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On Modeling and Interpreting the Economics of Catastrophic Climate Change

2009/01/28 by Martin L. Weitzman · 7 citations
Economics, Econometrics and Finance · Energy · Mathematics · #Bayesian inference #Bayesian probability #Climate Change Policy and Economics #Climate change #Damages #Discounting #Ecology #Econometrics #Economics #Global Energy and Sustainability Research #Market Dynamics and Volatility #Mathematics #Political science #Statistics

paper · doi:10.1162/rest.91.1.1

openalex publication_date 2009/01/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29

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.

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