Testing for VECM Granger Causality and Cointegration Between Economic Growth and Renewable Energy: Evidence from MENA Net Energy Importing Countries
Abstract
This paper employs several techniques to study the relationship between renewable energy consumption and economic growth in Net Energy Importing Countries in the Middle East and North Africa (MENA-NEICs) during the period from 2001 to 2015. Panel cointegration test shows that there is a long-term cointegration relationship between those variables. However, the Granger causality test in VECM shows that this relationship is bidirectional in the short and long term. Thus, MENA-NEICs must encourage the deployment of renewable energies to the detriment of fossil fuels. To this end, an investment incentive is suggested in this sector, which will be medium and long-term market-based. In the short term, a transitional stage of a mixed and dynamic approach consisting of a program of partial subsidies for renewable energy production and partial adjustment of fossil fuel prices that is progressively moving towards a final stage where subsidies to energy will be completely removed is suggested. In this way, these countries can make the trade-off between fiscal sustainability and political stability.
References
Alam, S. and Butt, M. S. (2002). Causality between energy and economic growth in Pakistan: An application of cointegration and error correction modeling techniques. Pacific and Asia Journal of Energy, 12(2):151–165.
Apergis, N. and Payne, J. E. (2010a). Energy consumption and growth in South America: Evidence from a panel error correction model. Energy Economics, 32(6):1421–1426.
Apergis, N. and Payne, J. E. (2010b). Renewable energy consumption and economic growth: Evidence from a panel of OECD countries. Energy Policy, 38(1):656–660.
Apergis, N. and Payne, J. E. (2010c). Renewable energy consumption and growth in Eurasia. Energy Economics, 32(6):1392–1397.
Bhutto, A. W., Bazmi, A. A., Zahedi, G., and Klemes, J. J. (2014). A review of progress in renewable energy implementation in the Gulf Cooperation Council countries. Journal of Cleaner Production, 71:168–180.
Burke, M., Hsiang, S. M., and Miguel, E. (2015). Global non-linear effect of temperature on economic production. Nature, 527:235–239.
Costantini, V. and Martini, C. (2010). The causality between energy consumption and economic growth: A multi-sectoral analysis using non-stationary cointegrated panel data. Energy Economics, 32(3):591–603.
Dees, P. and Vidican Auktor, G. (2018). Renewable energy and economic growth in the MENA region: empirical evidence and policy implications. Middle East Development Journal, 10(2):225–247.
Dickey, D. A. and Fuller, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series With a Unit Root. Journal of American Statistical Association, 74(366):427–431.
Engle, R. and Granger, C. (1987). Co-integration and Error Correction: Representation, Estimation, and Testing. Econometrica, 55(2):251–76.
Fei, L., Dong, S., Xue, L., Liang, Q., and Yang, W. (2011). Energy consumption-economic growth relationship and carbon dioxide emissions in China. Energy Policy, 39(2):568–574.
Ibrahiem, D. M. (2015). Renewable Electricity Consumption, Foreign Direct Investment and Economic Growth in Egypt: An ARDL Approach. Procedia Economics and Finance, 30:313–323.
Im, K. S., Pesaran, M. H., and Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1):53–74.
International Energy Agency (2009). World Energy Outlook. Paris, France.
International Energy Agency (2019). World Energy Investment 2019. https://webstore.iea.org/world-energy-investment-2019. [Online; accessed 22-08-2019].
International Institute for Sustainable Development (2014). Fossil-Fuel Subsidies: a Barrier to Renewable Energy in Five Middle East and North African Countries. [Online; accessed 22-08-2019].
International Renewable Energy Agency (2016). Renewable Energy Market Analysise: The GCC Region. [Online; accessed 22-08-2019].
International Renewable Energy Agency (2019a). Global Energy Transformation: A roadmap to 2050. https://www.irena.org/publications/2019/Apr/Global-energy-transformation-A-roadmap-to-2050-2019Edition. [Online; accessed 22-08-2019].
International Renewable Energy Agency (2019b). A New World: The Geopolitics of the Energy Transformation. https://www.irena.org/publications/2019/Jan/A-New-World-The-Geopolitics-of-the-Energy-Transformation. [Online; accessed 22- 08-2019].
Jinke, L., Hualing, S., and Dianming, G. (2008). Causality relationship between coal consumption and GDP: Difference of major OECD and non-OECD countries. Applied Energy, 85(6):421–429.
Jordan Times (2016). Renewables use can save $750b in Mideast, Africa — official. [Online; accessed 22. Aug. 2019].
Lee, C.-C. and Chang, C.-P. (2008). Energy consumption and economic growth in Asian economies: A more comprehensive analysis using panel data. Resource and Energy Economics, 30(1):50–65.
Levin, A., Lin, C.-F., and Chu, C.-S. J. (2002). Unit root tests in panel data: asymptotic and finite-sample properties. Journal of Econometrics, 108(1):1–24.
Mallick, H. (2009). Examining the Linkage between Energy Consumption and Economic Growth in India. Journal of Developing Areas, 43(1):249–280.
Managi, S. (2006). Are there increasing returns to pollution abatement? Empirical analytics of the Environmental Kuznets Curve in pesticides. Ecological Economics, 58(3):617–636.
Menyah, K. and Wolde-Rufael, Y. (2010). CO2 emissions, nuclear energy, renewable energy and economic growth in the US. Energy Policy, 38(6):2911–2915.
Pedroni, P. (2000). Fully Modified OLS for Heterogeneous Cointegrated Panels. Department of Economics Working Papers 2000-03, Department of Economics, Williams College.
Pedroni, P. (2004). Panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis. Econometric Theory, 20(3):597–625.
Phillips, P. C. B. and Perron, P. (1988). Testing for a Unit Root in Time Series Regression. Biometrika, 75(2):335–346.
Sadorsky, P. (2009). Renewable energy consumption, CO2 emissions and oil prices in the G7 countries. Energy Economics, 31(3):456–462.
Stern, D. I. (2000). A multivariate cointegration analysis of the role of energy in the US macroeconomy. Energy Economics, 22(2):267–283.
United Nations Environment Program (2019). Renewable energy investment in 2018 hit USD 288.9 billion, far exceeding fossil fuel investment. https://www.unenvironment.org/news-and-stories/press-release/renewable-energy-investment-2018-hit-usd-2889-billion-far-exceeding. [Online; accessed 22-08-2019].
World Bank (2016). World development indicators. https://data.worldbank.org/. [Online; accessed 22-08-2019].
Copyright (c) 2019 by the Author(s)
This work is licensed under a Creative Commons Attribution 4.0 International License.