Structural uncertainty and the value of statistical life in the economics of catastrophic climate change
By: Martin Weitzman.
Contributors: National Bureau of Economic Research.
Series: NBER working paper series -- no. 13490.; Working paper series (National Bureau of Economic Research) -- working paper no. 13490.
Publisher: National Bureau of Economic Research
Published: 2007
Place of publication: Cambridge, Mass
Language: eng
Number of pages: 34
Subjects: Climatic changes -- Economic aspects -- Econometric models; Disasters -- Economic aspects -- Econometric models; Life -- Valuation -- Econometric models
Description: 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.
Notes: "October 2007"

Includes bibliographical references (p. 32-34).

Also available in PDF from the NBER world wide web site (www.nber.org).