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Estimating country-specific environmental Kuznets curves from panel data: a Bayesian shrinkage approach

Author

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  • Thomas Jobert

    (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - UNS - Université Nice Sophia Antipolis (1965 - 2019) - CNRS - Centre National de la Recherche Scientifique - UniCA - Université Côte d'Azur)

  • Fatih Karanfil

    (EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

  • Anna Tykhonenko

    (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - UNS - Université Nice Sophia Antipolis (1965 - 2019) - CNRS - Centre National de la Recherche Scientifique - UniCA - Université Côte d'Azur)

Abstract

Designing an efficient global climate policy turns out to be a difficult yet crucial task since there are noteworthy cross-country differences in energy and carbon intensities. In this article, the environmental Kuznets curve (EKC) hypothesis is tested for carbon dioxide (CO2) emissions, and as a modelling technique, the iterative Bayesian shrinkage procedure is employed to handle the cross-country differences. The results suggest that first the EKC hypothesis is rejected for 47 out of the 51 countries considered when the heterogeneity in countries' energy efficiencies and cross-country differences in the CO2 emissions trajectories are accounted for; second, a classification of the results with respect to the development levels of the countries concerned reveals that the emergence of an overall inverted U-shaped curve is due to the fact that in high-income countries increase in gross domestic product (GDP) decreases emissions, while in low-income countries emissions and GDP are positively correlated.

Suggested Citation

  • Thomas Jobert & Fatih Karanfil & Anna Tykhonenko, 2014. "Estimating country-specific environmental Kuznets curves from panel data: a Bayesian shrinkage approach," Post-Print halshs-01053358, HAL.
  • Handle: RePEc:hal:journl:halshs-01053358
    DOI: 10.1080/00036846.2013.875111
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    Cited by:

    1. Thomas Jobert & Fatih Karanfil & Anna Tykhonenko, 2012. "Trade and Environment: Further Empirical Evidence from Heterogeneous Panels Using Aggregate Data," GREDEG Working Papers 2012-15, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    2. Lisa Gianmoena & Vicente Rios, 2018. "The Determinants of CO2 Emissions Differentials with Cross-Country Interaction Effects: A Dynamic Spatial Panel Data Bayesian Model Averaging Approach," Discussion Papers 2018/234, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    3. Fernández-Amador, Octavio & Francois, Joseph F. & Oberdabernig, Doris A. & Tomberger, Patrick, 2017. "Carbon Dioxide Emissions and Economic Growth: An Assessment Based on Production and Consumption Emission Inventories," Ecological Economics, Elsevier, vol. 135(C), pages 269-279.
    4. Karanfil, Fatih & Li, Yuanjing, 2015. "Electricity consumption and economic growth: Exploring panel-specific differences," Energy Policy, Elsevier, vol. 82(C), pages 264-277.
    5. Hao, Yu & Wei, Yi-Ming, 2015. "When does the turning point in China's CO2 emissions occur? Results based on the Green Solow model," Environment and Development Economics, Cambridge University Press, vol. 20(6), pages 723-745, December.
    6. Willenbockel, Dirk, 2014. "Reflections on the prospects for pro-poor low-carbon growth," MPRA Paper 69863, University Library of Munich, Germany.
    7. Karanfil, Fatih & Omgba, Luc Désiré, 2019. "Do the IMF’s structural adjustment programs help reduce energy consumption and carbon intensity? Evidence from developing countries," Structural Change and Economic Dynamics, Elsevier, vol. 49(C), pages 312-323.
    8. Sencer Atasoy, Burak, 2017. "Testing the environmental Kuznets curve hypothesis across the U.S.: Evidence from panel mean group estimators," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 731-747.

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