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Expected Utility and Catastrophic Risk in a Stochastic Economy-Climate Model

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  • Ikefuji, M.
  • Laeven, R.J.A.

    (Tilburg University, School of Economics and Management)

  • Magnus, J.R.

    (Tilburg University, School of Economics and Management)

  • Muris, C.H.M.

    (Tilburg University, School of Economics and Management)

Abstract

We analyze a stochastic dynamic finite-horizon economic model with climate change, in which the social planner faces uncertainty about future climate change and its economic damages. Our model (SDICE*) incorporates, possibly heavy-tailed, stochasticity in Nordhaus’ deterministic DICE model. We develop a regression-based numerical method for solving a general class of dynamic finite-horizon economy–climate models with potentially heavy-tailed uncertainty and general utility functions. We then apply this method to SDICE* and examine the effects of light- and heavy-tailed uncertainty. The results indicate that the effects can be substantial, depending on the nature and extent of the uncertainty and the social planner’s preferences.
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  • Ikefuji, M. & Laeven, R.J.A. & Magnus, J.R. & Muris, C.H.M., 2010. "Expected Utility and Catastrophic Risk in a Stochastic Economy-Climate Model," Other publications TiSEM 52cbee73-e1dc-4ed3-8ec9-6, Tilburg University, School of Economics and Management.
    • Handle: RePEc:tiu:tiutis:52cbee73-e1dc-4ed3-8ec9-61bd0090c3da
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    1. Simone Cerreia‐Vioglio & David Dillenberger & Pietro Ortoleva, 2015. "Cautious Expected Utility and the Certainty Effect," Econometrica, Econometric Society, vol. 83, pages 693-728, March.
    2. Michael W. Brandt & Amit Goyal & Pedro Santa-Clara & Jonathan R. Stroud, 2005. "A Simulation Approach to Dynamic Portfolio Choice with an Application to Learning About Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 831-873.
    3. Carriere, Jacques F., 1996. "Valuation of the early-exercise price for options using simulations and nonparametric regression," Insurance: Mathematics and Economics, Elsevier, vol. 19(1), pages 19-30, December.
    4. Kenneth Gillingham & William D. Nordhaus & David Anthoff & Geoffrey Blanford & Valentina Bosetti & Peter Christensen & Haewon McJeon & John Reilly & Paul Sztorc, 2015. "Modeling Uncertainty in Climate Change: A Multi-Model Comparison," NBER Working Papers 21637, National Bureau of Economic Research, Inc.
    5. Simon Dietz, 2011. "High impact, low probability? An empirical analysis of risk in the economics of climate change," Climatic Change, Springer, vol. 108(3), pages 519-541, October.
    6. Derek Lemoine & Christian Traeger, 2014. "Watch Your Step: Optimal Policy in a Tipping Climate," American Economic Journal: Economic Policy, American Economic Association, vol. 6(1), pages 137-166, February.
    7. Chichilnisky, Graciela, 2000. "An axiomatic approach to choice under uncertainty with catastrophic risks," Resource and Energy Economics, Elsevier, vol. 22(3), pages 221-231, July.
    8. Ikefuji, M. & Laeven, R.J.A. & Magnus, J.R. & Muris, C.H.M., 2010. "Burr Utility," Other publications TiSEM fddee215-edea-4800-ba72-d, Tilburg University, School of Economics and Management.
      • Ikefuji, M. & Laeven, R.J.A. & Magnus, J.R. & Muris, C.H.M., 2010. "Burr Utility," Discussion Paper 2010-81, Tilburg University, Center for Economic Research.
    9. Christopher A. Sims, 2001. "Pitfalls of a Minimax Approach to Model Uncertainty," American Economic Review, American Economic Association, vol. 91(2), pages 51-54, May.
    10. Marco Moscadelli, 2004. "The modelling of operational risk: experience with the analysis of the data collected by the Basel Committee," Temi di discussione (Economic working papers) 517, Bank of Italy, Economic Research and International Relations Area.
    11. Robert S. Pindyck, 2011. "Fat Tails, Thin Tails, and Climate Change Policy," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 5(2), pages 258-274, Summer.
    12. Geweke, John, 2001. "A note on some limitations of CRRA utility," Economics Letters, Elsevier, vol. 71(3), pages 341-345, June.
    13. Gollier, Christian, 2002. "Time Horizon and the Discount Rate," Journal of Economic Theory, Elsevier, vol. 107(2), pages 463-473, December.
    14. Schmitt-Grohe, Stephanie & Uribe, Martin, 2004. "Optimal fiscal and monetary policy under imperfect competition," Journal of Macroeconomics, Elsevier, vol. 26(2), pages 183-209, June.
    15. Martin L. Weitzman, 2009. "On Modeling and Interpreting the Economics of Catastrophic Climate Change," The Review of Economics and Statistics, MIT Press, vol. 91(1), pages 1-19, February.
    16. Schmitt-Grohe, Stephanie & Uribe, Martin, 2004. "Optimal fiscal and monetary policy under sticky prices," Journal of Economic Theory, Elsevier, vol. 114(2), pages 198-230, February.
    17. Kimball, Miles S, 1990. "Precautionary Saving in the Small and in the Large," Econometrica, Econometric Society, vol. 58(1), pages 53-73, January.
    18. Gilboa,Itzhak, 2009. "Theory of Decision under Uncertainty," Cambridge Books, Cambridge University Press, number 9780521517324, January.
    19. Ikefuji, M. & Laeven, R.J.A. & Magnus, J.R. & Muris, C.H.M., 2010. "Scrap Value Functions in Dynamic Decision Problems," Discussion Paper 2010-77, Tilburg University, Center for Economic Research.
    20. Ikefuji, Masako & Laeven, Roger J.A. & Magnus, Jan R. & Muris, Chris, 2015. "Expected utility and catastrophic consumption risk," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 306-312.
    21. Nordhaus, William D & Yang, Zili, 1996. "A Regional Dynamic General-Equilibrium Model of Alternative Climate-Change Strategies," American Economic Review, American Economic Association, vol. 86(4), pages 741-765, September.
    22. Christian Traeger, 2014. "A 4-Stated DICE: Quantitatively Addressing Uncertainty Effects in Climate Change," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 59(1), pages 1-37, September.
    23. In Hwang & Frédéric Reynès & Richard Tol, 2013. "Climate Policy Under Fat-Tailed Risk: An Application of Dice," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 56(3), pages 415-436, November.
    24. Yongyang Cai & Timothy M. Lenton & Thomas S. Lontzek, 2016. "Risk of multiple interacting tipping points should encourage rapid CO2 emission reduction," Nature Climate Change, Nature, vol. 6(5), pages 520-525, May.
    25. Leach, Andrew J., 2007. "The climate change learning curve," Journal of Economic Dynamics and Control, Elsevier, vol. 31(5), pages 1728-1752, May.
    26. Matthew Rabin, 2000. "Risk Aversion and Expected-Utility Theory: A Calibration Theorem," Econometrica, Econometric Society, vol. 68(5), pages 1281-1292, September.
    27. Alan Manne & Richard Richels, 1992. "Buying Greenhouse Insurance: The Economic Costs of CO2 Emission Limits," MIT Press Books, The MIT Press, edition 1, volume 1, number 026213280x, December.
    28. Roger J. A. Laeven & Mitja Stadje, 2014. "Robust Portfolio Choice and Indifference Valuation," Mathematics of Operations Research, INFORMS, vol. 39(4), pages 1109-1141, November.
    29. Buchholz, Wolfgang & Schymura, Michael, 2012. "Expected utility theory and the tyranny of catastrophic risks," Ecological Economics, Elsevier, vol. 77(C), pages 234-239.
    30. Keller, Klaus & Bolker, Benjamin M. & Bradford, D.F.David F., 2004. "Uncertain climate thresholds and optimal economic growth," Journal of Environmental Economics and Management, Elsevier, vol. 48(1), pages 723-741, July.
    31. -, 2009. "The economics of climate change," Sede Subregional de la CEPAL para el Caribe (Estudios e Investigaciones) 38679, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    32. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," University of California at Los Angeles, Anderson Graduate School of Management qt43n1k4jb, Anderson Graduate School of Management, UCLA.
    33. King, Robert G. & Rebelo, Sergio T., 1999. "Resuscitating real business cycles," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 14, pages 927-1007, Elsevier.
    34. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 113-147.
    35. Robert J. Barro & Jose F. Ursua, 2008. "Consumption Disasters in the Twentieth Century," American Economic Review, American Economic Association, vol. 98(2), pages 58-63, May.
    36. Stern,Nicholas, 2007. "The Economics of Climate Change," Cambridge Books, Cambridge University Press, number 9780521700801, January.
    37. Roughgarden, Tim & Schneider, Stephen H., 1999. "Climate change policy: quantifying uncertainties for damages and optimal carbon taxes," Energy Policy, Elsevier, vol. 27(7), pages 415-429, July.
    38. Kenneth J. Arrow, 1974. "The Use of Unbounded Utility Functions in Expected-Utility Maximization: Response," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 88(1), pages 136-138.
    39. Christian Gollier, 2008. "Discounting with fat-tailed economic growth," Journal of Risk and Uncertainty, Springer, vol. 37(2), pages 171-186, December.
    40. Loïc Berger & Johannes Emmerling & Massimo Tavoni, 2017. "Managing Catastrophic Climate Risks Under Model Uncertainty Aversion," Post-Print hal-01744501, HAL.
    41. Robert J. Barro, 2009. "Rare Disasters, Asset Prices, and Welfare Costs," American Economic Review, American Economic Association, vol. 99(1), pages 243-264, March.
    42. Johannes Brumm & Simon Scheidegger, 2017. "Using Adaptive Sparse Grids to Solve High‐Dimensional Dynamic Models," Econometrica, Econometric Society, vol. 85, pages 1575-1612, September.
    43. Peter H. Howard & Thomas Sterner, 2017. "Few and Not So Far Between: A Meta-analysis of Climate Damage Estimates," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 68(1), pages 197-225, September.
    44. Dietz, Simon, 2011. "High impact, low probability?: an empirical analysis of risk in the economics of climate change," LSE Research Online Documents on Economics 38586, London School of Economics and Political Science, LSE Library.
    45. Masako Ikefuji & Roger Laeven & Jan Magnus & Chris Muris, 2013. "Pareto utility," Theory and Decision, Springer, vol. 75(1), pages 43-57, July.
    46. Peter C. Fishburn, 1976. "Unbounded Utility Functions in Expected Utility Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 90(1), pages 163-168.
    47. 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.
    48. Ackerman, Frank & Stanton, Elizabeth A. & Bueno, Ramón, 2010. "Fat tails, exponents, extreme uncertainty: Simulating catastrophe in DICE," Ecological Economics, Elsevier, vol. 69(8), pages 1657-1665, June.
    49. Volker Krätschmer & Marcel Ladkau & Roger J. A. Laeven & John G. M. Schoenmakers & Mitja Stadje, 2018. "Optimal Stopping Under Uncertainty in Drift and Jump Intensity," Mathematics of Operations Research, INFORMS, vol. 43(4), pages 1177-1209, November.
    50. Jensen, Svenn & Traeger, Christian P., 2014. "Optimal climate change mitigation under long-term growth uncertainty: Stochastic integrated assessment and analytic findings," European Economic Review, Elsevier, vol. 69(C), pages 104-125.
    51. Loïc Berger & Johannes Emmerling & Massimo Tavoni, 2017. "Managing Catastrophic Climate Risks Under Model Uncertainty Aversion," Management Science, INFORMS, vol. 63(3), pages 749-765, March.
    52. Philip Protter & Emmanuelle Clément & Damien Lamberton, 2002. "An analysis of a least squares regression method for American option pricing," Finance and Stochastics, Springer, vol. 6(4), pages 449-471.
    53. Terence M. Ryan, 1974. "The Use of Unbounded Utility Functions in Expected-Utility Maximization: Comment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 88(1), pages 133-135.
    54. Dhami, Sanjit & Al-Nowaihi, Ali, 2010. "Optimal taxation in the presence of tax evasion: Expected utility versus prospect theory," Journal of Economic Behavior & Organization, Elsevier, vol. 75(2), pages 313-337, August.
    55. Thomas S. Lontzek & Yongyang Cai & Kenneth L. Judd & Timothy M. Lenton, 2015. "Stochastic integrated assessment of climate tipping points indicates the need for strict climate policy," Nature Climate Change, Nature, vol. 5(5), pages 441-444, May.
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    7. Ikefuji, M. & Laeven, R.J.A. & Magnus, J.R. & Muris, C.H.M., 2010. "Burr Utility," Discussion Paper 2010-81, Tilburg University, Center for Economic Research.
      • Ikefuji, M. & Laeven, R.J.A. & Magnus, J.R. & Muris, C.H.M., 2010. "Burr Utility," Other publications TiSEM fddee215-edea-4800-ba72-d, Tilburg University, School of Economics and Management.
    8. Lucas Bretschger & Alexandra Vinogradova, 2014. "Growth and Mitigation Policies with Uncertain Climate Damage," CEEES Paper Series CE3S-02/14, European University at St. Petersburg, Department of Economics.
    9. Bretschger, Lucas & Suphaphiphat, Nujin, 2014. "Effective climate policies in a dynamic North–South model," European Economic Review, Elsevier, vol. 69(C), pages 59-77.
    10. Christian Fries & Lennart Quante, 2023. "Intergenerational Equity in Models of Climate Change Mitigation: Stochastic Interest Rates introduce Adverse Effects, but (Non-linear) Funding Costs can Improve Intergenerational Equity," Papers 2309.16186, arXiv.org, revised Sep 2023.
    11. Stanca Lorenzo, 2023. "Robust Bayesian Choice," Working papers 079, Department of Economics, Social Studies, Applied Mathematics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.
    12. Lorenzo Stanca, 2023. "Robust Bayesian Choice," Carlo Alberto Notebooks 690 JEL Classification: C, Collegio Carlo Alberto.
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    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • E2 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics

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