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Transient temperature response modeling in IAMs: the effects of over simplification on the SCC

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  • Marten, Alex L.

Abstract

Integrated Assessment Models (IAMs) couple representations of the natural climate system with models of the global economy to capture interactions that are important for the evaluation of potential climate and energy policies. The U.S. federal government currently uses such models to derive the benefits of carbon mitigation policies through estimates of the social cost of carbon (SCC). To remain tractable these models often utilize highly simplified representations of complex natural, social, and economic systems. This makes IAMs susceptible to oversimplification by failing to capture key features of the underlying system that are important for policy analysis. In this paper we focus on one area in which these models appear to have fallen into such a trap. We consider three prominent IAMs, DICE, FUND, and PAGE, and examine the way in which these models represent the transient temperature response to increases in radiative forcing. We compare the highly simplified temperature response models in these IAMs to two upwelling diffusion energy balance models that better reflect the progressive uptake of heat by the deep ocean. We find that all three IAMs are unable to fully capture important characteristics in the temporal dynamics of temperature response, especially in the case of high equilibrium climate sensitivity. This has serious implications given that these models are often run with distributions for the equilibrium climate sensitivity that contain a positive probability for such states of the world. We find that all else equal the temperature response function utilized in the FUND model results in estimates of the expected SCC that are up to 25% lower than those derived with the more realistic climate models, while the functions used in DICE and PAGE lead to expected SCC estimates up to 40% and 50% higher, respectively.

Suggested Citation

  • Marten, Alex L., 2011. "Transient temperature response modeling in IAMs: the effects of over simplification on the SCC," Economics Discussion Papers 2011-11, Kiel Institute for the World Economy.
  • Handle: RePEc:zbw:ifwedp:201111
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    Cited by:

    1. Richard S. J. Tol, 2024. "Database for the meta-analysis of the social cost of carbon (v2026.1)," Papers 2402.09125, arXiv.org, revised Jan 2026.
    2. 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.
    3. Kögel, Tomas, 2011. "The social cost of carbon on an optimal balanced growth path," Economics Discussion Papers 2011-35, Kiel Institute for the World Economy.
    4. Raphael Calel & David Stainforth & Simon Dietz, 2015. "Tall tales and fat tails: the science and economics of extreme warming," Climatic Change, Springer, vol. 132(1), pages 127-141, September.
    5. Kevin D. Dayaratna & Ross McKitrick & Patrick J. Michaels, 2020. "Climate sensitivity, agricultural productivity and the social cost of carbon in FUND," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 22(3), pages 433-448, July.
    6. Newbold, Stephen C. & Marten, Alex L., 2014. "The value of information for integrated assessment models of climate change," Journal of Environmental Economics and Management, Elsevier, vol. 68(1), pages 111-123.
    7. In Chang Hwang & Richard S. J. Tol & Marjan W. Hofkes, 2019. "Active Learning and Optimal Climate Policy," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(4), pages 1237-1264, August.
    8. Hwang, In Chang & Reynès, Frédéric & Tol, Richard S.J., 2017. "The effect of learning on climate policy under fat-tailed risk," Resource and Energy Economics, Elsevier, vol. 48(C), pages 1-18.
    9. Alex L. Marten, 2014. "The Role Of Scenario Uncertainty In Estimating The Benefits Of Carbon Mitigation," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 5(03), pages 1-29.
    10. Alex Marten & Robert Kopp & Kate Shouse & Charles Griffiths & Elke Hodson & Elizabeth Kopits & Bryan Mignone & Chris Moore & Steve Newbold & Stephanie Waldhoff & Ann Wolverton, 2013. "Improving the assessment and valuation of climate change impacts for policy and regulatory analysis," Climatic Change, Springer, vol. 117(3), pages 433-438, April.
    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. Kopp, Robert E. & Mignone, Bryan K., 2012. "The US government's social cost of carbon estimates after their first two years: Pathways for improvement," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-41.
    13. KEVIN DAYARATNA & ROSS McKITRICK & DAVID KREUTZER, 2017. "Empirically Constrained Climate Sensitivity And The Social Cost Of Carbon," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 8(02), pages 1-12, May.
    14. Marten, Alex L., 2014. "The Role of Scenario Uncertainty in Estimating the Benefits of Carbon Mitigation," National Center for Environmental Economics-NCEE Working Papers 280920, United States Environmental Protection Agency (EPA).
    15. Richard S. J. Tol, 2021. "Estimates of the social cost of carbon have increased over time," Papers 2105.03656, arXiv.org, revised Aug 2022.
    16. Stephen C. Newbold & Charles Griffiths & Chris Moore & Ann Wolverton & Elizabeth Kopits, 2013. "A Rapid Assessment Model For Understanding The Social Cost Of Carbon," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 4(01), pages 1-40.
    17. 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.
    18. Hwang, In Chang & Tol, Richard S.J. & Hofkes, Marjan W., 2016. "Fat-tailed risk about climate change and climate policy," Energy Policy, Elsevier, vol. 89(C), pages 25-35.
    19. Louise Kessler, 2017. "Estimating The Economic Impact Of The Permafrost Carbon Feedback," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 8(02), pages 1-23, May.
    20. Louise Kessler, 2015. "Estimating the economic impact of the permafrost carbon feedback," GRI Working Papers 219, Grantham Research Institute on Climate Change and the Environment.
    21. Richard S.J. Tol, 2021. "Estimates of the social cost of carbon have not changed over time," Working Paper Series 0821, Department of Economics, University of Sussex Business School.

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    JEL classification:

    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

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