ON MODELING AND INTERPRETING THE ECONOMICS OF CATASTROPHIC CLIMATE CHANGE
成果类型：
Article
署名作者：
Weitzman, Martin L.
署名单位：
Harvard University
刊物名称：
REVIEW OF ECONOMICS AND STATISTICS
ISSN/ISSBN：
0034-6535
DOI：
10.1162/rest.91.1.1
发表日期：
2009-02
页码：
1-19
关键词：
摘要：
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.
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