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Robust Control in Global Warming Management: An Analytical Dynamic Integrated Assessment

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  • Hennlock, Magnus

    () (Department of Economics, School of Business, Economics and Law, Göteborg University)

Abstract

Knightian uncertainty in climate sensitivity is analyzed in a two sectoral integrated assessment model (IAM), based on an extension of DICE. A representative household that expresses ambiguity aversion uses robust control to identify robust climate policy feedback rules that work well over IPCC climate-sensitivity uncertainty range [1]. Ambiguity aversion, together with linear damage, increases carbon cost in a similar way as a low pure rate of time preference. Secondly, in combination with non-linear damage it makes policy responsive to changes in climate data observations as it makes the household concerned about misreading sudden increases in carbon concentration rate and temperature as sources to global warming. Perfect ambiguity aversion results in an infinite expected shadow carbon cost and a zero carbon-intensive consumption path. Dynamic programming identifies an analytically tractable solution to the model.

Suggested Citation

  • Hennlock, Magnus, 2009. "Robust Control in Global Warming Management: An Analytical Dynamic Integrated Assessment," Working Papers in Economics 354, University of Gothenburg, Department of Economics.
  • Handle: RePEc:hhs:gunwpe:0354
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    File URL: http://hdl.handle.net/2077/20081
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    References listed on IDEAS

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    1. Craig R. Fox & Amos Tversky, 1995. "Ambiguity Aversion and Comparative Ignorance," The Quarterly Journal of Economics, Oxford University Press, vol. 110(3), pages 585-603.
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    7. William D. Nordhaus, 2006. "The "Stern Review" on the Economics of Climate Change," NBER Working Papers 12741, National Bureau of Economic Research, Inc.
    8. Thomas J. Sargent & LarsPeter Hansen, 2001. "Robust Control and Model Uncertainty," American Economic Review, American Economic Association, vol. 91(2), pages 60-66, May.
    9. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-291, March.
    10. Stefan Trautmann & Ferdinand Vieider & Peter Wakker, 2008. "Causes of ambiguity aversion: Known versus unknown preferences," Journal of Risk and Uncertainty, Springer, vol. 36(3), pages 225-243, June.
    11. Schmeidler, David, 1989. "Subjective Probability and Expected Utility without Additivity," Econometrica, Econometric Society, vol. 57(3), pages 571-587, May.
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    Citations

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    Cited by:

    1. Richard S. J. Tol & In Chang Hwang & Frédéric Reynès, 2012. "The Effect of Learning on Climate Policy under Fat-tailed Uncertainty," Working Paper Series 5312, Department of Economics, University of Sussex.
    2. 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.
    3. Lemoine, Derek & Traeger, Christian P., 2016. "Ambiguous tipping points," Journal of Economic Behavior & Organization, Elsevier, vol. 132(PB), pages 5-18.
    4. repec:kap:compec:v:50:y:2017:i:1:d:10.1007_s10614-016-9583-2 is not listed on IDEAS
    5. Anderson, Evan W. & Brock, William & Sanstad, Alan H., 2016. "Robust Consumption and Energy Decisions," 2017 Allied Social Science Association (ASSA) Annual Meeting, January 6-8, 2017, Chicago, Illinois 250117, Agricultural and Applied Economics Association.
    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. Mark Kagan, 2012. "Climate Change Skepticism in the Face of Catastrophe," Tinbergen Institute Discussion Papers 12-112/VIII, Tinbergen Institute, revised 29 Sep 2014.
    8. Hwang, In Chang, 2014. "A recursive method for solving a climate-economy model: value function iterations with logarithmic approximations," MPRA Paper 54782, University Library of Munich, Germany.

    More about this item

    Keywords

    robust control; climate change policy; carbon cost; Knightian uncertainty; ambiguity aversion; integrated assessment models;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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