Document Type: Original Article

Authors

1 Department of Industrial Engineering and Management Systems, Amirkabir University of Technology.

2 Department of Industrial Engineering and Management Systems, Amirkabir University of Technology

Abstract

In the recent years, renewable energy sources are an important component of world energy consumption. GDP is one of the main measures of a country’s economic activity. Most of the studies examine the impact of renewable energy consumption on GDP with single equation model and the others use dynamic panel data. Since the Granger causality analysis’s findings of this paper establish bidirectional causality between GDP and renewable energy consumption, the purpose of this study is to develop a simultaneous-equations model to explore the interaction between GDP and renewable energy consumption in a dynamic panel data. This model uses GDP and renewable energy consumption as endogenous variables and seven factors as exogenous variables. By using a dynamic panel data of 34 OECD countries from 1990 to 2012, the model is estimated by using the two-stage least-squares method. The results confirm the important influence of renewables and non-renewables as well as capital and labor force on GDP in OECD countries. Based on the results, both GDP and real oil price play an important role in renewable energy consumption. Our findings suggest that energy planners and policy makers need to increase renewable energy investment to ensure sustainable economic development in future.

Keywords

Al-Mulali, U., Fereidouni, H.G. & Lee, J.Y.M., 2013. Examining the bi-directional long run relationship between renewable energy consumption and GDP growth. Renewable and Sustainable Energy Reviews, 22, pp.209–222. Available at: http://dx.doi.org/10.1016/j.rser.2013.02.005.

Al-Mulali, U., Fereidouni, H.G. & Lee, J.Y.M., 2014. Electricity consumption from renewable and non-renewable sources and economic growth: Evidence from Latin American countries. Renewable and Sustainable Energy Reviews, 30, pp.290–298. Available at: http://dx.doi.org/10.1016/j.rser.2013.10.006.

Apergis, N. & Payne, J.E., 2011a. Renewable and non-renewable electricity consumption-growth nexus: Evidence from emerging market economies. Applied Energy, 88(12), pp.5226–5230. Available at: http://dx.doi.org/10.1016/j.apenergy.2011.06.041.

Apergis, N. & Payne, J.E., 2012a. Renewable and non-renewable energy consumption-growth nexus: Evidence from a panel error correction model. Energy Economics, 34(3), pp.733–738. Available at: http://dx.doi.org/10.1016/j.eneco.2011.04.007.

Apergis, N. & Payne, J.E., 2012b. Renewable and non-renewable energy consumption-growth nexus: Evidence from a panel error correction model. Energy Economics, 34(3), pp.733–738.

Apergis, N. & Payne, J.E., 2010a. Renewable energy consumption and economic growth: Evidence from a panel of OECD countries. Energy Policy, 38(1), pp.656–660. Available at: http://dx.doi.org/10.1016/j.enpol.2009.09.002.

Apergis, N. & Payne, J.E., 2010b. Renewable energy consumption and economic growth: Evidence from a panel of OECD countries. Energy Policy, 38(1), pp.656–660.

Apergis, N. & Payne, J.E., 2010c. Renewable energy consumption and growth in Eurasia. Energy Economics, 32(6), pp.1392–1397. Available at: http://dx.doi.org/10.1016/j.eneco.2010.06.001.

Apergis, N. & Payne, J.E., 2010d. Renewable energy consumption and growth in Eurasia. Energy Economics, 32(6), pp.1392–1397.

Apergis, N. & Payne, J.E., 2011b. The renewable energy consumption-growth nexus in Central America. Applied Energy, 88(1), pp.343–347. Available at: http://dx.doi.org/10.1016/j.apenergy.2010.07.013.

Apergis, N. & Payne, J.E., 2011c. The renewable energy consumption-growth nexus in Central America. Applied Energy, 88(1), pp.343–347.

Bash, E., 2015. No Title No Title. PhD Proposal, 1(1), pp.1–13.

Bilgili, F. & Ozturk, I., 2015a. Biomass energy and economic growth nexus in G7 countries: Evidence from dynamic panel data. Renewable and Sustainable Energy Reviews, 49, pp.132–138. Available at: http://dx.doi.org/10.1016/j.rser.2015.04.098.

Bilgili, F. & Ozturk, I., 2015b. Biomass energy and economic growth nexus in G7 countries: Evidence from dynamic panel data. Renewable and Sustainable Energy Reviews, 49, pp.132–138.

Bilgili, F. & Ozturk, I., 2015c. Biomass energy and economic growth nexus in G7 countries: Evidence from dynamic panel data. Renew. Sustain. Energy Rev., 49, pp.132–138. Available at: http://www.sciencedirect.com/science/article/pii/S1364032115003688.

Cerdeira Bento, J.P. et al., 2016. The effect of renewable energy consumption on economic growth: Evidence from top 38 countries. Applied Energy, 162, pp.733–741. Available at: http://linkinghub.elsevier.com/retrieve/pii/S0306261915013318nhttp://linkinghub.elsevier.com/retrieve/pii/S0921800915002323nhttp://www.sciencedirect.com/science/article/pii/S0360544215001085nhttp://linkinghub.elsevier.com/retrieve/pii/S1364032115012307.

Chang, T.H., Huang, C.M. & Lee, M.C., 2009. Threshold effect of the economic growth rate on the renewable energy development from a change in energy price: Evidence from OECD countries. Energy Policy, 37(12), pp.5796–5802. Available at: http://dx.doi.org/10.1016/j.enpol.2009.08.049.

Cho, S., Heo, E. & Kim, J., 2015. Causal relationship between renewable energy consumption and economic growth: comparison between developed and less-developed countries. Geosystem Engineering, 18(6), pp.284–291.

 

Fang, Y., 2011. Economic welfare impacts from renewable energy consumption: The China experience. Renewable and Sustainable Energy Reviews, 15(9), pp.5120–5128. Available at: http://dx.doi.org/10.1016/j.rser.2011.07.044.

Levin, A., Lin, C.-F. & James Chu, C.-S., 2002. Unit root tests in panel data: asymptotic and finite-sample properties. Journal of Econometrics, 108(1), pp.1–24. Available at: http://www.sciencedirect.com/science/article/pii/S0304407601000987 [Accessed April 3, 2016].

Magnani, N. & Vaona, A., 2013. Regional spillover effects of renewable energy generation in Italy. Energy Policy, 56, pp.663–671. Available at: http://dx.doi.org/10.1016/j.enpol.2013.01.032.

Marques, A.C. & Fuinhas, J.A., 2012. Is renewable energy effective in promoting growth? Energy Policy, 46, pp.434–442.

Menegaki, A.N., 2011. Growth and renewable energy in Europe: A random effect model with evidence for neutrality hypothesis. Energy Economics, 33(2), pp.257–263. Available at: http://dx.doi.org/10.1016/j.eneco.2010.10.004.

Müller, S., Brown, A. & Ölz, S., 2011. Policy Considerations For Deploying Renewables. Renewable Energy, p.72. Available at: https://www.iea.org/publications/freepublications/publication/Renew_Policies.pdf.

Ocal, O. & Aslan, A., 2013. Renewable energy consumption-economic growth nexus in Turkey. Renewable and Sustainable Energy Reviews, 28, pp.494–499. Available at: http://dx.doi.org/10.1016/j.rser.2013.08.036.

Ohler, A. & Fetters, I., 2014. The causal relationship between renewable electricity generation and GDP growth: A study of energy sources. Energy Economics, 43, pp.125–139. Available at: http://dx.doi.org/10.1016/j.eneco.2014.02.009.

Omri, A. & Nguyen, D.K., 2014. On the determinants of renewable energy consumption: International evidence. Energy, 72, pp.554–560. Available at: http://dx.doi.org/10.1016/j.energy.2014.05.081.

Pao, H.T. & Fu, H.C., 2013. Renewable energy, non-renewable energy and economic growth in Brazil. Renewable and Sustainable Energy Reviews, 25, pp.381–392. Available at: http://dx.doi.org/10.1016/j.rser.2013.05.004.

Payne, J.E., 2009. On the dynamics of energy consumption and output in the US. Applied Energy, 86(4), pp.575–577. Available at: http://dx.doi.org/10.1016/j.apenergy.2008.07.003.

Pedroni, P., 1999a. Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics and statistics, pp.653–670.

Pedroni, P., 1999b. CRITICAL VALUES FOR COINTEGRATION TESTS IN HETEROGENEOUS PANELS WITH MULTIPLE REGRESSORS.

Robert F . Engle and C . W . J . Granger, 1987. Co-Integration and Error Correction : Representation , Estimation , and Testing. Econometrica, 55(2), pp.251–276.

Sadorsky, P., 2009a. Renewable energy consumption, CO2 emissions and oil prices in the G7 countries. Energy Economics, 31(3), pp.456–462.

Sadorsky, P., 2009b. Renewable energy consumption and income in emerging economies. Energy Policy, 37(10), pp.4021–4028. Available at: http://dx.doi.org/10.1016/j.enpol.2009.05.003.

Salim, R.A. & Rafiq, S., 2012. Why do some emerging economies proactively accelerate the adoption of renewable energy? Energy Economics, 34(4), pp.1051–1057.

Smiech, S. & Papiez, M., 2014. Energy consumption and economic growth in the light of meeting the targets of energy policy in the EU: The bootstrap panel Granger causality approach. Energy Policy, 71, pp.118–129.

Tiwari, A.K., 2011. Volume 31 , Issue 2 A structural VAR analysis of renewable energy consumption , real GDP and. Economics Bulletin, 31(2), pp.1793–1806.

Tugcu, C.T., Ozturk, I. & Aslan, A., 2012a. Renewable and non-renewable energy consumption and economic growth relationship revisited: Evidence from G7 countries. Energy Economics, 34(6), pp.1942–1950. Available at: http://dx.doi.org/10.1016/j.eneco.2012.08.021.

Tugcu, C.T., Ozturk, I. & Aslan, A., 2012b. Renewable and non-renewable energy consumption and economic growth relationship revisited: Evidence from G7 countries. Energy Economics, 34(6), pp.1942–1950.

 

do Valle Costa, C., La Rovere, E. & Assmann, D., 2008. Technological innovation policies to promote renewable energies: Lessons from the European experience for the Brazilian case. Renewable and Sustainable Energy Reviews, 12(1), pp.65–90.

Yildirim, E., Sukruoglu, D. & Aslan, A., 2014. Energy consumption and economic growth in the next 11 countries: The bootstrapped autoregressive metric causality approach. Energy Economics, 44, pp.14–21.

Zhang, X.-P. & Cheng, X.-M., 2009. Energy consumption, carbon emissions, and economic growth in China. Ecological Economics, 68(10), pp.2706–2712. Available at: http://linkinghub.elsevier.com/retrieve/pii/S092180090900216X.

World Bank, various issues. World Bank Development Indicators. Washington DC: World Bank.

Energy Information Administration (EIA). International Energy Outlook. Washington, DC: US Energy Information Administration, US Department of Energy; 2013.

Engle RF, Granger CWJ. Cointegration and error correction: representation, estimation and testing. Econometrica 1987;55:251–76.