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Fat Tails, Thin Tails, and Climate Change Policy

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  • Robert S. Pindyck

Abstract

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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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 16353.

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Date of creation: Sep 2010
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Publication status: published as Robert S. Pindyck, 2011. "Fat Tails, Thin Tails, and Climate Change Policy," Review of Environmental Economics and Policy, Oxford University Press for Association of Environmental and Resource Economists, vol. 5(2), pages 258-274, Summer.
Handle: RePEc:nbr:nberwo:16353

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  1. Geoffrey Heal & Bengt Kriström, 2002. "Uncertainty and Climate Change," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 22(1), pages 3-39, June.
  2. Robert S. Pindyck, 2009. "Uncertain Outcomes and Climate Change Policy," Working Papers 0907, Massachusetts Institute of Technology, Center for Energy and Environmental Policy Research.
  3. Robert S. Pindyck & Neng Wang, 2009. "The Economic and Policy Consequences of Catastrophes," NBER Working Papers 15373, National Bureau of Economic Research, Inc.
  4. Robert S. Pindyck, 2011. "Modeling the Impact of Warming in Climate Change Economics," NBER Chapters, in: The Economics of Climate Change: Adaptations Past and Present, pages 47-71 National Bureau of Economic Research, Inc.
  5. Adam Daigneault & Steve Newbold, 2009. "Climate Response Uncertainty and the Unexpected Benefits of Greenhouse Gas Emissions Reductions," NCEE Working Paper Series 200806, National Center for Environmental Economics, U.S. Environmental Protection Agency, revised Mar 2009.
  6. Pindyck, Robert S., 2002. "Optimal timing problems in environmental economics," Journal of Economic Dynamics and Control, Elsevier, vol. 26(9-10), pages 1677-1697, August.
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Cited by:
  1. Matthew J. Holian & Matthew E. Kahn, 2014. "Household Demand for Low Carbon Public Policies: Evidence from California," NBER Working Papers 19965, National Bureau of Economic Research, Inc.
  2. Pycroft, Jonathan & Vergano, Lucia & Hope, Chris & Paci, Daniele & Ciscar, Juan Carlos, 2011. "A tale of tails: Uncertainty and the social cost of carbon dioxide," Economics Discussion Papers 2011-36, Kiel Institute for the World Economy.
  3. In Hwang & Frédéric Reynès & Richard Tol, 2013. "Climate Policy Under Fat-Tailed Risk: An Application of Dice," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 56(3), pages 415-436, November.
  4. Robert N. Stavins, 2011. "The Problem of the Commons: Still Unsettled after 100 Years," American Economic Review, American Economic Association, vol. 101(1), pages 81-108, February.
  5. Kousky, Carolyn & Kopp, Robert E. & Cooke, Roger, 2011. "Risk premia and the social cost of carbon: A review," Economics Discussion Papers 2011-19, Kiel Institute for the World Economy.
  6. Tol, Richard S.J., 2013. "Targets for global climate policy: An overview," Journal of Economic Dynamics and Control, Elsevier, vol. 37(5), pages 911-928.
  7. In Chang Hwang & Richard S.J. Tol & Marjan W. Hofkes, 2013. "Tail-effect and the Role of Greenhouse Gas Emissions Control," Working Paper Series 6613, Department of Economics, University of Sussex.
  8. Simon Dietz & Anca N. Matei, 2013. "Is there space for agreement on climate change? A non-parametric approach to policy evaluation," Grantham Research Institute on Climate Change and the Environment Working Papers 136, Grantham Research Institute on Climate Change and the Environment.
  9. Xepapadeas, Anastasios & Ralli, Parthenopi & Kougea, Eva & Spyrou, Sofia & Stavropoulos, Nikolaos & Tsiaousi, Vasiliki & Tsivelikas, Athanasios, 2014. "Valuing insurance services emerging from a gene bank: The case of the Greek Gene Bank," Ecological Economics, Elsevier, vol. 97(C), pages 140-149.
  10. Hwang, In Chang, 2014. "Fat-tailed uncertainty and the learning-effect," MPRA Paper 53671, University Library of Munich, Germany.
  11. Benjamin Jones & Michael Keen & Jon Strand, 2013. "Fiscal implications of climate change," International Tax and Public Finance, Springer, vol. 20(1), pages 29-70, February.
  12. David Martimort & Stéphane Straub, 2011. "How to Design Public-Private Partnerships in a Warming World? - When Infrastructure Becomes a Really “Hot” Topic," Working Papers 2011/25, Maastricht School of Management.
  13. Tack, Jesse, 2013. "A Nested Test for Common Yield Distributions with Applications to U.S. Corn," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 38(1), April.
  14. In Chang Hwang & Richard S.J. Tol & Marjan W. Hofkes, 2013. "Active Learning about Climate Change," Working Paper Series 6513, Department of Economics, University of Sussex.
  15. Boyarchenko, Svetlana & Levendorskii, Sergei, 2010. "Discounting when income is stochastic and climate change policies," MPRA Paper 27998, University Library of Munich, Germany.

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