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Optimal Learning on Climate Change: Why climate skeptics should reduce emissions

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  • Sweder van Wijnbergen
  • Tim Willems

Abstract

Climate skeptics typically argue that the possibility that global warming is exogenous, implies that we should not take additional action towards reducing emissions until we know what drives warming. This paper however shows that even climate skeptics have an incentive to reduce emissions: such a directional change generates information on the causes of global warming. Since the optimal policy depends upon these causes, they are valuable to know. Although increasing emissions would also generate information, that option is inferior due to its irreversibility. We show that optimality can even imply that climate skeptics should actually argue for lower emissions than believers.

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Bibliographic Info

Paper provided by Oxford Centre for the Analysis of Resource Rich Economies, University of Oxford in its series OxCarre Working Papers with number 111.

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Date of creation: 2013
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Handle: RePEc:oxf:oxcrwp:111

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Keywords: climate policy; global warming; climate skepticism; active learning; irreversibilities;

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  1. Bertocchi, Graziella & Spagat, Michael, 1991. "Learning, Experimentation and Monetary Policy," Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) 1991018, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
  2. Elizabeth Chase MacRae, 1972. "Linear Decision with Experimentation," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 1, number 4, pages 435-445 National Bureau of Economic Research, Inc.
  3. Grossman, Sanford J & Kihlstrom, Richard E & Mirman, Leonard J, 1977. "A Bayesian Approach to the Production of Information and Learning by Doing," Review of Economic Studies, Wiley Blackwell, vol. 44(3), pages 533-47, October.
  4. Henry, Claude, 1974. "Investment Decisions Under Uncertainty: The "Irreversibility Effect."," American Economic Review, American Economic Association, vol. 64(6), pages 1006-12, December.
  5. Sandy Grossman, 2010. "A Bayesian Approach to the Production of Information and Learning by Doing," Levine's Working Paper Archive 230, David K. Levine.
  6. Timothy Cogley & Riccardo Colacito & Lars Peter Hansen & Thomas J. Sargent, 2008. "Robustness and U.S. Monetary Policy Experimentation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(8), pages 1599-1623, December.
  7. Prescott, Edward C, 1972. "The Multi-Period Control Problem Under Uncertainty," Econometrica, Econometric Society, vol. 40(6), pages 1043-58, November.
  8. Aghion, P. & Bolton, P. & Harris, C. & Jullien, B., 1990. "Optimal Learning By Experimentation," DELTA Working Papers 90-10, DELTA (Ecole normale supérieure).
  9. Kolstad, Charles D., 1996. "Learning and Stock Effects in Environmental Regulation: The Case of Greenhouse Gas Emissions," Journal of Environmental Economics and Management, Elsevier, vol. 31(1), pages 1-18, July.
  10. 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.
  11. Epstein, Larry G, 1980. "Decision Making and the Temporal Resolution of Uncertainty," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(2), pages 269-83, June.
  12. Aghion, Philippe, et al, 1991. "Optimal Learning by Experimentation," Review of Economic Studies, Wiley Blackwell, vol. 58(4), pages 621-54, July.
  13. Gollier, C. & Jullien, B. & Treich, N., 1997. "Learning and Irreversibility: An Econmic Interpretation of the "Precautionnary Principle"," Papers 97.470, Toulouse - GREMAQ.
  14. Kolstad, Charles D., 1996. "Fundamental irreversibilities in stock externalities," Journal of Public Economics, Elsevier, vol. 60(2), pages 221-233, May.
  15. Ulph, Alistair & Ulph, David, 1997. "Global Warming, Irreversibility and Learning," Economic Journal, Royal Economic Society, vol. 107(442), pages 636-50, May.
  16. Tim Willems, 2013. "Actively Learning by Pricing: A Model of an Experimenting Seller," Economics Series Working Papers 687, University of Oxford, Department of Economics.
  17. Kelly, David L. & Kolstad, Charles D., 1999. "Bayesian learning, growth, and pollution," Journal of Economic Dynamics and Control, Elsevier, vol. 23(4), pages 491-518, February.
  18. Arrow, Kenneth J & Fisher, Anthony C, 1974. "Environmental Preservation, Uncertainty, and Irreversibility," The Quarterly Journal of Economics, MIT Press, vol. 88(2), pages 312-19, May.
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Cited by:
  1. 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.

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