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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 Massachusetts Institute of Technology, Center for Energy and Environmental Policy Research in its series Working Papers with number 1012.

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Date of creation: Sep 2010
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Handle: RePEc:mee:wpaper:1012

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  1. Pindyck, Robert S., 2012. "Uncertain outcomes and climate change policy," Journal of Environmental Economics and Management, Elsevier, vol. 63(3), pages 289-303.
  2. Robert S. Pindyck & Neng Wang, 2013. "The Economic and Policy Consequences of Catastrophes," American Economic Journal: Economic Policy, American Economic Association, vol. 5(4), pages 306-39, November.
  3. Robert S. Pindyck, 2010. "Modeling the Impact of Warming in Climate Change Economics," NBER Working Papers 15692, National Bureau of Economic Research, Inc.
  4. 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.
  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. 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.
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Cited by:
  1. Jones, Benjamin & Keen, Michael & Strand, Jon, 2012. "Fiscal implications of climate change," Policy Research Working Paper Series 5956, The World Bank.
  2. Hwang, In Chang, 2014. "Fat-tailed uncertainty and the learning-effect," MPRA Paper 53671, University Library of Munich, Germany.
  3. 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.
  4. Stavins, Robert Norman, 2010. "The Problem of the Commons: Still Unsettled After 100 Years," Scholarly Articles 4450130, Harvard Kennedy School of Government.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. Boyarchenko, Svetlana & Levendorskii, Sergei, 2010. "Discounting when income is stochastic and climate change policies," MPRA Paper 27998, University Library of Munich, Germany.
  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. 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.

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