Fat Tails, Thin Tails, and Climate Change Policy
Working Papers from Massachusetts Institute of Technology, Center for Energy and Environmental Policy Research
Climate policy is complicated by the considerable compounded uncertainties over the costs and benefits of abatement. We don’t even know the probability distributions for future temperatures and impacts, making cost-benefit analysis based on expected values challenging to say the least. There are good reasons to think that those probability distributions are fat-tailed, which implies that if social welfare is based on the expectation of a CRRA utility function, we should be willing to sacrifice close to 100% of GDP to reduce GHG emissions. I argue that unbounded marginal utility makes little sense, and once we put a bound on marginal utility, this implication of fat tails goes away: Expected marginal utility will be finite even if the distribution for outcomes is fat-tailed. Furthermore, depending on the bound on marginal utility, the index of risk aversion, and the damage function, a thin-tailed distribution can yield a higher expected marginal utility (and thus a greater willingness to pay for abatement) than a fat-tailed one.
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Journal Article: Fat Tails, Thin Tails, and Climate Change Policy (2011)
Working Paper: Fat Tails, Thin Tails, and Climate Change Policy (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:mee:wpaper:1012
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