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National models of climate governance among major emitters

Author

Listed:
  • Johnathan Guy

    (University of California)

  • Esther Shears

    (University of California
    University of Bologna)

  • Jonas Meckling

    (University of California)

Abstract

National climate institutions structure the process of climate mitigation policymaking and shape climate policy ambition and performance. Countries have, for example, been building science bodies, passing climate laws and creating new agencies. Here we provide the first systematic comparison of climate institutions across 21 of the largest emitters. Drawing on an original dataset, we identify in a bottom-up cluster analysis four national models of climate governance: Climate Technocracies, Climate Developmentalists, Carbon Fragmentists and Carbon Centralists. These national models of climate governance are associated with policy ambition and performance. Climate Technocracies and Developmentalists tend to score higher than Carbon Fragmentists and Centralists in policy ambition and performance. The relative ambition of national models of governance is associated with some macro-institutional and macro-economic features, but not others. This suggests potential for domestic and international policymakers to invest in building national climate institutions across country settings to strengthen climate policy capacity.

Suggested Citation

  • Johnathan Guy & Esther Shears & Jonas Meckling, 2023. "National models of climate governance among major emitters," Nature Climate Change, Nature, vol. 13(2), pages 189-195, February.
    • Handle: RePEc:nat:natcli:v:13:y:2023:i:2:d:10.1038_s41558-022-01589-x
    DOI: 10.1038/s41558-022-01589-x
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    Cited by:

    1. Qingwei Shi & Yupeng Hu & Tiecheng Yan, 2023. "A Study on the Effect of Innovation-Driven Policies on Industrial Pollution Reduction: Evidence from 276 Cities in China," Sustainability, MDPI, vol. 15(12), pages 1-18, June.
    2. Uddin, Mohammad Jalal, 2023. "Investigating the impulse responses of renewable energy in the context of China: A Bayesian VAR Approach," Renewable Energy, Elsevier, vol. 219(P2).

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