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Consommation d’énergies et croissance du PIB dans les pays de l’UEMOA : Une analyse en données de panel
[Energy consumption and GDP growth in WAEMU countries : A panel data analysis]

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  • Okey, Mawussé Komlagan Nézan

Abstract

This paper analyze the causal relationship between energy consumption and economic growth,as well as the relationship between energy sources for a panel of four WAEMU countries; Benin, Côte d’Ivoire, Senegal and Togo, for the period 1970-2005. Econometric analysis results indicate that there are: a bi-directional causality between oil consumption and economic growth, for the panel as a whole, but no causality between electricity and economic growth, and no substitution between energy sources at the short run. At the long run, there is a bi-directional causality between economic growth and both the energy sources which become substitutable. These results not only underline the energy dependence of the economic growth, and the rigidity of energy consumption behaviors of these four countries at the short run, but also support regional energy policies which must take account some countries specificities.

Suggested Citation

  • Okey, Mawussé Komlagan Nézan, 2009. "Consommation d’énergies et croissance du PIB dans les pays de l’UEMOA : Une analyse en données de panel [Energy consumption and GDP growth in WAEMU countries : A panel data analysis]," MPRA Paper 15521, University Library of Munich, Germany, revised 02 Jun 2009.
    • Handle: RePEc:pra:mprapa:15521
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    References listed on IDEAS

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    More about this item

    Keywords

    energy consumption; economic growth; panel; WAEMU;
    All these keywords.

    JEL classification:

    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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