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Climate Change Catastrophes

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  • Pizer, William

    (Resources for the Future)

Abstract

Most studies that compare price and quantity controls for greenhouse gas emissions under uncertainty find that price mechanisms perform substantially better. In these studies, the benefits from reducing emissions are proportional to the level of reductions, and such linear benefits strongly favor price policies (Weitzman 1974). Catastrophic damages, however, challenge that intuition as consequences become highly nonlinear. Catastrophe avoidance offers huge benefits, and incremental adjustments on either side of the associated threshold are relatively unimportant, suggesting a strong preference for quantity controls. This paper shows that with catastrophic damages, both price and quantity mechanisms offer large gains over the business-as-usual alternative, and the difference between policies is never more than 10%. Catastrophe avoidance is much more important than efficient catastrophe avoidance. Although previous studies favoring price policies in the presence of uncertainty have worried that catastrophes would reverse their results, this analysis indicates that such concerns are not borne out.

Suggested Citation

  • Pizer, William, 2003. "Climate Change Catastrophes," RFF Working Paper Series dp-03-31, Resources for the Future.
  • Handle: RePEc:rff:dpaper:dp-03-31
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    References listed on IDEAS

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    1. Kolstad, Charles D., 1996. "Learning and Stock Effects in Environmental Regulation: The Case of Greenhouse Gas Emissions," Journal of Environmental Economics and Management, Elsevier, vol. 31(1), pages 1-18, July.
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    3. Newell, Richard G. & Pizer, William A., 2003. "Regulating stock externalities under uncertainty," Journal of Environmental Economics and Management, Elsevier, vol. 45(2, Supple), pages 416-432, March.
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    7. Pizer, William A., 1999. "The optimal choice of climate change policy in the presence of uncertainty," Resource and Energy Economics, Elsevier, vol. 21(3-4), pages 255-287, August.
    8. Pizer, William, 1997. "Prices vs. Quantities Revisited: The Case of Climate Change," RFF Working Paper Series dp-98-02, Resources for the Future.
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    Cited by:

    1. Nicolas Taconet & Céline Guivarch & Antonin Pottier, 2021. "Social Cost of Carbon Under Stochastic Tipping Points," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 78(4), pages 709-737, April.
    2. Halkos, George, 2014. "The Economics of Climate Change Policy: Critical review and future policy directions," MPRA Paper 56841, University Library of Munich, Germany.
    3. Robert S. Pindyck, 2006. "Uncertainty In Environmental Economics," NBER Working Papers 12752, National Bureau of Economic Research, Inc.
    4. Nicolas Taconet & Céline Guivarch & Antonin Pottier, 2019. "Social Cost of Carbon under stochastic tipping points: when does risk play a role?," CIRED Working Papers hal-02408904, HAL.
    5. Cédric Philibert, 2009. "Assessing the value of price caps and floors," Climate Policy, Taylor & Francis Journals, vol. 9(6), pages 612-633, November.
    6. Halkos, George, 2013. "Uncertainty in optimal pollution levels: Modeling the benefit area," MPRA Paper 47768, University Library of Munich, Germany.
    7. George E. Halkos & Dimitra C. Kitsou, 2015. "Uncertainty in optimal pollution levels: modelling and evaluating the benefit area," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 58(4), pages 678-700, April.

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    More about this item

    Keywords

    climate change; global warming; prices versus quantities; stock externalities; integrated assessment; uncertainty;
    All these keywords.

    JEL classification:

    • Q28 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Government Policy
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models

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