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Optimal Climate Policy When Damages Are Unknown

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  • Ivan Rudik

Abstract

Integrated assessment models (IAMs) are economists' primary tool for analyzing the optimal carbon tax. Damage functions, which link temperature to economic impacts, have come under fire because of their assumptions that may be incorrect in significant but a priori unknowable ways. Here I develop recursive IAM frameworks to model uncertainty, learning, and concern for misspecification about damages. I decompose the carbon tax into channels capturing state uncertainty, insurance motives, and precautionary saving. Damage learning improves ex ante welfare by 750 billion USD. If damage functions are misspecified and omit the potential for catastrophic damages, robust control may be beneficial ex post.

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  • Ivan Rudik, 2020. "Optimal Climate Policy When Damages Are Unknown," American Economic Journal: Economic Policy, American Economic Association, vol. 12(2), pages 340-373, May.
    • Handle: RePEc:aea:aejpol:v:12:y:2020:i:2:p:340-73
    DOI: 10.1257/pol.20160541
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    References listed on IDEAS

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    1. Yongyang Cai & Thomas S. Lontzek, 2019. "The Social Cost of Carbon with Economic and Climate Risks," Journal of Political Economy, University of Chicago Press, vol. 127(6), pages 2684-2734.
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    Cited by:

    1. Fillon, Romain & Guivarch, Céline & Taconet, Nicolas, 2023. "Optimal climate policy under tipping risk and temporal risk aversion," Journal of Environmental Economics and Management, Elsevier, vol. 121(C).
    2. Vilhuber, Lars, 2023. "Reproducibility and transparency versus privacy and confidentiality: Reflections from a data editor," Journal of Econometrics, Elsevier, vol. 235(2), pages 2285-2294.
    3. Loïc Berger & Massimo Marinacci, 2020. "Model Uncertainty in Climate Change Economics: A Review and Proposed Framework for Future Research," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 77(3), pages 475-501, November.
    4. Agliardi, Elettra & Xepapadeas, Anastasios, 2022. "Temperature targets, deep uncertainty and extreme events in the design of optimal climate policy," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    5. Frederick Ploeg, 2021. "Carbon pricing under uncertainty," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 28(5), pages 1122-1142, October.
    6. Stan Olijslagers & Sweder Wijnbergen, 2024. "Discounting the Future: On Climate Change, Ambiguity Aversion and Epstein–Zin Preferences," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(3), pages 683-730, March.
    7. Edenhofer, Ottmar & Lessmann, Kai & Tahri, Ibrahim, 2024. "Asset pricing and the carbon beta of externalities," Journal of Environmental Economics and Management, Elsevier, vol. 125(C).
    8. Svenn Jensen & Christian P. Traeger & Christian Träger, 2021. "Pricing Climate Risk," CESifo Working Paper Series 9196, CESifo.
    9. Yingjie Niu & Zhentao Zou, 2024. "Robust Abatement Policy with Uncertainty About Environmental Disasters," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(4), pages 933-965, April.
    10. Lint Barrage, 2023. "Fiscal Costs of Climate Change in the United States," CER-ETH Economics working paper series 23/380, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.

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    More about this item

    JEL classification:

    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

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