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Evolution of the Global Distribution of Carbon Dioxide: A Finite Mixture Analysis

Author

Listed:
  • Michele Battisti

    (Department of Law, Politics and Society, University of Palermo)

  • Michael S. Delgado

    (Department of Agricultural Economics, Purdue University)

  • Christopher F. Parmeter

    (Department of Economics, University of Miami)

Abstract

Economists and environmental policymakers have recently begun advocating a bottom-up approach to climate change mitigation, focusing on reduction targets for groups of nations, rather than large scale global policies. We advance this discussion by taking a quantitative perspective, focusing on econometric identification of groups of countries that have statistically similar distributions of carbon emissions using a broad range of finite mixture models. Nearly all of our results yield a consistent pattern: after 1980, there are two distinct emissions distributions, and that these distributions continue to evolve over time. We provide a rigorous analysis of these distributional differences along several important dimensions: polarization, mobility, and volatility. We discuss how this robust quantitative evidence may aid policymakers in forging a heterogeneous carbon abatement policy.

Suggested Citation

  • Michele Battisti & Michael S. Delgado & Christopher F. Parmeter, 2013. "Evolution of the Global Distribution of Carbon Dioxide: A Finite Mixture Analysis," Working Papers 2013-10, University of Miami, Department of Economics.
  • Handle: RePEc:mia:wpaper:2013-10
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    File URL: https://www.herbert.miami.edu/_assets/files/repec/WP2103-10.pdf
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    2. Zhou, Yang & Shi, Zhixiong & Shi, Zhengyu & Gao, Qing & Wu, Libo, 2019. "Disaggregating power consumption of commercial buildings based on the finite mixture model," Applied Energy, Elsevier, vol. 243(C), pages 35-46.

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    More about this item

    Keywords

    Carbon emissions; Emissions groups; Heterogeneity; Abatement policy; Finite mixture models;
    All these keywords.

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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