Fat tails, exponents, extreme uncertainty: Simulating catastrophe in DICE
The problem of low-probability, catastrophic risk is increasingly central to discussion of climate science and policy. But the integrated assessment models (IAMs) of climate economics rarely incorporate this possibility. What modifications are needed to analyze catastrophic economic risks in an IAM? We explore this question using DICE, a well-known IAM. We examine the implications of a fat-tailed probability distribution for the climate sensitivity parameter, a focus of recent work by Martin Weitzman, and the shape of the damage function, one of the issues raised by the Stern Review. Forecasts of disastrous economic outcomes in DICE can result from the interaction of these two innovations, but not from either one alone.
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- Martin L. Weitzman, 2009.
"On Modeling and Interpreting the Economics of Catastrophic Climate Change,"
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- Weitzman, Martin L., 1998. "Why the Far-Distant Future Should Be Discounted at Its Lowest Possible Rate," Journal of Environmental Economics and Management, Elsevier, vol. 36(3), pages 201-208, November.
- 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.
- Stephen Newbold & Adam Daigneault, 2009. "Climate Response Uncertainty and the Benefits of Greenhouse Gas Emissions Reductions," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 44(3), pages 351-377, November.
- Simon Dietz & Chris Hope & Nicholas Stern & Dimitri Zenghelis, 2007. "REFLECTIONS ON THE STERN REVIEW (1) A Robust Case for Strong Action to Reduce the Risks of Climate Change," World Economics, World Economics, Economic & Financial Publishing, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 8(1), pages 121-168, January.
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