On Modeling and Interpreting the Economics of Catastrophic Climate Change

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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 catastro- phes. 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 su¢ ciently 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 eects of discounting in climate-change policy analysis. What is the essence of the economic problem posed by climate change? The economic uniqueness of the climate-change problem is not just that today's decisions have di¢ cult-to- reverse impacts that will be felt very far out into the future, thereby straining the concept of time discounting and placing a heavy burden on the choice of an interest rate. Nor does uniqueness come from the unsure outcome of a stochastic process with known structure and known objective-frequency probabilities. Much more unsettling for an application of (present discounted) expected utility analysis are the unknowns: deep structural uncertainty in the science coupled with an economic inability to evaluate meaningfully the catastrophic losses from disastrous temperature changes. The climate science seems to be saying that the probability of a disastrous collapse of planetary welfare is non-negligible, even if this � Without blaming them for remaining de…ciencies of the paper, I am extremely grateful for the construc-

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