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CO 2 Emissions and Income Dynamics: What Does the Global Evidence Tell Us?

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  • Thomas Bassetti

    ()

  • Nikos Benos

    ()

  • Stelios Karagiannis

    ()

Abstract

This paper analyzes the co-evolution of two major determinants of social welfare, namely, income and carbon emissions. In particular, by using a distribution dynamics approach based on Markov chains, we investigate the shape and behavior of the joint distribution of per-capita income and carbon dioxide emissions. We arrive at several interesting conclusions, especially in the context of international negotiations on climate change. First, evidence does not support theoretical models predicting the existence of a poverty-environment trap. Specifically, in the long-run two main groups of countries will emerge: poor versus polluting countries. Second, the typical development path leads initially to high emission levels and, subsequently, to high income. Third, the convergence process towards the stationary distribution is very slow. Finally, for carbon emissions, whenever it is observed, the environmental Kuznets curve seems to be only a transitory phenomenon. Copyright Springer Science+Business Media B.V. 2013

Suggested Citation

  • Thomas Bassetti & Nikos Benos & Stelios Karagiannis, 2013. "CO 2 Emissions and Income Dynamics: What Does the Global Evidence Tell Us?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 54(1), pages 101-125, January.
  • Handle: RePEc:kap:enreec:v:54:y:2013:i:1:p:101-125
    DOI: 10.1007/s10640-012-9583-1
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    Citations

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    Cited by:

    1. Roberto Martino & Phu Nguyen-Van, 2016. "Environmental Kuznets curve and environmental convergence: A unified empirical framework for CO2 emissions," Working Papers of BETA 2016-18, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    2. Jian-Xin Wu & Ling-Yun He, 2017. "The Distribution Dynamics of Carbon Dioxide Emissions Intensity across Chinese Provinces: A Weighted Approach," Sustainability, MDPI, Open Access Journal, vol. 9(1), pages 1-19, January.
    3. Jonathan Pickering & Frank Jotzo & Peter J. Wood, 2015. "Splitting the Difference: Can Limited Coordination Achieve a Fair Distribution of the Global Climate Financing Effort?," CCEP Working Papers 1504, Centre for Climate Economics & Policy, Crawford School of Public Policy, The Australian National University.
    4. Mahmut Zortuk & Sinan Çeken, 2016. "Testing Environmental Kuznets Curve in the Selected Transition Economies with Panel Smooth Transition Regression Analysis," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 18(43), pages 537-537, August.
    5. Alexander Golub & Michael Toman, 2016. "Climate Change, Industrial Transformation, and “Environmental Growth Traps”," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 63(2), pages 249-263, February.
    6. Golub, Alexander & Toman, Michael, 2014. "Climate change, industrial transformation, and"development traps"," Policy Research Working Paper Series 6951, The World Bank.
    7. Antal, Miklós, 2014. "Green goals and full employment: Are they compatible?," Ecological Economics, Elsevier, vol. 107(C), pages 276-286.
    8. Battisti, Michele & Delgado, Michael S. & Parmeter, Christopher F., 2015. "Evolution of the global distribution of carbon dioxide: A finite mixture analysis," Resource and Energy Economics, Elsevier, vol. 42(C), pages 31-52.
    9. Fouad El Ouardighi & Konstantin Kogan & Raouf Boucekkine, 2017. "Optimal recycling under heterogeneous waste sources and the environmental Kuznets curve," Working Papers hal-01693488, HAL.
    10. Jules Pretty, 2013. "The Consumption of a Finite Planet: Well-Being, Convergence, Divergence and the Nascent Green Economy," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 55(4), pages 475-499, August.

    More about this item

    Keywords

    CO 2 emissions; Convergence; Markov chains; Multiple equilibria; C14; O11; O44; Q53;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • O44 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Environment and Growth
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling

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