Structural Uncertainty and the Value of Statistical Life in the Economics of Catastrophic Climate Change
AbstractUsing 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.
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Bibliographic InfoPaper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 13490.
Date of creation: Oct 2007
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Find related papers by JEL classification:
- Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-10-20 (All new papers)
- NEP-ENE-2007-10-20 (Energy Economics)
- NEP-ENV-2007-10-20 (Environmental Economics)
- NEP-HEA-2007-10-20 (Health Economics)
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