Y.C. (2018), Agricultural sector input technical coefficients, demand changes and CO2 emissions after the financial crisis: Environmental input-output growth factor model approach. International Journal of Energy Economics and Policy, 8(6), 339-345. Hong, C.Y., Yen, Y.S., Chien, P.C. (2019), Sources of economic growth and changes in energy consumption: Empirical evidence for Taiwan (2004-2016). International Journal of Energy Economics and Policy, 9(3), 346-352. Jorgenson, A.K., Givens, J.E. (2014), Economic globalization and environmental concern: A multilevel analysis of individuals within 37 nations. Environment and Behavior, 46(7), 848-871. Kraft, J., Kraft, A. (1978), On the relationship between energy and GNP. The Journal of Energy and Development, 3, 401-403. Lee, C.C., Lee, J.D. (2009), Income and CO2 emissions: Evidence from panel unit root and cointegration tests. Energy Policy, 37, 413-23. Li, Z., Xu, N., Yuan, J. (2015), New evidence on trade-environment Table 6: CO2 emissions factors of power system related industries (2011-2016) Classification of industries Changes in factors (a) Changes in domestic final demand (b) Changes in exports (c) Changes in final goods imports (d) Changes in self‑sufficiency (e) Changes in input technology Power generation, transmission and distribution −182,448 −41,059 13,039 1,473 52,221 Battery −3,906 −1,861 3,061 20,922 9,698 Wires, cables and wiring −439,282 −35,733 5,367 −20,313 128,605 Lighting device −32,432 −7,700 −332 519 15,938 Household appliances −21,389 3,132 −3,440 671 24,723 Other power equipment 330,425 −118,941 63,097 536,791 169,247 Professional machinery −779,495 −389,612 222,046 145,935 553,086 Transportation related −13,971 194,834 −59,517 −57,109 404,286 Total −1,142,499 −396,940 243,320 628,889 1,357,805 Unit: Tons Yang, et al.: Decomposition of Growth Factors in High-tech Industries and CO2 Emissions: After the World Financial Crisis in 2008 International Journal of Energy Economics and Policy | Vol 10 • Issue 4 • 2020506 linkage via air visibility. Economics Letters, 128, 72-74. Managi, K., Kumar, S. (2009), Energy price-induced and exogenous technological change: Assessing the economic and environmental outcomes. Resource and Energy Economics, 31(4), 334-353. Njoke, M.L., Wu, Z., Tamba, J.G. (2019), Empirical analysis of electricity consumption, CO2 emissions and economic growth: Evidence from Cameroon. International Journal of Energy Economics and Policy, 9(5), 63-73. Ozturk, I. (2010), A literature survey on energy-growth nexus. Energy Policy, 38(1), 340-349. Ozturk, I., Acaravci, A. (2011), Electricity consumption and real GDP causality nexus: Evidence from ARDL bounds testing approach for 11 MENA countries. Applied Energy, 88, 2885-2892. Payne, J.E. (2010a), Survey of the international evidence on the causal relationship between energy consumption and growth. Journal of Economic Studies, 37, 53-95. Payne, J.E. (2010b), A survey of the electricity consumption-growth literature. Applied Energy, 87, 723-731. Presno, M.J., Landajo, M., González, P.F. (2018), Stochastic convergence in per capita CO2 emissions. An approach from nonlinear stationarity analysis. Energy Economics, 70, 563-581. Saboori, B., Sulaiman, J., Mohd, S. (2012), Economic growth and CO2 emissions in Malaysia: A cointegration analysis of the environmental Kuznets curve. Energy Policy, 51, 184-191. Sunde, T. (2020), Energy consumption and economic growth modelling in SADC countries: An application of the VAR Granger causality analysis. International Journal of Energy Technology and Policy, 16(1), 41-56. Yavuz, N.C., Yilanci, V. (2013), Convergence in per capita carbon dioxide emissions among G7 countries: A TAR panel unit root approach. Environmental and Resource Economics, 54(2), 283-291. You, W., Lv, Z. (2018), Spillover effects of economic globalization on CO2 emissions: A spatial panel approach. Energy Economics, 73, 248-257.