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On Modeling and Interpreting the Economics of Catastrophic Climate Change

Martin Weitzman

Scholarly Articles from Harvard University Department of Economics

Abstract: 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.

Date: 2009
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Citations: View citations in EconPapers (702)

Published in Review of Economics and Statistics

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Persistent link: https://EconPapers.repec.org/RePEc:hrv:faseco:3693423

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