. International Journal of Energy Economics and Policy | Vol 5 • Issue 2 • 2015 385 International Journal of Energy Economics and Policy ISSN: 2146-4553 available at http: www.econjournals.com International Journal of Energy Economics and Policy, 2015, 5(2), 385-401. Review Paper on Economic Growth–Aggregate Energy Consumption Nexus Zaidi Isa, Ahmed R.M. Al Sayed*, Sek Siok Kun School of Mathematical Sciences, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia. *Email: alsayed@siswa.ukm.edu.my ABSTRACT The aim of this study is to survey the empirical studies which interested in detecting the causal relationship between energy consumption (EC) and economic growth, and to provide some recommendations to policymakers for designing the environmental policies and policy implications of effective energy. Our review paper concentrates to make a survey depending on included variables in the studies, thus it has been classified into two groups; bivariate framework and multivariate framework. The results show that the multivariate studies support the feedback hypothesis more than the bivariate studies with (45.7%) and (29.5%) respectively. In contrast of that in neutrality hypothesis, the bivariate framework studies support it with (26.2%) which is more than that in multivariate framework (12.1%) only. In the other hand the results by considering the whole empirical studies in our survey support the hypotheses as the following; (34.3%), (24.0%), (19.7%) and (22.0%) for the feedback, growth, conservation and neutrality hypothesis respectively. Moreover we provide some suggestions for future studies; it should focuses more on new approaches consist the multivariate framework rather than by applying common methods with the same variables in bivariate framework only, which could be solved by adding unprecedented variables such as technology innovation, index investment and environmental quality with applying environmental Kuznets curve. In the analysis should considers the possibility of structural breaks, the coefficients signs, and distinguish between the short and long run causality relationship. And it should include two distinct groups of EC; renewable and nonrenewable energy rather than aggregate or disaggregate energy consumption. Keywords: Economic Growth, Aggregate Energy Consumption, Causality Relationship JEL Classifications: Q4, Q43 1. INTRODUCTION The issue of economic growth and energy consumption (EC) relationship becomes a hot topic and it has been extensively examined by researchers and industrial sectors. In the last four decades, the causal relationship between economic growth (gross domestic product [GDP]) and EC has investigated widely in many empirical researches. Early studies had conducted by Griffin and Gregory (1976), Berndt and Wood (1979), and Berndt (1980, 1990) and they have postulated the substitutability and complementarity between GDP and EC, while Bergman (1988), Jorgenson and Wilcoxen (1993), Kemfert and Welsch (2000), and Smulders and de Nooij (2003) and others, had investigated the effects of energy within a general equilibrium approach. The empirical studies have concentrated on different countries, utilizing a variety of time periods, proxy model variables with applying different methods to detect the relationship between GDP and EC. Moreover the findings of those empirical studies have been reported different results. It appears to be varying on the causality relationships direction and in the long-term versus short-term. Chen et al., (2007) propose that the variation in the results of the previous literatures due to the several changing on the data set, econometric methodologies, different target groups, different characteristics involved the different economic histories and political, different indigenous energy supplies, different political arrangements, different institutional arrangements, different energy policies and different cultures, etc. Karanfil (2008) has expressed that the results in developing countries studies might be not accurate and that due to unrecorded activities into real GDP correctly, subsequently examine the relationship between EC and real GDP may not give reliable results. However most of previous studies have ignored to include other factors in their model study such as environmental quality (EQ) which may have an effect on International Journal of Energy Economics and Policy | Vol 5 • Issue 2 • 2015386 Isa, et al.: Review Paper on Economic Growth–Aggregate Energy Consumption Nexus GDP, knowing that there are few recent studies considered that variable by using CO2 or GHG as proxy variables, they suggest that it plays a vital role in both of GDP and EC. The causality relationship between the GDP and EC is not conclusive to support the policy maker to take their decision. Indeed, realization of the interrelationship and the causality direction between GDP, EC and other factors such as EQ, index investment, capital, and technology innovation are significant in designing and implementation of environmental and energy policies. In light of the aforementioned literatures, the main purpose of this paper is to survey the empirical literatures on the causality relationship between EC and GDP. To best of our knowledge this survey paper is the first paper surveys the relevant literatures on aggregate EC and economics nexus for a period 1978-2014. The remaining parts of this paper is organized as follows; Section 2 illustrates the forth hypotheses which represent the results of the causality relationship between EC and GDP. Section 3 surveys the empirical studies in detecting the causality between EC and GDP by two parts, first part the studies which concentrate into bivariate framework, while the second part focuses into the multivariate framework studies, then the discussion of results. Section 4 provides remarkable conclusion and suggestion for future research. 2. THE FOUR HYPOTHESES REPRESENTING THE RESULTS OF CAUSALITY RELATIONSHIP BETWEEN EC AND ECONOMIC GROWTH In this area of the empirical researches; there are enormous amount of studies focuses on detecting the causality link between GDP and EC, followed by Kraft and Kraft (1978) who investigated the relationship between those variables for USA, and their findings suggest that causality relationship has a significant policy implications. In other hands those studies have applied several techniques to examine the causality direction in both long run and short run into miscellaneous countries. However those empirical studies have failed to acquire unanimous results. Those studies have reported different outcomes, due to that we are going to categorize them into four groups depending on their findings of the causality direction, as same as the classification of hypotheses on the EC-economic growth nexus. First results group shows bidirectional causality between EC and GDP which represented by feedback hypothesis, it postulates a joint effect between EC and GDP, each one of them has effect the other one, the increasing (decreasing) in EC causes an increasing (decreasing) in GDP level respectively and vice versa. Second group asserts the unidirectional causality running from EC to GDP, and it called growth hypothesis, it illustrates that any an increase (decrease) in EC could causes an increase (decrease) in GDP level; therefore EC has a vital role in production process of GDP. While the third group emphasizes the existence of the unidirectional causality running from GDP to EC which called conservation hypothesis, the increase in GDP may cause an increase on EC. Finally the forth group supports the absence of relationship between GDP and EC and it called neutrality hypothesis, it suggests that there is no significant effect from EC into GDP and vice versa (Ozturk, 2010). 3. THE LITERATURES SURVEY OF CAUSALITY EC AND ECONOMIC GROWTH NEXUS As we have mentioned earlier that there are several empirical studies have interested and attempted to determine the casual relationship between GDP and EC, while the findings of those studies have been intermingled and conflicted. Due to that some studies provide the causality relationship running from GDP to EC, but others showed the reverse that causality relationship running from EC to GDP. However some found that there is bi-directional causality between the two variables while others support that there is no causality relationship between those variables. In this section, we extend a chronological list of the empirical literature on the causality relationship between GDP and EC, providing the applied methodologies, target countries, period spanning, findings, published year, and author name. While most of previous studies have focused in that causality relationship in specific country or cross countries, and in other way most of them have concentrated on industrialized and developed countries only. We are going to divide the survey literatures into two major groups by variables included in the study; First group involved the bivariate framework studies as in Table 1, while the second group shows the multivariate framework as shown in Table 2. Note that our literature survey concentrates on the studies which taken the aggregated EC as a proxy of EC rather than the disaggregate energy levels, to avoid the bias results. 3. 1. Bivariate Framework Studies Depending on the Results of Hypotheses This part of literature includes the empirical studies which interested into detect the casual relationship between two variables only; economic growth GDP and EC. The direction of causality has been counted in each study according to hypothesis. The bivariate framework studies has summarized in Table 1. 3.1.1 Feedback hypothesis shows bidirectional causality between EC and GDP The empirical studies which support the feedback hypothesis by specific country and cross countries have been summarized in Table 1. The following studies provide bidirectional causality between EC and GDP on a country specific; Hwang and Gum (1992) focuses his study in Taiwan for period spanning from 1961 to 1990 by using Granger causality method. Zarnikau (1997) his target group is USA country during the period 1970-1992 by employed the Granger causality. Jumbe (2004) his analysis included data spanning from 1970 to 1999 of Malawi country. Erdal et al. (2008) concentrate their study in Turkey for the period 1970 to 2006 by using pair-wise Granger causality and Johansen co-integration. Belloumi (2009) focuses in Tunisia for monthly data from 1971 to 2004 by applying Granger causality and vector error correction model (VECM) approaches. Zhang (2011) focuses in Russia over the period 1970-2008 by using time-varying co- integration and Toda Yamamoto (TY) causality test. Zhang and Xu (2012) his study conducted in China over the period 1995 to 2008 by using panel causality tests. Shahiduzzaman and Alam (2012) concentrate in Australia for times series 1960-2009 by employing International Journal of Energy Economics and Policy | Vol 5 • Issue 2 • 2015 387 Isa, et al.: Review Paper on Economic Growth–Aggregate Energy Consumption Nexus Author Methodology Year Scope Findings and Results Kraft and Kraft (1978) Granger and Sims causality 1947-1974A USA GDP→EC Akarca and Long (1980) Sims causality 1950-1970A USA GNP ― EC Yu and Choi (1985) Sims and granger causality 1947-1979A 1950-1976A 1950-1976A 1950-1976A 1954-1976A USA UK Poland Philippines South Korea GNP ― EC EC→GNP GNP ― EC EC→GNP GNP→EC Erol and Yu (1987a) Sims and granger causality 1950-1982A 1950-1982A 1950-1982A 1950-1982A 1950-1980 1950-1982A Japan Germany Italy Canada France UK EC↔GNP GNP→EC GNP→EC EC→GNP GNP ― EC GNP ― EC Nachane et al. (1988) EG 1950-1985A Argentina Brazil Chile Colombia Greece Guatemala India Israel Portugal Mexico Venezuela France Germany Italy Japan UK CEC→GDP CEC↔GDP CEC→GDP CEC↔GDP CEC→GDP CEC→GDP CEC↔GDP CEC↔GDP CEC→GDP CEC→GDP CEC↔GDP CEC→GDP CEC↔GDP CEC→GDP CEC↔GDP CEC→GDP Abosedra and Baghestani (1991) Granger causality 1947-1987A USA GNP→EC Hwang and Gum (1992) Granger causality 1961–1990A Taiwan GNP↔EC Yu and Jin (1992) Granger causality 1974–1990A USA GDP― EC Ebohon (1996) Granger causality 1960-1981A 1960-1984A Tanzania Nigeria GDP↔EC GDP↔EC Masih and Masih (1996) JJ and VDC 1955-1990A 1955-1990A 1960-1990A 1955-1990A 1960-1990A 1955-1991A India Pakistan Indonesia Malaysia Singapore Philippines GNP→EC GNP↔EC GNP→EC GNP ― EC GNP ― EC GNP ― EC Zarnikau (1997) Granger causality 1970-1992A USA GNP↔EC Glasure and Lee (1998) EG 1961-1990A South Korea Singapore GDP↔EC GDP↔EC Yang (2000) EG 1954-1997A Taiwan EC↔GDP Soytas et al. (2001) Co-integration, Granger causality 1960-1995A Turkey EC→GDP Fatai et al. (2002) Granger causality, ARDL and TY 1960-1999A New Zealand GDP ― EC Ghosh (2002) Cointegration 1950-1997A India GDP→EC Soytas and Sari (2003) JJ and VDC 1950-1990A 1950-1992A 1950-1992A 1950-1992A 1960-1992A 1953-1991A 1950-1992A 1953-1991A 1965-1994A Argentina Canada France Germany Indonesia Italy Japan Korea Poland GDP↔EC GDP ― EC EC→GDP EC→GDP GDP ― EC GDP→EC EC→GDP GDP→EC GDP ― EC Table 1: The summary of empirical studies on EC and GDP nexus for bivariate framework (Contd...) International Journal of Energy Economics and Policy | Vol 5 • Issue 2 • 2015388 Isa, et al.: Review Paper on Economic Growth–Aggregate Energy Consumption Nexus Author Methodology Year Scope Findings and Results 1950-1992A 1950-1992A 1950-1992A Turkey UK USA GDP↔EC GDP ― EC GDP ― EC Altinay and Karagol (2004) Granger causality 1950-2000A Turkey GDP ― EC Fatai et al. (2004) Granger-causality, TY, ARDL and JJ 1960-1999A Australia New Zealand India Indonesia Thailand Philippines GDP→EC GDP→EC EC→GDP EC→GDP EC↔GDP EC↔GDP Wolde-Rufael (2004) TY 1952-1999A Shanghai EC→GDP Jumbe (2004) Cointegration 1970-1999A Malawi GDP↔EC Wolde-Rufael (2005) ARDL and TY 1971-2001A Algeria Benin Cameroon DR Congo Rep Congo Egypt Gabon Ghana Ivory Coast Kenya Morocco Nigeria Senegal South Africa Sudan Togo Tunisia Zambia Zimbabwe GDP→EC GDP ― EC EC→GDP GDP→EC GDP ― EC GDP→EC GDP↔EC GDP→EC GDP→EC GDP ― EC EC→GDP EC→GDP GDP ― EC GDP ― EC GDP ― EC GDP ― EC GDP ― EC GDP↔EC GDP ― EC Lee and Chang (2005) JJ 1954-2003A Taiwan EC↔GDP Al-Iriani (2006) Pedroni panel cointegration 1971-2002A Panel of 6 countries in Middle East GDP→EC Chontanawat et al. (2006) JJ and dynamic panel estimation 1960-2000A OECD countries Australia Austria Belgium Canada Czech Denmark Finland France Germany Greece Hungary Iceland Ireland Italy Japan Korea Luxembourg Mexico The Netherlands New Zealand Norway Poland GDP→EC EC→GDP EC→GDP GDP→EC EC→GDP EC→GDP GDP→EC GDP↔EC GDP↔EC GDP↔EC GDP↔EC GDP↔EC EC→GDP GDP↔EC GDP↔EC EC→GDP GDP ― EC EC→GDP EC→GDP GDP↔EC GDP↔EC EC→GDP Table 1: (Continued...) (Contd...) International Journal of Energy Economics and Policy | Vol 5 • Issue 2 • 2015 389 Isa, et al.: Review Paper on Economic Growth–Aggregate Energy Consumption Nexus Author Methodology Year Scope Findings and Results Portugal Slovakia Spain Sweden Switzerland Turkey UK USA GDP↔EC GDP↔EC GDP→EC GDP→EC EC→GDP GDP ― EC GDP ― EC GDP ― EC 1971-2000A Non-OECD Albania GDP→EC Algeria GDP→EC Angola GDP↔EC Argentina GDP↔EC Bahrain GDP ― EC Bangladesh EC→GDP Benin GDP ― EC Bolivia GDP→EC Brazil GDP↔EC Brunei GDP↔EC Bulgaria GDP→EC Cameroon GDP ― EC Chile EC→GDP China GDP ― EC Colombia EC→GDP Congo GDP ― EC Congo Republic EC→GDP Costa Rica GDP→EC Cote d’Ivoire GDP ― EC Cuba GDP→EC Cyprus EC→GDP Dominican Republic EC→GDP Ecuador GDP ― EC Egypt EC→GDP El Salvador GDP→EC Ethiopia GDP→EC Gabon GDP ― EC Ghana GDP↔EC Gibraltar GDP↔EC Haiti GDP ― EC Honduras GDP ― EC Hong Kong GDP ― EC India GDP ― EC Iran GDP↔EC Iraq GDP ― EC Israel EC→GDP Jamaica GDP ― EC Jordan GDP↔EC Kenya EC→GDP Kuwait GDP↔EC Lebanon GDP↔EC Libya GDP ― EC Malaysia GDP ― EC Malta GDP ― EC Morocco GDP↔EC Mozambique GDP↔EC Myanmar GDP↔EC Nepal EC→GDP Nicaragua GDP ― EC Nigeria GDP ― EC Oman EC→GDP Pakistan GDP ― EC Panama GDP→EC Paraguay GDP→EC Peru GDP→EC Table 1: (Continued...) (Contd...) International Journal of Energy Economics and Policy | Vol 5 • Issue 2 • 2015390 Isa, et al.: Review Paper on Economic Growth–Aggregate Energy Consumption Nexus (Contd...) Author Methodology Year Scope Findings and Results Philippines EC→GDP Qatar GDP↔EC Romania GDP↔EC Saudi Arabia GDP→EC Senegal GDP ― EC Singapore GDP ― EC Sri Lanka GDP ― EC Sudan GDP↔EC Taiwan GDP↔EC Tanzania GDP ― EC Thailand GDP→EC Togo GDP ― EC Trinidad GDP↔EC Tunisia GDP↔EC UAE GDP↔EC Uruguay EC→GDP Venezuela GDP→EC Vietnam EC→GDP Yemen GDP↔EC Zambia GDP ― EC Zimbabwe GDP→EC Lee (2006) TY 1960-2001A 1965-2001A 1960-2001A 1971-2001A 1960-2001A 1960-2001A 1960-2001A 1960-2001A 1960-2001A 1960-2001A 1960-2001A Belgium Canada France Germany Italy Japan The Netherlands Sweden Switzerland UK USA EC→GDP EC→GDP GDP→EC GDP ― EC GDP→EC GDP→EC EC→GDP GDP ― EC EC→GDP GDP ― EC GDP↔EC Francis et al. (2007) EG 1971-2002A Haiti Jamaica Trinidad and Tobago GDP↔EC GDP↔EC GDP↔EC Lise and Montfort (2007) EG 1970-2003A Turkey GDP→EC Mehrara (2007a) Pedroni panel cointegration 1971-2002A Panel of 7 countries in middle east GDP→EC Mehrara (2007b) TY and JJ 1971-2002A Iran Kuwait Saudi Arabia GDP→CEC GDP→CEC CEC→GDP Ang (2007) Cointegration, VECM 1960-2000A France EC→GDP Ho and Siu (2007) Cointegration, VECM 1966–2002A Hong Kong EC→GDP Chiou et al. (2008) JJ; Baek and Brock non-linear Granger causality 1954-2006A 1971-2003A 1971-2003A 1971-2003A 1971-2003A 1971-2003A 1971-2003A 1971-2003A 1960-2003A Taiwan Hong Kong Singapore Korea Malaysia Indonesia Philippines Thailand USA EC→GDP EC→GDP GDP→EC GDP ― EC GDP ― EC GDP↔EC GDP→EC GDP ― EC GDP ― EC Ang (2008) JJ and VECM 1971-1999A Malaysia GDP→EC Erdal et al. (2008) Pair-wise Granger causality and JJ 1970-2006A Turkey GDP↔EC Akinlo (2008) ARDL 1980-2003A Gambia Ghana Sudan Zimbabwe Congo GDP→EC GDP→EC GDP→EC GDP→EC GDP→EC Table 1: (Continued...) International Journal of Energy Economics and Policy | Vol 5 • Issue 2 • 2015 391 Isa, et al.: Review Paper on Economic Growth–Aggregate Energy Consumption Nexus (Contd...) Author Methodology Year Scope Findings and Results Senegal Cameroon Coted’ Ivories Nigeria Kenya Togo GDP ― EC GDP ― EC GDP ― EC GDP ― EC GDP ― EC GDP ― EC Belloumi (2009) Granger causality and VECM 1971-2004M Tunisia GDP↔EC Zhang and Cheng (2009) Granger causality 1960-2007A China GDP→EC Bowden and Payne (2009) TY 1949-2006A United States GDP ― EC Ozturk et al. (2010) Pedroni panel cointegration 1971-2005A 51 countries: Low income 14 Lower middle 24 Upper middle 13 GDP→EC GDP↔EC GDP↔EC Ozturk and Acaravci (2010) ARDL and ECM 1980-2006A Albania Bulgaria Hungary Romania GDP ― EC GDP ― EC GDP↔EC GDP ― EC Bartleet and Gounder (2010) ARDL cointegration, ECM causality 1960-2004A New Zealand GDP→EC Tsani (2010) TY 1960-2006A Greece EC→GDP Warr and Ayres (2010) JJ, cointegration, VECM 1946-2000A USA EC→GDP Hossain and Saeki (2011) Panel causality (Granger, EG and GMM) 1971-2007A Panel of South Asian countries EC→GDP Zhang (2011) TY and Time-varying cointegration 1970-2008A Russia GDP↔EC Eggoh et al. (2011) Panel cointegration, Panel causality 1970-2006A African countries 21 Energy exporters 11 Energy importers 10 GDP↔EC GDP↔EC GDP↔EC Belke et al. (2011) Dynamic Panel causality 1981-2007A Panel of 25 OECD GDP↔EC Lau et al. (2011) Granger causality test and FMOLS 1980 – 2006A Panel of 17 Asian countries GDP→EC Abid and Sebri (2011) VECM 1980-2007A Tunisia GDP↔EC Sadorsky (2012) Panel cointegration, Panel causality 1980-2007A Panel of 7 countries in South American GDP↔EC Narayan and Popp (2012) Panel cointegration, Panel causality 1980-2006A Global panel 93 Western European 20 Asian panel 17 Latin American 17 Middle East panel 12 African panel 25 G6 panel 6 GDP↔EC EC→GDP EC→GDP EC→GDP GDP ― EC GDP↔EC EC→GDP Souhila and Kourbali (2012) Threshold cointegration and Granger causality 1965-2008A Algeria GDP→EC Fuinhas and Marques (2012) ARDL cointegration, and ECM 1965-2009A Portugal Italy Greece Spain Turkey GDP↔EC GDP↔EC GDP↔EC GDP↔EC GDP↔EC Pirlogea and Cicea (2012) Co-integration tests 1990-2010A Romania Spain EC→GDP EC→GDP Zhang and Xu (2012) Panel cointegration, Panel causality 1995-2008A China GDP↔EC Shahiduzzaman and Alam (2012) JJ, cointegration, and VECM 1960-2009A Australia GDP↔EC Wesseh Jr and Zoumara (2012) Parametric and non-parametric Granger causality approaches 1980-2008A Liberian GDP↔EC Ocal and aslan (2013) ARDL and TY 1990-2010A Turkey GDP→REC Table 1: (Continued...) International Journal of Energy Economics and Policy | Vol 5 • Issue 2 • 2015392 Isa, et al.: Review Paper on Economic Growth–Aggregate Energy Consumption Nexus Author Methodology Year Scope Findings and Results Herrerias et al. (2013) Panel cointegration techniques 1995-2009A Chinese GDP→EC Dergiades et al. (2013) Parametric and non-parametric test 1960-2008A Greece EC→GDP The unidirectional causality, bidirectional causality and no causality between EC and GDP have been represented by the symbols →, ↔ and ― respectively. For the abbreviations of methods; TY: Toda-Yamamoto causality test, JJ: Johansen-Juselius. ARDL: Autoregressive distributed lag bounds test. EG: Engle-Granger. VDC: Forecast error variance decomposition. VECM: Vector error correction model. ECM: Error correction model. PECM: Panel error-correction model. GMM: Generalized method of moments. While the abbreviations of main variables and scope; GNP or GDP represent the economic growth. EC: Energy consumption, CEC: Commercial energy consumption. G6: France, West Germany, Italy, Japan, the United Kingdom and the United States. OECD: Organization for economic co-operation and development countries, GDP: Gross domestic product, GNP: Gross national product Table 1: (Continued...) Author Methodology Year Scope Additional variables Findings anf Results Yu and Hwang (1984) Sims and Granger causality 1947-1979A USA EMP GNP ― EC EC→EMP Stern (1993) Granger causality and VAR 1947-1990A USA EMP and capital EC→GDP Cheng (1996) EG 1947-1990A USA Capital EC ― GNP Cheng (1997) EG 1963-1993A 1949-1993A 1952-1993A Brazil Mexico Venezuela Capital EC→GDP EC ― GDP EC ― GDP Cheng and Lai (1997) EG 1955-1993A Taiwan EMP GDP→EC EC→EMP Masih and Masih (1997) JJ, VDC and IRF 1961-1990A Korea Taiwan Consumer prices GDP↔EC GDP↔EC Cheng (1998) JJ and Hsiao’s Granger causality 1952-1995A Japan Capital and EMP GNP→EC Masih and Masih (1998) JJ, VDC and IRF 1955-1991A Thailand Sri Lanka Consumer prices EC→GDP EC→GDP Cheng (1999) JJ, Co-integration, ECM and Granger causality 1952-1995A India Capital and population GNP→EC Asafu-Adjaye (2000) JJ 1973-1995A 1973-1995A 1971-1995A 1971-1995A India Indonesia Thailand Philippines Consumer prices EC→GDP EC→GDP EC↔GDP EC↔GDP Stern (2000) JJ and Granger causality 1948-1994A USA EMP and capital EC→GDP Aqeel and Butt (2001) EG 1955-1996A Pakistan EMP GDP→EC Glasure (2002) JJ and VDC 1961-1990A Korea Energy prices EC↔GDP Hondroyiannis et al. (2002) JJ and VECM 1960-1999A Greece Consumer prices EC↔GDP Ghali and El-Sakka (2004) JJ, VDC and VEC 1961-1997 A Canada Capital and EMP EC↔GDP Oh and Lee (2004a) JJ, Granger causality and VECM 1970-1999 A Korea Capital and labor EC↔GDP Oh and Lee (2004b) JJ 1981-2000Q South Korea Capital, labor and real energy prices GDP→EC Paul and Bhattacharya (2004) EG and JJ 1950-1996A India Population and capital EC↔GDP Lee (2005) Pedroni panel cointegration 1975-2001A Panel of 18 Developing countries Capital EC→GDP Soytas and Sari (2006a) TY and VDC 1971-2002A China labor force and capital EC―GDP Soytas and Sari (2006b) JJ and VDC 1960-2004A 1970-2002A 1971-2002A 1960-2004A 1960-2004A 1960-2004A 1960-2004A Canada France Germany Italy Japan UK USA Labor force and real gross fixed capital formation EC↔GDP EC→GDP EC↔GDP EC↔GDP EC↔GDP EC↔GDP EC→GDP Climent and Pardo (2007) JJ 1984-2003Q Spain Consumer prices and employment EC↔GDP Table 2: The summary of empirical studies on EC and GDP for multivariate framework (Contd...) International Journal of Energy Economics and Policy | Vol 5 • Issue 2 • 2015 393 Isa, et al.: Review Paper on Economic Growth–Aggregate Energy Consumption Nexus (Contd...) Author Methodology Year Scope Additional variables Findings anf Results Jobert and Karanfil (2007) JJ 1960-2003A Turkey IVA EC―GNP EC―IVA Mahadevan and Asafu-Adjaye (2007) Pedroni panel cointegration; JJ and VECM 1971-2002A Exporters developed Australia Norway UK Exporters developing Argentina Indonesia Kuwait Malaysia Nigeria Saudi Arabia Venezuela Importers developed Japan Sweden USA Importers developing Ghana India Senegal South Africa South Korea Singapore Thailand Consumer prices EC↔GDP EC↔GDP EC↔GDP EC↔GDP EC↔GDP EC↔GDP EC↔GDP EC↔GDP EC↔GDP EC↔GDP EC↔GDP EC↔GDP EC↔GDP EC↔GDP EC↔GDP EC↔GDP EC→GDP EC↔GDP EC→GDP EC→GDP EC↔GDP EC→GDP EC↔GDP EC→GDP Narayan and Smyth (2007) Pedroni panel cointegration 1972-2002A Panel of 7 western countries Capital EC→GDP Soytas et al. (2007) TY and VDC 1960-2000A USA Real gross fixed capital formation, labor force and CO2 EC ― GDP Zachariadis (2007) JJ, ARDL and TY 1960-2004A Canada France Germany Italy Japan UK USA IVA All: GDP→EC JJ: EC↔GDP ARDL: EC→GDP TY: EC ― GDP JJ: EC↔GDP ARDL: GDP→EC TY: EC ― GDP JJ: EC↔GDP ARDL: EC↔GDP TY: EC ― GDP JJ: EC↔GDP ARDL: EC↔GDP TY: EC→GDP All: GDP→EC All: EC ― GDP Zamani (2007) EG 1967-2003A Iran IVA and AVA GDP→EC Yuan et al. (2008) JJ and IRF 1963-2005A China Capital, employment EC↔GDP Huang et al. (2008) Dynamic panel estimation, GMM and VAR 1972-2002A Low income Middle income High income Over all panel Capital stock+labor force EC ― GDP GDP→EC GDP→EC EC↔GDP Lee and Chang (2008) Pedroni panel cointegration 1971-2002A Asian panel, APEC, ASEAN Capital stock and labor force EC→GDP EC→GDP EC→GDP Table 2: (Continued...) International Journal of Energy Economics and Policy | Vol 5 • Issue 2 • 2015394 Isa, et al.: Review Paper on Economic Growth–Aggregate Energy Consumption Nexus (Contd...) Author Methodology Year Scope Additional variables Findings anf Results Soytas and Sari (2008) TY and VDC 1960-2000A Turkey Real gross fixed capital formation, labor force and CO2 EC ― GDP Payne (2009) TY 1949-2006A USA Real gross fixed capital formation and Employment EC ― GDP Apergis and Payne (2009) Pedroni panel cointegration 1980-2004A Panel of 6 South America countries Real gross fixed capital formation and labor force EC→GDP Costantini and Martini (2010) VECM 1960-2005A 71 countries 26 OECD 45 non-OECD Energy prices GDP→EC EC↔GDP GDP→EC Acaravci and Ozturk (2010) Cointegration, ARDL 1960e2005 19 Europe countries Austria Belgium Denmark Finland France Germany Greece Hungary Iceland Ireland Italy Luxembourg Netherlands Norway Portugal Spain Sweden Switzerland United Kingdom CO2 EC ― GDP EC ― GDP EC ― GDP EC ― GDP EC ― GDP EC ― GDP GDP→EC EC ― GDP EC ― GDP GDP→EC EC ― GDP EC ― GDP EC ― GDP EC ― GDP EC ― GDP EC ― GDP EC ― GDP EC↔GDP EC ― GDP Apergis and Payne (2010) Cointegration and ECM 1985-2005A 20 OECD countries Capital and labor force EC↔GDP Odhiambo (2010) Cointegration, ARDL and ECM 1972-2006A South Africa Kenya congo Energy prices EC→GDP EC→GDP GDP→EC Ozturk and Acaravci (2010) Cointegration, ARDL 1968-2005A Turkey CO2, employment ratio EC ― GDP Hatzigeorgiou et al. (2011) cointegration, JJ and VECM 1977-2007A Greece CO2 GDP→EC Pao and Tsai (2011) Cointegration panel causality 1980-2007A panel of 4 BRIC countries FDI and CO2 EC↔GDP Hossain (2011) Granger causality and EG 1971-2007A Panel of 9 NIC CO2 GDP→EC Wang et al. (2011) Panel cointegration, VECM 1995-2007A China CO2 EC↔GDP Alam et al. (2011) Dynamic modeling 1971-2006A India Fixed capital stock, labor force and CO2 EC ― GDP Farhani and Ben (2012). Panel cointegration, Panel causality 1973-2008A 15 MENA countries CO2 GDP→EC Hossein et al. (2012) EG and ECM 1980-2008A Iran Iraq Qatar UAE Saudi Arabia Algeria Energy price GDP→EC GDP→EC GDP→EC GDP→EC GDP→EC EC→GDP Table 2: (Continued...) International Journal of Energy Economics and Policy | Vol 5 • Issue 2 • 2015 395 Isa, et al.: Review Paper on Economic Growth–Aggregate Energy Consumption Nexus Author Methodology Year Scope Additional variables Findings anf Results Angola Ecuador Kuwait Libya Nigeria Venezuela EC→GDP EC→GDP EC→GDP EC→GDP EC→GDP EC→GDP Shahbaz et al. (2012) ARDL and VECM 1972-2011A Pakistan Capital and labor EC↔GDP EC↔GDP Al-mulali and Che Sab (2012) Panel cointegration, Panel causality 1980-2008A Panel of 30 Sub-Saharan African countries Financial development and CO2 EC↔GDP Abalaba, and Dada, (2013) ECM and JJ 1971-2010A Nigeria Financial development, monetary policy rate and consumer prices EC ― GDP Saboori and Sulaiman (2013a) ARDL and JJ 1980-2009 A Malaysia CO2 EC↔GDP Saboori and Sulaiman (2013b) ARDL and VECM 1971-2008 A Indonesia Malaysia Philippines Singapore Thailand CO2 EC↔GDP EC↔GDP EC↔GDP GDP→EC GDP→EC Alkhathlan and Javid (2013) ARDL, VECM 1980-2011A Saudi Arabia CO2 EC ― GDP Yang, and Zhao (2014) Granger causality and DAG 1979-2008A India CO2 EC→GDP EC→CO2 The unidirectional causality, bidirectional causality and no causality between EC and GDP have been represented by the symbols →, ↔ and ― respectively. For the Abbreviations of methods; TY: Toda-Yamamoto causality test, JJ: Johansen-Juselius, ARDL: Autoregressive distributed lag bounds test. EG: Engle-Granger. VDC: Forecast error variance decomposition. VECM: Vector error correction model. ECM: Error correction model. PECM: Panel error-correction model. GMM: Generalized method of moments. While the abbreviation of main variables and scope; GNP or GDP represent the economic growth. EC: Energy consumption, CEC: Commercial energy consumption. AVA: Agricultural value added. IVA: Industrial value added. CO2: Carbon dioxide emissions. EMP: Employment. FDI: Foreign direct investment. NIC: Newly industrialized countries; Iran, Israel, Kuwait, Oman, Saudi Arabia and Syria. BRIC countries: Brazil, Russia, India and China. OECD: Organization for Economic Co-operation and Development countries. APEC: Asia-Pacific Economic Cooperation. ASEAN: Association of Southeast Asian Nations, GDP: Gross domestic product, GNP: Gross national product Table 2: (Continued...) Johansen co-integration and VECM causality tests. Wesseh Jr and Zoumara (2012) interested in Liberian over the period 1980-2008 by applying parametric and non-parametric Granger causality approaches. In the other hand there are some studies support the bidirectional causality relationship between EC and GDP by considering several countries in one panel in analysis such as; Eggoh et al. (2011) their analysis included 21 African countries, 10 of them are energy exporters, while 11 are energy importers countries over the period 1970-2006 by using panel causality. Belke et al. (2011) covered 25 organization for economic co- operation and development countries during the period 1981-2007 by using dynamic panel causality. Sadorsky (2012) concentrates his analysis in 7 countries of South American for annual time series data 1980-2007 by applying panel causality. Ozturk et al. (2010) have included 51 countries in his analysis and he divided them into three groups low income, lower middle income and upper middle income, the bidirectional causality relationship found in panels of (lower and upper) middle income countries. Narayan and Popp (2012) used 93 countries in the analysis into one panel and the findings support the feedback hypothesis. Furthermore there are several studies support bidirectional causality between EC and GDP in some individual country of their cross countries analysis such as in; Erol and Yu (1987) the bidirectional causality relationship has noted in Japan only, while Nachane et al. (1988) existed it in Brazil, Colombia, India, Israel, Venezuela, Germany and Japan. Ebohon (1996) supports that causality relationship in Tanzania and Nigeria. Masih and Masih (1996) found it in Pakistan only. Glasure and Lee (1998) found it in South Korea and Singapore. Soytas and Sari (2003) suggest that it existed in Turkey only. Wolde-Rufael (2005) showed it in Gabon and Zambia. Chontanawat et al. (2008) support that in France, Germany, Greece, Hungary, Iceland, Italy, Japan, New Zealand, Norway, Portugal, Slovakia, Angola, Argentina, Brazil, Brunei, Ghana, Gibraltar, Iran, Jordan, Kuwait, Lebanon, Morocco, Mozambique, Myanmar, Qatar, Romania, Sudan, Taiwan, Trinidad, Tunisia, UAE and in Yemen. Lee (2006) found it in USA only. Francis et al. (2007) support it in Haiti, Jamaica and Trinidad. Chiou-Wei et al. (2008) suggest that it is exist in Indonesia. Fuinhas and Marques (2012) resulting it in the all countries of their study; Portugal, Italy, Greece, Spain and Turkey. 3.1.2. Growth hypothesis asserts the unidirectional causality running from EC to GDP Furthermore many empirical studies support the growth hypothesis. First we start with studies which provide a unidirectional causality running from EC to GDP onto country specific such as Soytas et al. (2001) concentrates in Turkey with annual time series data 1960-1995 and he used cointegration and Granger causality in the analysis. Ang (2007) interested in France during the period 1960-2000 by using cointegration and VECM approach in his analysis. Ho and Siu (2007) focused in Hong Kong region by applying Cointegration and VECM in the annual data spanning from 1966 to 2002. Tsani (2010) used TY causality test in annual data 1960-2006 in Greece. Warr and Ayres (2010) focus is USA International Journal of Energy Economics and Policy | Vol 5 • Issue 2 • 2015396 Isa, et al.: Review Paper on Economic Growth–Aggregate Energy Consumption Nexus by using the Johansen cointegration causality and VECM in their analysis over the annual period 1946 to 2000. Dergiades et al. (2013) focused in Greece by using annual data from 1960 to 2008 and employing Parametric and non-parametric test. However there are few studies support the growth hypothesis by one panel countries such as; Hossain and Saeki (2011) included several Asian countries in one panel over the period 1971-2007 by using Granger causality, Engle-Granger (EG) and generalized method of moments (GMM). While in Narayan and Popp (2012) study, they included several countries panels, the growth hypothesis has existed in; Western European panel which involved 20 countries, and in other panel consisted of 17 countries of Asian, panel of 17 Latin American countries and 6 countries of G6. In the other hand there are some empirical studies support the growth hypothesis in individual country such as; Erol and Yu (1987) it has existed in Canada. Nachane et al. (1988) study, it has resulted in Argentina, Chile, Greece, Guatemala, Portugal, Mexico, France, Italy and UK. Soytas and Sari (2003) found it in France, Germany and Japan. Wolde-Rufael (2005) found it in Cameroon, Morocco and Nigeria. Chontanawat et al. (2006) support the growth hypotheses in the following countries; Austria, Belgium, Czech, Denmark, Ireland, Korea, Mexico, Netherlands, Poland, Switzerland, Bangladesh, Chile, Colombia, Congo, Cyprus, Dominican Republic, Egypt, Israel, Kenya, Nepal, Oman, Philippines, Uruguay and Vietnam. Lee (2006) found it in Belgium, Canada, Netherlands and Switzerland. Mehrara (2007a) support it in Saudi Arabia. Chiou-Wei et al. (2008) showed it in Taiwan and Hong Kong. While Pirlogea and Cicea (2012) support it in Romania and Spain. 3.1.3. Conservation hypothesis emphasizes the unidirectional causality running from GDP to EC In addition there are several studies providing the conservation hypothesis. First we start with studies which provide a unidirectional causality relationship running from EC to GDP on a country specific such as; Kraft and Kraft (1978) study and in Abosedra and Baghestani (1991) study, they used annual data from 1947-1974 and 1947-1987 respectively in same country USA by applying same method Granger and Sims causality. Ghosh (2002) focused in India over the period 1950-1997. Lise and Montfort (2007) interested in Turkey during the period 1970-2003 by applying EG method. Ang (2008) concentrated in Malaysia during 1971-1999 by using Johansen cointegration and VECM approaches. Zhang and Cheng (2009) focused in China over the period 1960-2007 by employing Granger causality. Souhila and Kourbali (2012) interested in Algeria over the time period 1965-2008 by using the threshold cointegration and Granger causality tests. Ocal and aslan (2013) interested in Turkey over the period 1990-2010 by employing autoregressive distributed lag (ARDL) and TY approaches. Herrerias et al. (2013) focused in Chinese for annual data from 1995 to 2009 by using panel cointegration techniques. However there are some studies support the growth hypothesis by using panel countries analysis such as; Al-Iriani (2006) his study covered six countries from middle east in one panel for annual data spanning from 1971 to 2002 by employing Johansen- Juselius and dynamic panel estimation. And Mehrara (2007a) his study involved seven countries from middle east in one panel with annual data spanning from 1971 to 2002 by employing pedroni panel cointegration. Ozturk et al. (2010) his study contain from several panels of countries, one of them represented 14 countries in low income group, and by using panel cointegration method for annual data from 1971 to 2005 the finding support Conservation hypothesis. Lau et al. (2011) examined the relationship between GDP and EC in panel of 17 Asia countries. In the other hand there are some empirical studies support the Conservation hypothesis in individual country such as; Erol and Yu (1987) has existed it in Germany and in Italy. Masih and Masih (1996) found it in India and in Indonesia. Soytas and Sari (2003) provided it in Italy and in Korea. Wolde-Rufael (2005) supports it in Algeria, Congo, Egypt, Ghana and Ivory Coast. Chontanawat et al. (2006) have found it in Australia, Canada, Finland, Spain, Sweden, Albania, Algeria, Bolivia, Bulgaria, Costa Rica, Cuba, El Salvador, Ethiopia, Panama, Paraguay, Peru, Saudi Arabia, Thailand, Venezuela and Zimbabwe. Lee (2006) supports it in France, Italy and in Japan. Mehrara (2007a) found it in Iran and in Kuwait. Chiou-Wei et al. (2008) supports it in Singapore and in Philippines. Akinlo (2008) found it in Gambia, Ghana, Sudan, Zimbabwe and Congo. 3.1.4. Neutrality hypothesis supports the absence of causality relationship between GDP and EC Moreover it has noted clearly among the empirical researches some finding supports the neutrality hypothesis, which means no relationship between EC to GDP. We are going to illustrate them by starting on a country specific studies such as; Akarca and Long (1980) concentrates in USA over the period 1950-1970 by applying Sims causality. Yu and Jin (1992) interested in USA by using Co- integration and Granger causality into annual data spanning from 1974 to 1990. Fatai et al. (2002) focused in New Zealand over the period 1960-1999 by using TY Granger causality and ARDL. Altinay and Karagol (2004) they focused in Turkey over the period 1950-2000 by applying Hsiao’s version of Granger causality. Bowden and Payne (2009) in USA by using TY causality test in annual data spanning from 1949 to 2006. However we have not met studies has taken several countries in one panel into their analysis except one study for middle east panel contain of 12 countries for Narayan and Popp (2012) study. In the other hand there are some empirical studies support the neutrality hypothesis in individual country of their studies such as; Erol and Yu (1987) support it in France and UK. Masih and Masih (1996) found it in Malaysia, Singapore and Philippines. Soytas and Sari (2003) found it in Canada, Indonesia, Poland, UK and USA. Wolde-Rufael (2005) supports it in Benin, Congo, Kenya, Senegal, South Africa, Sudan, Togo, Tunisia and Zimbabwe. Chontanawat et al. (2008) support the neutrality hypothesis in Luxembourg, Turkey, UK, USA, Bahrain, Benin, Cameroon, China, Congo, Cote d’Ivoire, Ecuador, Gabon, Haiti, Honduras, Hong Kong, India, Iraq, Jamaica, Libya, Malaysia, Malta, Nicaragua, Nigeria, Pakistan, Senegal, Singapore, Sri Lanka, Tanzania, Togo and Zambia. Lee (2006) found it in Germany, Sweden and UK. Chiou et al. (2008) found it in Korea, Malaysia, Thailand and USA. Akinlo (2008) support it in Senegal Cameroon, Coted’Ivoire, Nigeria Kenya and Togo. Ozturk and Acaravci (2010) support it Albania, Bulgaria and Romania. 3.2. Multivariate Framework Studies Depending on the Results of Hypotheses Nevertheless, some of authors claim that the bivariate analysis has resulted inaccurate findings on detecting the relationship International Journal of Energy Economics and Policy | Vol 5 • Issue 2 • 2015 397 Isa, et al.: Review Paper on Economic Growth–Aggregate Energy Consumption Nexus between EC and GDP. Many researchers suggest that is due to the possibility of omitted variable bias Lu¨tkepohl (1982). Tang and Tan (2013) bivariate model specification may not appropriate for examining the energy growth nexus. After that suggestion, there are several studies had used the multivariate framework to investigate that causality relationship. In addition of the later variables they employed additional factors in the analysis such as; labor force in the following studies; Oh and Lee (2004b), Soytas and Sari (2006a), Soytas and Sari (2006b), Soytas et al. (2007), Huang et al. (2008), Lee and Chang (2008), Soytas and Sari (2008), Apergis and Payne (2009), Apergis and Payne (2010), Alam et al. (2011), Shahbaz et al. (2012), among others. Moreover some other studies had included the employment as a main factor in their analysis such as; Yu and Hwang (1984), Stern (1993), Cheng and Lai (1997), Cheng (1998), Stern (2000), Aqeel and Butt (2001), Ghali and El-Sakka (2004), Climent and Pardo (2007), Yuan et al. (2008), Payne (2009) and Ozturk and Acaravci (2010), among others. However some studies added the real gross fixed capital formation as a main variable; Stern (1993), Cheng (1996), Cheng (1997), Cheng (1998), Cheng (1999), Stern (2000), Ghali and El-Sakka (2004), Oh and Lee (2004a), Oh and Lee (2004b), Paul and Bhattacharya (2004), Lee (2005), Soytas and Sari (2006b), Soytas and Sari (2006a), Narayan and Smyth (2007), Soytas et al. (2007), Yuan et al.(2008), Huang et al. (2008), Lee and Chang (2008), Soytas and Sari (2008), Payne (2009), Apergis and Payne (2009), Apergis and Payne (2010), Alam et al. (2011), Shahbaz et al. (2012) and among others. As well some studies had included consumer or real energy prices; Masih and Masih (1997), Masih and Masih (1998), Asafu-Adjaye (2000), Glasure (2002), Hondroyiannis et al. (2002), Oh and Lee (2004b), Climent and Pardo (2007), Mahadevan and Asafu-Adjaye (2007), Costantini and Martini (2010), Odhiambo (2010), Hossein et al. (2012), Abalaba, and Dada, (2013). Furthermore in recent studies many other researchers has added the carbon dioxide emissions CO2 in their analysis, as they claim it has an important effect in the causality relationship between EC and GDP, some of those studies are; Soytas et al.(2007), Soytas and Sari (2008), Acaravci and Ozturk (2010), Hatzigeorgiou et al. (2011), Pao and Tsai (2011), Hossain (2011), Wang et al. (2011), Alam et al. (2011), Al-mulali and Che Sab (2012), Farhani, and Ben (2012), Saboori and Sulaiman (2013a), Saboori and Sulaiman (2013b), Alkhathlan and Javid (2013), among others. While some studies has added the population as main factor in their model such as; Cheng (1999), Paul and Bhattacharya (2004), among others. And other has considered the industrial value added in their analysis, Jobert and Karanfil (2007), Zachariadis (2007), Zamani (2007), and the later had included the agricultural value added in his analysis too. Pao and Tsai (2011) had considered the foreign direct investment in his molding. Al-mulali and Che Sab (2012) involve the financial development in their analysis. In additional on the study outlined in Table 2 we summarized some of them which has included different factors in the estimated model as following; Soytas et al. (2007) he studied the long run Granger causality between EC, CO2 and the GDP in the USA. Moreover he added some other factors in his model such as the labor force and investment in capital, while his findings do not support the existence of the causality direction neither between the GDP and CO2, nor between the GDP and EC. Moreover he confirmed that the main resource of emission is the EC. Soytas and Sari (2008) their study has focuses on examine the Granger causality relationship in long run only between GDP, EC and CO2 which is the most common pollutant emission in Turkey province, and they controlling the labor force and gross fixed capital, data spanning from 1960 to 2000. Moreover he applied five unit root tests (ADF, PP, KPSS, DF-GLS, and NP-Z) in his diagnostic analysis to examine the stationarity in the variables. His significant findings show that there is uni-directional causality running from CO2 to EC but the reverse is not true. And his result support that in the long run the EC does not seem to be Granger causing GDP in Turkey. In conclusion of their paper, they suggest that to take the technology investments and its effects into account. Ozturk and Acaravci (2010) concentrated on the causal relationship between the following variables; GDP, CO2, EC and employment ratio in turkey during the period 1968-2005 by applying recently developed ARDL bounds cointegration method for testing the long run relationships between the variables, and they used the error-correction based Granger causality models to test the causality. The findings indicate the expectance of long-run relationship between variables. There is no evidence show Granger causality of neither CO2 nor EC cause GDP in turkey. However in short run employment ratio causes GDP. Furthermore there is no causal relationship between GDP and CO2, due to that there is no any evidence support the environmental Kuznets curve (EKC) hypothesis. Moreover there is no causal relationship between GDP and both of EC and employment ratios. In additional of that the Long run causality have found only for the real GDP equation. In conclusion of that there is no sufficient evidence to say there is adverse effect from EC and CO2 to GDP. Zhang and Cheng (2009) concentrated to examine the Granger causal relationship among the GDP, EC and CO2 in china during the period 1960 to 2007 by using multivariate model for those variables including the gross fixed capital formation and urban population. They conducted three unit root tests ADF, PP and KPSS. Moreover they used ZA unit root test which can test the stationary of series with structural break. The results indicate the existence of two unidirectional Granger causality relationships; first one is running from GDP to EC, while the second one running from EC to CO2 in long run. In additional of that no clear evidence to enhance the influence of CO2 or EC towards the GDP. Al Sayed and Sek (2013) detect the relationship between GDP and CO2 for developed and developing countries for data spanning from 1961 to 2009 by using Panel data method. The EKC relationship has been detected in CO2. As a conclusion from those studies in Table 2, it is difficult to reach a consensus on the causal relationship between EC and GDP. 4. DISSECTION THE RESULTS OF FOUR HYPOTHESES EXISTENCE IN THE SURVEYED STUDIES The results of our empirical studies survey which concentrates in detecting the causality relationship between GDP and EC supporting one of the following hypotheses; growth, conservation, neutrality and feedback hypotheses. As we divided the survey studies into two classifications, bivariate and multivariate International Journal of Energy Economics and Policy | Vol 5 • Issue 2 • 2015398 Isa, et al.: Review Paper on Economic Growth–Aggregate Energy Consumption Nexus frameworks, we are going to calculate the percentage of each classification separately, and then we figure the results of the whole empirical studies. In one hand we illustrate the percentage of existence four hypotheses in the bivariate framework studies; the highest percentage supports the feedback hypothesis with 29.5%, followed by 26.2% for the neutrality hypothesis, then the growth hypothesis with 23.6%, and finally the lowest percentage is found in the conservation hypothesis. In the other hand the multivariate studies shows different results; as the highest percentage is also supports the existence of feedback hypothesis with 45.7%, but it followed by 25.0% in favor to growth hypothesis, and then 17.2% for the conservation hypothesis, and the lowest percentage is found in neutrality hypothesis with 12.1% only. However the percentages of those hypothesis in the whole survey empirical studies has presented as the following; in the leading position is the feedback hypothesis with 34.3%, then the growth hypothesis supported by 24.0%, and 22.0% in favor to the neutrality hypothesis, and only 19.7% for the conservation hypothesis. Table 3 and Figure 1 illustrate those results clearly. From the previous results we noted that the percentages among the two frameworks; bivariate and multivariate in the hypotheses are different. In conclusion we claim that the additional variables may increase (decrease) the probability of the feedback (neutrality) hypothesis existence, as it found 29.5% and 26.2% in bivariate framework, while it reach to 45.7% and 12.1% in multivariate framework respectively. 5. CONCLUSION Detecting the relationship between the EC and economic growth is very important for policy makers and to conserve the environment and to reduce the consumption of the nonrenewable energy. This survey has conducted to classify the studies into two groups by the framework bivariate and multivariate of the previous empirical studies. Secondly, to detect that if there is a significant influence of the additional variables to the bivariate framework into the four hypotheses. From our survey we conclude that there is no consensus on the direction of causality relationship between EC and GDP as the finding of those empirical studies have showed uneven results in terms of the four hypotheses (feedback, growth, conservation, and neutrality). At the end of it, we provide some suggestions for future researches; as we have mention earlier that no consensus in the results of direction into the causality relationship between the EC and GDP in a specific countries or panel countries, income classification groups, exporters and importers countries, etc. we recommend who interested to investigate that relationship to consider the following suggestions; future researches should focus more on new approaches and perspectives in multivariate framework rather than applying common methods with the same variables in bivariate framework only, most of the studies just changed the target group and the period time which does not lead to more potential contribution into that causality relationship. And that may be by adding new variables in the analysis such as; technology innovation recently undertaken by Tang and Tan (2013) but they used the electricity consumption as a main variable instead of take the aggregate EC. And other variables; GDP deflator, exchange rates, interest rates and EQ including CO2, SO2, GHG, SPM10, etc. Also we recommend of using several methods into detecting the causal relationship to get more robust findings which has supported by Zachariadis (2007) study. And to include the possibility of structural breaks in both the unit root process of the individual variable and in the tests for cointegration among the variables to get more accurate results. Moreover most of the previous study had ignored to detect the coefficients signs of the casualty relationship and the magnitude of that relationship, it should be considered and it might lead to clear explanation of that relationship. There is other limitation in the previous conducted studies; they considered the aggregation or the disaggregation EC as a proxy of the EC; they have not considered the renewable energy into their analysis. 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