IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/47279.html
   My bibliography  Save this paper

Output, renewable energy consumption and trade in Africa

Author

Abstract

We use panel cointegration techniques to examine the relationship between renewable energy consumption, trade and output in a sample of 11 African countries covering the period 1980-2008. The results from panel error correction model reveal that there is evidence of bidirectional causality between output and exports and between output and imports in both the short-run and the long-run. However, in the short-run, there is no evidence of causality between output and renewable energy consumption and between trade (exports or imports) and renewable energy consumption. In the long-run, the FMOLS panel approach estimation shows that renewable energy consumption and trade (exports or imports) have a statistically significant and positive impact on output. Policies recommendations are that, in the long-run, international trade enables African countries to benefit from technology transfer and to build the human and physical capacities needed to produce more renewable energies, which in turn increases their output.

Suggested Citation

  • Ben Jebli, Mehdi & Ben Youssef, Slim, 2013. "Output, renewable energy consumption and trade in Africa," MPRA Paper 47279, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:47279
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/47279/1/MPRA_paper_47279.pdf
    File Function: original version
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Apergis, Nicholas & Payne, James E., 2010. "Renewable energy consumption and growth in Eurasia," Energy Economics, Elsevier, vol. 32(6), pages 1392-1397, November.
    2. Pedroni, Peter, 2004. "Panel Cointegration: Asymptotic And Finite Sample Properties Of Pooled Time Series Tests With An Application To The Ppp Hypothesis," Econometric Theory, Cambridge University Press, vol. 20(3), pages 597-625, June.
    3. Sadorsky, Perry, 2009. "Renewable energy consumption and income in emerging economies," Energy Policy, Elsevier, vol. 37(10), pages 4021-4028, October.
    4. Kaddour Hadri, 2000. "Testing for stationarity in heterogeneous panel data," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 148-161.
    5. Sadorsky, Perry, 2012. "Energy consumption, output and trade in South America," Energy Economics, Elsevier, vol. 34(2), pages 476-488.
    6. Apergis, Nicholas & Payne, James E., 2010. "Renewable energy consumption and economic growth: Evidence from a panel of OECD countries," Energy Policy, Elsevier, vol. 38(1), pages 656-660, January.
    7. Sadorsky, Perry, 2009. "Renewable energy consumption, CO2 emissions and oil prices in the G7 countries," Energy Economics, Elsevier, vol. 31(3), pages 456-462, May.
    8. Kao, Chihwa, 1999. "Spurious regression and residual-based tests for cointegration in panel data," Journal of Econometrics, Elsevier, vol. 90(1), pages 1-44, May.
    9. Apergis, Nicholas & Payne, James E., 2011. "The renewable energy consumption-growth nexus in Central America," Applied Energy, Elsevier, vol. 88(1), pages 343-347, January.
    10. Maddala, G S & Wu, Shaowen, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 631-652, Special I.
    11. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
    12. Sadorsky, Perry, 2011. "Trade and energy consumption in the Middle East," Energy Economics, Elsevier, vol. 33(5), pages 739-749, September.
    13. Josep Lluís Carrion-i-Silvestre & Tomás del Barrio-Castro & Enrique López-Bazo, 2005. "Breaking the panels: An application to the GDP per capita," Econometrics Journal, Royal Economic Society, vol. 8(2), pages 159-175, July.
    14. Lean, Hooi Hooi & Smyth, Russell, 2010. "Multivariate Granger causality between electricity generation, exports, prices and GDP in Malaysia," Energy, Elsevier, vol. 35(9), pages 3640-3648.
    15. Apergis, Nicholas & Payne, James E., 2012. "Renewable and non-renewable energy consumption-growth nexus: Evidence from a panel error correction model," Energy Economics, Elsevier, vol. 34(3), pages 733-738.
    16. Narayan, Paresh Kumar & Smyth, Russell, 2009. "Multivariate granger causality between electricity consumption, exports and GDP: Evidence from a panel of Middle Eastern countries," Energy Policy, Elsevier, vol. 37(1), pages 229-236, January.
    17. Jaroslava Hlouskova & Martin Wagner, 2006. "The Performance of Panel Unit Root and Stationarity Tests: Results from a Large Scale Simulation Study," Econometric Reviews, Taylor & Francis Journals, vol. 25(1), pages 85-116.
    18. Peter Pedroni, 2001. "Purchasing Power Parity Tests In Cointegrated Panels," The Review of Economics and Statistics, MIT Press, vol. 83(4), pages 727-731, November.
    19. Banerjee, Anindya, 1999. "Panel Data Unit Roots and Cointegration: An Overview," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 607-629, Special I.
    20. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
    21. Lean, Hooi Hooi & Smyth, Russell, 2010. "On the dynamics of aggregate output, electricity consumption and exports in Malaysia: Evidence from multivariate Granger causality tests," Applied Energy, Elsevier, vol. 87(6), pages 1963-1971, June.
    22. World Bank, 2010. "World Development Indicators 2010," World Bank Publications, The World Bank, number 4373.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Renewable energy consumption; International trade; Africa; Panel cointegration.;

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • F14 - International Economics - - Trade - - - Empirical Studies of Trade
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:47279. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Joachim Winter). General contact details of provider: http://edirc.repec.org/data/vfmunde.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.