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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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    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 Business School.
    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 Business School.
    3. Xin Li & Borghan N. Narajabad & Ted Temzelides, 2014. "Robust Dynamic Optimal Taxation and Environmental Externalities," Finance and Economics Discussion Series 2014-75, Board of Governors of the Federal Reserve System (U.S.).
    4. Lemoine, Derek & Traeger, Christian P., 2016. "Ambiguous tipping points," Journal of Economic Behavior & Organization, Elsevier, vol. 132(PB), pages 5-18.
    5. Kousky, Carolyn & Kopp, Robert E. & Cooke, Roger M., 2011. "Risk premia and the social cost of carbon: A review," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 5, pages 1-24.
    6. David Anthoff & Richard Tol, 2014. "Climate policy under fat-tailed risk: an application of FUND," Annals of Operations Research, Springer, vol. 220(1), pages 223-237, September.
    7. Brock, William & Xepapadeas, Anastasios, 2021. "Regional climate policy under deep uncertainty: robust control and distributional concerns," Environment and Development Economics, Cambridge University Press, vol. 26(3), pages 211-238, June.
    8. In Chang Hwang, 2017. "A Recursive Method for Solving a Climate–Economy Model: Value Function Iterations with Logarithmic Approximations," Computational Economics, Springer;Society for Computational Economics, vol. 50(1), pages 95-110, June.
    9. Anderson, Evan W. & Brock, William & Sanstad, Alan H., 2016. "Robust Consumption and Energy Decisions," 2017 Allied Social Sciences Association (ASSA) Annual Meeting, January 6-8, 2017, Chicago, Illinois 250117, Agricultural and Applied Economics Association.
    10. Peter von zur Muehlen, 2022. "Prices and Taxes in a Ramsey Climate Policy Model under Heterogeneous Beliefs and Ambiguity," Economies, MDPI, vol. 10(10), pages 1-56, October.
    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. 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.
    13. William Brock & Anastasios Xepapadeas, 2019. "Regional Climate Policy under Deep Uncertainty: Robust Control, Hot Spots and Learning," DEOS Working Papers 1903, Athens University of Economics and Business.
    14. 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.
    15. William Brock & Anastasios Xepapadeas, 2019. "Regional Climate Policy under Deep Uncertainty," DEOS Working Papers 1901, Athens University of Economics and Business.
    16. 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 Business School.
    17. Mark Kagan, 2012. "Climate Change Skepticism in the Face of Catastrophe," Tinbergen Institute Discussion Papers 12-112/VIII, Tinbergen Institute, revised 29 Sep 2014.

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    More about this item

    Keywords

    robust control; climate change policy; carbon cost; Knightian uncertainty; ambiguity aversion; integrated assessment models;
    All these keywords.

    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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