Structural Uncertainty and the Value of Statistical Life in the Economics of Catastrophic Climate Change

Martin L. Weitzman

No 13490, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Using climate change as a prototype motivating example, this paper analyzes the implications of structural uncertainty for the economics of low-probability high-impact catastrophes. The paper shows that having an uncertain multiplicative parameter, which scales or amplifies exogenous shocks and is updated by Bayesian learning, induces a critical "tail fattening" of posterior-predictive distributions. These fattened tails can 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. The essence of the problem is the difficulty of learning extreme-impact tail behavior from finite data alone. At least potentially, the influence on cost-benefit analysis of fat-tailed uncertainty about the scale of damages -- coupled with a high value of statistical life -- can outweigh the influence of discounting or anything else.

JEL-codes: Q54 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ene, nep-env and nep-hea
Date: 2007-10
Note: EEE PE
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