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Can you trust a model whose output keeps changing? Interpreting changes in the social cost of carbon produced by the DICE model

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  • Milad Eghtedari Naeini

    (The University of Texas at Austin)

  • Benjamin D. Leibowicz

    (The University of Texas at Austin)

  • J. Eric Bickel

    (The University of Texas at Austin)

Abstract

The social cost of carbon (SCC) measures the present value of the economic damages caused by emitting one marginal ton of carbon dioxide into the atmosphere. It plays a crucial role in climate policy analysis, where it is used to suggest optimal carbon prices or quantify the benefits of actions that reduce emissions. One prominent framework used to estimate the SCC is the Dynamic Integrated Climate-Economy (DICE) model. As updated versions of DICE have been introduced, its SCC estimates have changed, sometimes by amounts that would appear significant. For example, the SCC in 2020 produced by DICE rose 54% from its 2013R version to its 2016R2 version. We address two important questions. First, what changes to DICE explain this increase in its SCC? Second, how surprising is the magnitude of this increase, relative to the uncertainty present in DICE’s input parameters? We find that changes in scientific parameters and updated initial conditions due to near-term forecasting errors accounted for the largest shares of the SCC increase. The later SCC estimate falls within the 80% probability interval produced using the earlier model with uncertainty. Therefore, the 54% increase should not be considered surprising or dispositive regarding the quality of DICE itself.

Suggested Citation

  • Milad Eghtedari Naeini & Benjamin D. Leibowicz & J. Eric Bickel, 2020. "Can you trust a model whose output keeps changing? Interpreting changes in the social cost of carbon produced by the DICE model," Environment Systems and Decisions, Springer, vol. 40(3), pages 301-320, September.
    • Handle: RePEc:spr:envsyd:v:40:y:2020:i:3:d:10.1007_s10669-020-09783-y
    DOI: 10.1007/s10669-020-09783-y
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    1. William Nordhaus, 2018. "Evolution of modeling of the economics of global warming: changes in the DICE model, 1992–2017," Climatic Change, Springer, vol. 148(4), pages 623-640, June.
    2. Tol, Richard S. J., 2008. "The Social Cost of Carbon: Trends, Outliers and Catastrophes," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 2, pages 1-22.
    3. Delavane Diaz & Frances Moore, 2017. "Quantifying the economic risks of climate change," Nature Climate Change, Nature, vol. 7(11), pages 774-782, November.
    4. Roger Cooke & Bruce A. Wielicki & David F. Young & Martin G. Mlynczak, 2014. "Value of information for climate observing systems," Environment Systems and Decisions, Springer, vol. 34(1), pages 98-109, March.
    5. Kriegler, Elmar & Petermann, Nils & Krey, Volker & Schwanitz, Valeria Jana & Luderer, Gunnar & Ashina, Shuichi & Bosetti, Valentina & Eom, Jiyong & Kitous, Alban & Méjean, Aurélie & Paroussos, Leonida, 2015. "Diagnostic indicators for integrated assessment models of climate policy," Technological Forecasting and Social Change, Elsevier, vol. 90(PA), pages 45-61.
    6. Crost, Benjamin & Traeger, Christian P., 2013. "Optimal climate policy: Uncertainty versus Monte Carlo," Economics Letters, Elsevier, vol. 120(3), pages 552-558.
    7. Scrieciu, S. Şerban & Barker, Terry & Ackerman, Frank, 2013. "Pushing the boundaries of climate economics: critical issues to consider in climate policy analysis," Ecological Economics, Elsevier, vol. 85(C), pages 155-165.
    8. J. Eric Bickel, 2013. "Climate engineering and climate tipping-point scenarios," Environment Systems and Decisions, Springer, vol. 33(1), pages 152-167, March.
    9. Andries Hof & Chris Hope & Jason Lowe & Michael Mastrandrea & Malte Meinshausen & Detlef Vuuren, 2012. "The benefits of climate change mitigation in integrated assessment models: the role of the carbon cycle and climate component," Climatic Change, Springer, vol. 113(3), pages 897-917, August.
    10. Nicholas Stern, 2013. "The Structure of Economic Modeling of the Potential Impacts of Climate Change: Grafting Gross Underestimation of Risk onto Already Narrow Science Models," Journal of Economic Literature, American Economic Association, vol. 51(3), pages 838-859, September.
    11. David Anthoff & Richard Tol, 2013. "The uncertainty about the social cost of carbon: A decomposition analysis using fund," Climatic Change, Springer, vol. 117(3), pages 515-530, April.
    12. Kenneth Gillingham & William Nordhaus & David Anthoff & Geoffrey Blanford & Valentina Bosetti & Peter Christensen & Haewon McJeon & John Reilly, 2018. "Modeling Uncertainty in Integrated Assessment of Climate Change: A Multimodel Comparison," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 5(4), pages 791-826.
    13. Chris Hope, 2013. "Critical issues for the calculation of the social cost of CO 2 : why the estimates from PAGE09 are higher than those from PAGE2002," Climatic Change, Springer, vol. 117(3), pages 531-543, April.
    14. William Nordhaus, 2014. "Estimates of the Social Cost of Carbon: Concepts and Results from the DICE-2013R Model and Alternative Approaches," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 1(1), pages 000.
    15. Wilkerson, Jordan T. & Leibowicz, Benjamin D. & Turner, Delavane D. & Weyant, John P., 2015. "Comparison of integrated assessment models: Carbon price impacts on U.S. energy," Energy Policy, Elsevier, vol. 76(C), pages 18-31.
    16. David Anthoff & Richard Tol, 2013. "Erratum to: The uncertainty about the social cost of carbon: A decomposition analysis using fund," Climatic Change, Springer, vol. 121(2), pages 413-413, November.
    17. Martin L. Weitzman, 2011. "Fat-Tailed Uncertainty in the Economics of Catastrophic Climate Change," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 5(2), pages 275-292, Summer.
    18. Igor Linkov & Dmitriy Burmistrov, 2003. "Model Uncertainty and Choices Made by Modelers: Lessons Learned from the International Atomic Energy Agency Model Intercomparisons," Risk Analysis, John Wiley & Sons, vol. 23(6), pages 1297-1308, December.
    19. 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.
    20. Ekholm, Tommi, 2018. "Climatic Cost-benefit Analysis Under Uncertainty and Learning on Climate Sensitivity and Damages," Ecological Economics, Elsevier, vol. 154(C), pages 99-106.
    21. Ackerman, Frank & Munitz, Charles, 2012. "Climate damages in the FUND model: A disaggregated analysis," Ecological Economics, Elsevier, vol. 77(C), pages 219-224.
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    Cited by:

    1. 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.
    2. Zachary A. Collier & James H. Lambert & Igor Linkov, 2020. "Concurrent threats and disasters: modeling and managing risk and resilience," Environment Systems and Decisions, Springer, vol. 40(3), pages 299-300, September.
    3. Richard S. J. Tol, 2021. "Estimates of the social cost of carbon have increased over time," Papers 2105.03656, arXiv.org, revised Aug 2022.

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