Endogenous Risks and Learning in Climate Change Decision Analysis

  • B. O’Neill
  • Y. Ermoliev
  • T. Ermolieva
Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 581)

Abstract

We analyze the effects of risks and learning on climate change decisions. Using a new two-stage, dynamic, climate change stabilization model with random time horizons, we show that the explicit incorporation of ex-post learning and safety constraints induces risk aversion in ex-ante decisions. This risk aversion takes the form in linear models of VaR- and CVaR-type risk measures. We also analyze extensions of the model that account for the possibility of nonlinear costs, limited emissions abatement capacity, and partial learning. We find that in all cases, even in linear models, any conclusion about the effect of learning can be reversed. Namely, learning may lead to either less- or more restrictive ex-ante emission reductions depending on model assumptions regarding costs, the distributions describing uncertainties, and assumptions about what might be learned. We analyze stylized elements of the model in order to identify the key factors driving outcomes and conclude that, unlike in most previous models, the quantiles of probability distributions play a critical role in solutions.

Key words

stochastic nonsmooth optimization climate stabilization learning catastrophic risk 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Alley, R.B., Marotzke, J., Nordhaus, W.D., Overpeck, J.T., Peteet, D.M., Pielke Jr., R.A., Pierrehumbert, R.T., Rhines, P.B., Stocker, T.F., Talley, L.D., Wallace, J.M. Abrupt Climate Change. Science. 299.Google Scholar
  2. 2.
    Arrow, K.J., Fisher, A.C. (1974) Environmental Preservation, Uncertainty, and Irreversibility. Quarterly Journal of Economics. 88, 312–319.CrossRefGoogle Scholar
  3. 3.
    Chichilnisky, G., Heal, G. (1993) Global Environmental Risks. Journal of Economic Perspectives. 7(4), 65–86. Analysis.Google Scholar
  4. 4.
    Dantzig, G., Madansky, A. (1961) On the Solution of Two-stage Linear Programs under Uncertainty. Proc. Fourth Berkeley Symposium on Mathematical Statistics and Probability. 1, 165–176, Univ. California Press, Berkley..Google Scholar
  5. 5.
    Dixit, A.K., Pindyck, R.S. (1994) Investments under Uncertainty. Princeton University Press.Google Scholar
  6. 6.
    Embrechts, P., Klueppelberg, C., Mikosch, T. (2000) Modeling Extremal Events for Insurance and Finance. Applications of Mathematics, Stochastic Modeling and Applied Probability. Springer Verlag, Heidelberg.Google Scholar
  7. 7.
    Epstein, L.G. (1980) Decision Making and the Temporal Resolution of Uncertainty. International Economic Review, 21(2), 269–282.MATHMathSciNetCrossRefGoogle Scholar
  8. 8.
    Ermoliev, Y., Ermolieva, T.Y., MacDonald, G., and Norkin, V. (2000) Stochastic Optimization of Insurance Portfolios for Managing Exposure to Catastrophic Risks. Annals of Operations Research. 99, 207–225.MATHMathSciNetCrossRefGoogle Scholar
  9. 9.
    Ermoliev, Y.M., Norkin, V.I. (1997) On Nonsmooth and Discontinuous Problems of Stochastic Systems Optimization. European Journal of European Research. 101, 230–244.MATHCrossRefGoogle Scholar
  10. 10.
    Ermoliev, Y., Wets, R. (Eds., 1988) Numerical Techniques for Stochastic Optimization. Computational Mathematics, Springer Verlag, Berlin.Google Scholar
  11. 11.
    Fisher, A.C., Narain, U. (2003) Global Warming, Endogenous Risk, and Irreversibility. Environmental and Resource Economics. 25, 395–416.CrossRefGoogle Scholar
  12. 12.
    Ha-Duong, M., Hourcade, J.-C., Grubb, M. (1997) The Influence of Inertia and Uncertainty upon Optimal CO2 Policies. Nature. 390, 270–274.CrossRefADSGoogle Scholar
  13. 13.
    Henry, C. (1974) Investment Decisions under Uncertainty: The Irreversibility Effect. American Economic Review. 64/6, 1006–1012.Google Scholar
  14. 14.
    IPCC (2001) Climate Change 2001: The Scientific Basis. Technical Report. Intergovernmental Panel on Climate Change.Google Scholar
  15. 15.
    Kall, P., Wallace, S.W. (1994) Stochastic Programming. J. Wiley, Chichaster.Google Scholar
  16. 16.
    Kolstad, C.D. (1996) Learning and Stock Effects in Environmental Regulations: The Case of Greenhouse Gas Emissions. Journal of Environmental Economics and Management. 31, 1–18.MATHCrossRefGoogle Scholar
  17. 17.
    Manne, A.S., Richels, R.G. (1992) Buying Greenhouse Insurance: The Economic Costs of Carbon Dioxide Emission Limits. Cambridge, Mass., MIT Press.Google Scholar
  18. 18.
    Marti, K. (2005) Stochastic Optimization Methods. Springer, Berlin, Heidelberg.MATHGoogle Scholar
  19. 19.
    O’Neill, B., Oppenheimer, M. (2002) Dangerous Climate Impacts and the Kyoto Protocol. Science. 296, 1971–1972.PubMedCrossRefGoogle Scholar
  20. 20.
    Nordhaus, W.D. (1994) Managing the Global Commons: The Economics of Climate Change. Cambridge, Mass.: MIT Press.Google Scholar
  21. 21.
    Pindyck, R.S. (1999) Irreversibilities and the Timing of Environmental Policy. Working Paper 99-005, Center for Energy and Environmental Policy Research, Massachusetts Institute of Technology, Cambridge, MA.Google Scholar
  22. 22.
    Rockafellar, T., Uryasev, S. (2000) Optimization of Conditional Value-at-Risk. The Journal of Risk. 2/3, 21–41.Google Scholar
  23. 23.
    Schultz, P.A., Kasting, J.F. (1997) Optimal Reduction in CO2 Emissions. Energy Policy. 25/5, 491–500.CrossRefGoogle Scholar
  24. 24.
    Ulph, A., Ulph, D. (1997) Global Warming, Irreversibility and Learning. Economic Journal. 107/442, 636–650.CrossRefGoogle Scholar
  25. 25.
    Viscusi, W.K., Zeckhauser, R. (1976) Environmental Policy Choice under Uncertainty. Journal of Environmental and Economic Management. 3, 97–112. Kiev (In Ukrainian).CrossRefGoogle Scholar
  26. 26.
    Yastremskij, A. (1983): Stochastic Models of Mathematical Economics. Vischa Shkola, Kiev (In Russian).MATHGoogle Scholar
  27. 27.
    Webster, M. (2002) The Curious Role of “Learning” in Climate Policy: Should We Wait for More Data? The Energy Journal. 23/2, 97–119.Google Scholar
  28. 28.
    Wright, E.L., Erickson, J.D. (2003) Incorporating Catastrophes into Integrated Assessment: Science, Impacts, and Adaptation. Climate Change. 57, 265–286.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • B. O’Neill
    • 1
  • Y. Ermoliev
    • 1
  • T. Ermolieva
    • 1
  1. 1.Institute for Applied Systems AnalysisLaxenburgAustria

Personalised recommendations