IDEAS home Printed from https://ideas.repec.org/a/spr/envsyd/v40y2020i3d10.1007_s10669-020-09783-y.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10669-020-09783-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10669-020-09783-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Delavane Diaz & Frances Moore, 2017. "Quantifying the economic risks of climate change," Nature Climate Change, Nature, vol. 7(11), pages 774-782, November.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. Crost, Benjamin & Traeger, Christian P., 2013. "Optimal climate policy: Uncertainty versus Monte Carlo," Economics Letters, Elsevier, vol. 120(3), pages 552-558.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. J. Eric Bickel, 2013. "Climate engineering and climate tipping-point scenarios," Environment Systems and Decisions, Springer, vol. 33(1), pages 152-167, March.
    19. 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.
    20. 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.
    21. Ackerman, Frank & Munitz, Charles, 2012. "Climate damages in the FUND model: A disaggregated analysis," Ecological Economics, Elsevier, vol. 77(C), pages 219-224.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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. Richard S. J. Tol, 2021. "Estimates of the social cost of carbon have increased over time," Papers 2105.03656, arXiv.org, revised Aug 2022.
    3. Richard S J Tol, 2018. "The Economic Impacts of Climate Change," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 12(1), pages 4-25.
    4. van den Bergh, J.C.J.M. & Botzen, W.J.W., 2015. "Monetary valuation of the social cost of CO2 emissions: A critical survey," Ecological Economics, Elsevier, vol. 114(C), pages 33-46.
    5. Rising, James A. & Taylor, Charlotte & Ives, Matthew C. & Ward, Robert E.t., 2022. "Challenges and innovations in the economic evaluation of the risks of climate change," LSE Research Online Documents on Economics 114941, London School of Economics and Political Science, LSE Library.
    6. Rising, James A. & Taylor, Charlotte & Ives, Matthew C. & Ward, Robert E.T., 2022. "Challenges and innovations in the economic evaluation of the risks of climate change," Ecological Economics, Elsevier, vol. 197(C).
    7. J. Farmer & Cameron Hepburn & Penny Mealy & Alexander Teytelboym, 2015. "A Third Wave in the Economics of Climate Change," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(2), pages 329-357, October.
    8. De Bruin, Kelly & Kiran Krishnamurthy, Chandra, 2021. "Optimal Climate Policy with Fat-tailed Uncertainty: What the Models Can Tell Us," Papers WP697, Economic and Social Research Institute (ESRI).
    9. Zhang, Hong & Jin, Gui & Zhang, Zhengyu, 2021. "Coupling system of carbon emission and social economy: A review," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    10. Shumilov, Andrei, 2021. "Анализ Неопределенности В Интегрированных Моделях Климата И Экономики: Обзор Литературы [Uncertainty analysis in integrated assessment models of the economics of climate change: a literature survey," MPRA Paper 110171, University Library of Munich, Germany.
    11. Peter Harrison Howard & Derek Sylvan, 2020. "Wisdom of the experts: Using survey responses to address positive and normative uncertainties in climate-economic models," Climatic Change, Springer, vol. 162(2), pages 213-232, September.
    12. Yongyang Cai, 2020. "The Role of Uncertainty in Controlling Climate Change," Papers 2003.01615, arXiv.org, revised Oct 2020.
    13. Weyant John, 2014. "Integrated assessment of climate change: state of the literature," Journal of Benefit-Cost Analysis, De Gruyter, vol. 5(3), pages 377-409, December.
    14. Lint Barrage, 2019. "The Nobel Memorial Prize for William D. Nordhaus," Scandinavian Journal of Economics, Wiley Blackwell, vol. 121(3), pages 884-924, July.
    15. Miftakhova, Alena, 2021. "Global sensitivity analysis for optimal climate policies: Finding what truly matters," Economic Modelling, Elsevier, vol. 105(C).
    16. 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.
    17. Havranek, Tomas & Irsova, Zuzana & Janda, Karel & Zilberman, David, 2015. "Selective reporting and the social cost of carbon," Energy Economics, Elsevier, vol. 51(C), pages 394-406.
    18. Jin, Gui & Shi, Xin & Zhang, Lei & Hu, Shougeng, 2020. "Measuring the SCCs of different Chinese regions under future scenarios," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    19. van den Bijgaart, Inge & Gerlagh, Reyer & Liski, Matti, 2016. "A simple formula for the social cost of carbon," Journal of Environmental Economics and Management, Elsevier, vol. 77(C), pages 75-94.
    20. Lamperti, F. & Dosi, G. & Napoletano, M. & Roventini, A. & Sapio, A., 2018. "Faraway, So Close: Coupled Climate and Economic Dynamics in an Agent-based Integrated Assessment Model," Ecological Economics, Elsevier, vol. 150(C), pages 315-339.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:envsyd:v:40:y:2020:i:3:d:10.1007_s10669-020-09783-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.