On Modeling and Interpreting the Economics of Catastrophic Climate Change
With climate change as prototype example, this paper analyzes the implications of structural uncertainty for the economics of low-probability, high-impact catastrophes. Even when updated by Bayesian learning, uncertain structural parameters induce a critical "tail fattening" of posterior-predictive distributions. Such fattened tails have strong implications for situations, like climate change, where a catastrophe is theoretically possible because prior knowledge cannot place sufficiently narrow bounds on overall damages. This paper shows that the economic consequences of fat-tailed structural uncertainty (along with unsureness about high-temperature damages) can readily outweigh the effects of discounting in climate-change policy analysis. Copyright by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.
Volume (Year): 91 (2009)
Issue (Month): 1 (February)
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References listed on IDEAS
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- François Bellavance & Georges Dionne & Martin Lebeau, 2006.
"The Value of a Statistical Life: a Meta-Analysis with a Mixed Effects Regression Model,"
Cahiers de recherche
- Bellavance, Franois & Dionne, Georges & Lebeau, Martin, 2009. "The value of a statistical life: A meta-analysis with a mixed effects regression model," Journal of Health Economics, Elsevier, vol. 28(2), pages 444-464, March.
- Scott Barrett, 2008. "The Incredible Economics of Geoengineering," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 39(1), pages 45-54, January.
- Richard S.J. Tol, 2000. "Is the Uncertainty about Climate Change Too Large for Expected Cost-Benefit Analysis?," Working Papers FNU-3, Research unit Sustainability and Global Change, Hamburg University, revised Sep 2000.
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