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A Note on Growth, Energy Intensity and the Energy Mix: A Dynamic Panel Data Analysis

Author

Listed:
  • Antonia Díaz

    () (Universidad Carlos III de Madrid)

  • Gustavo A. Marrero

    () (Universidad de La Laguna)

  • Luis Puch

    () (Universidad Complutense de Madrid)

  • Jesús Rodríguez-López

    () (U. Pablo de Olavide)

Abstract

This paper explores how changes in energy intensity and the switch to renewables can boost economic growth. In doing so, we implement a dynamic panel data approach on a sample of 134 countries over the period 1960 to 2010. We incorporate a set of control variables, related to human and physical capital, socio-economic conditions, and policies which are widely used in the associated literature. According to our results, and given the current state of technology, improving energy intensity is an approach that could reconcile growth and the environment at the worldwide level. Moving to conventional renewables (biomass and hydro) may reduce CO2 emissions, consistent with the related literature, although we do not find evidence that supports a growth enhancing effect. However, moving to frontier renewables (wind, solar, wave or geothermic) does reconcile the reduction of CO2 emissions with economic growth. Our results are robust to the specification of the dynamic panel with respect to three alternative methods, namely, the pooled OLS regression, the regression under fixed effects, and the GMM estimation.

Suggested Citation

  • Antonia Díaz & Gustavo A. Marrero & Luis Puch & Jesús Rodríguez-López, 2018. "A Note on Growth, Energy Intensity and the Energy Mix: A Dynamic Panel Data Analysis," Working Papers 18.08, Universidad Pablo de Olavide, Department of Economics.
  • Handle: RePEc:pab:wpaper:18.08
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    References listed on IDEAS

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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. El Impuesto-Dividendo CO2
      by Antonia Díaz in Nada Es Gratis on 2019-04-02 05:07:32

    More about this item

    Keywords

    Economic growth; energy intensity; renewable energy; dynamic panel data models.;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • O5 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies
    • Q2 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation
    • Q3 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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