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

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  • Simon Dietz

Abstract

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.

Suggested Citation

  • 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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    Cited by:

    1. Jensen, Svenn & Traeger, Christian P., 2014. "Optimal climate change mitigation under long-term growth uncertainty: Stochastic integrated assessment and analytic findings," European Economic Review, Elsevier, vol. 69(C), pages 104-125.
    2. David Hendry, 2010. "Climate Change: Lessons for our Future from the Distant Past," Economics Series Working Papers 485, University of Oxford, Department of Economics.
    3. 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.
    4. Aldred, Jonathan, 2013. "Justifying precautionary policies: Incommensurability and uncertainty," Ecological Economics, Elsevier, vol. 96(C), pages 132-140.
    5. Dietz, Simon, 2012. "The treatment of risk and uncertainty in the US social cost of carbon for regulatory impact analysis," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-12.
    6. Crost, Benjamin & Traeger, Christian P., 2013. "Optimal climate policy: Uncertainty versus Monte Carlo," Economics Letters, Elsevier, vol. 120(3), pages 552-558.
    7. Thijs Dekker & Rob Dellink & Janina Ketterer, 2013. "The Fatter the Tail, the Fatter the Climate Agreement - Simulating the Influence of Fat Tails in Climate Change Damages on the Success of International Climate Negotiations," CESifo Working Paper Series 4059, CESifo.
    8. Rob Dellink & Thijs Dekker & Janina Ketterer, 2013. "The Fatter the Tail, the Fatter the Climate Agreement," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 56(2), pages 277-305, October.

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