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ON MODELING AND INTERPRETING THE ECONOMICS OF CATASTROPHIC CLIMATE CHANGE

Published on Feb 1, 2009in The Review of Economics and Statistics3.64
· DOI :10.1162/rest.91.1.1
Martin L. Weitzman54
Estimated H-index: 54
(Harvard University)
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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. Copyright by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.
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