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High impact, low probability? An empirical analysis of risk in the economics of climate change


  • Simon Dietz


To what extent does economic analysis of climate change depend on low-probability, high-impact events? This question has received a great deal of attention lately, with the contention increasingly made that climate damage could be so large that societal willingness to pay to avoid extreme outcomes should overwhelm other seemingly important assumptions, notably on time preference. This paper provides an empirical examination of some key theoretical points, using a probabilistic integrated assessment model. New, fat-tailed distributions are inputted for key parameters representing climate sensitivity and economic costs. It is found that welfare estimates do strongly depend on tail risks, but for a set of plausible assumptions time preference can still matter.

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  • Simon Dietz, 2009. "High impact, low probability? An empirical analysis of risk in the economics of climate change," GRI Working Papers 9, Grantham Research Institute on Climate Change and the Environment.
  • Handle: RePEc:lsg:lsgwps:wp09

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    References listed on IDEAS

    1. Tol, Richard S. J., 2005. "The marginal damage costs of carbon dioxide emissions: an assessment of the uncertainties," Energy Policy, Elsevier, vol. 33(16), pages 2064-2074, November.
    2. Roughgarden, Tim & Schneider, Stephen H., 1999. "Climate change policy: quantifying uncertainties for damages and optimal carbon taxes," Energy Policy, Elsevier, vol. 27(7), pages 415-429, July.
    3. Hope, Chris, 2008. "Discount rates, equity weights and the social cost of carbon," Energy Economics, Elsevier, vol. 30(3), pages 1011-1019, May.
    4. Geoffrey Heal, 2009. "Climate Economics: A Meta-Review and Some Suggestions for Future Research," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 3(1), pages 4-21, Winter.
    5. Geweke, John, 2001. "A note on some limitations of CRRA utility," Economics Letters, Elsevier, vol. 71(3), pages 341-345, June.
    6. Martin L. Weitzman, 2009. "On Modeling and Interpreting the Economics of Catastrophic Climate Change," The Review of Economics and Statistics, MIT Press, vol. 91(1), pages 1-19, February.
    7. Claude HENRY & Marc HENRY, 2002. "Formalization and Applications of the Precuationary Principle," Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) 2002009, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    8. Aumann, Robert J & Kurz, Mordecai, 1977. "Power and Taxes," Econometrica, Econometric Society, vol. 45(5), pages 1137-1161, July.
    9. Stephen C Peck & Thomas J. Teisberg, 1992. "CETA: A Model for Carbon Emissions Trajectory Assessment," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 55-78.
    10. Ackerman, Frank & Stanton, Elizabeth A. & Bueno, Ramón, 2010. "Fat tails, exponents, extreme uncertainty: Simulating catastrophe in DICE," Ecological Economics, Elsevier, vol. 69(8), pages 1657-1665, June.
    11. Martin L. Weitzman, 2007. "A Review of the Stern Review on the Economics of Climate Change," Journal of Economic Literature, American Economic Association, vol. 45(3), pages 703-724, September.
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    Cited by:

    1. Crost, Benjamin & Traeger, Christian P., 2013. "Optimal climate policy: Uncertainty versus Monte Carlo," Economics Letters, Elsevier, vol. 120(3), pages 552-558.
    2. Martin L. Weitzman, 2012. "GHG Targets as Insurance Against Catastrophic Climate Damages," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 14(2), pages 221-244, March.
    3. Aldred, Jonathan, 2013. "Justifying precautionary policies: Incommensurability and uncertainty," Ecological Economics, Elsevier, vol. 96(C), pages 132-140.

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