Fat Tails, Thin Tails, and Climate Change Policy

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 goo...

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Main Author: Pindyck, Robert S.
Format: Working Paper
Language:en_US
Published: MIT Center for Energy and Environmental Policy Research 2010
Online Access:http://hdl.handle.net/1721.1/59466
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author Pindyck, Robert S.
author_facet Pindyck, Robert S.
author_sort Pindyck, Robert S.
collection MIT
description 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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spelling mit-1721.1/594662019-04-12T11:34:37Z Fat Tails, Thin Tails, and Climate Change Policy Pindyck, Robert S. 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. - Massachusetts Institute of Technology. Center for Energy and Environmental Policy Research. 2010-10-22T14:38:06Z 2010-10-22T14:38:06Z 2010-09 Working Paper 2010-012 http://hdl.handle.net/1721.1/59466 en_US MIT-CEEPR (Series);2010-012 application/pdf MIT Center for Energy and Environmental Policy Research
spellingShingle Pindyck, Robert S.
Fat Tails, Thin Tails, and Climate Change Policy
title Fat Tails, Thin Tails, and Climate Change Policy
title_full Fat Tails, Thin Tails, and Climate Change Policy
title_fullStr Fat Tails, Thin Tails, and Climate Change Policy
title_full_unstemmed Fat Tails, Thin Tails, and Climate Change Policy
title_short Fat Tails, Thin Tails, and Climate Change Policy
title_sort fat tails thin tails and climate change policy
url http://hdl.handle.net/1721.1/59466
work_keys_str_mv AT pindyckroberts fattailsthintailsandclimatechangepolicy