IDEAS home Printed from https://ideas.repec.org/p/nev/wpaper/wp200806.html
   My bibliography  Save this paper

Climate Response Uncertainty and the Unexpected Benefits of Greenhouse Gas Emissions Reductions

Author

Listed:
  • Adam Daigneault
  • Steve Newbold

Abstract

Some recent research suggests that uncertainty about the response of the climate system to atmospheric greenhouse gas (GHG) concentrations can have a disproportionately large influence on benefits estimates for climate change policies, potentially even dominating the effect of the discount rate. In this paper we conduct a series of numerical simulation experiments to investigate the quantitative significance of climate response uncertainty for economic assessments of climate change. First we characterize climate uncertainty by constructing two probability density functions—a Bayesian model-averaged and a Bayesian updated version—based on a combination of uncertainty ranges for climate sensitivity reported in the scientific literature. Next we estimate the willingness to pay of a representative agent for a range of emissions reduction policies using two simplified economic models. Our results illustrate the potential for large risk premiums in benefits estimates as suggested by the recent theoretical work on climate response uncertainty, and they show that the size and even the sign of the risk premium may depend crucially on how the posterior distribution describing the overall climate sensitivity uncertainty is constructed and on the specific shape of the damage function.- Submitted July, 2008; Resubmitted March, 2009

Suggested Citation

  • Adam Daigneault & Steve Newbold, 2009. "Climate Response Uncertainty and the Unexpected Benefits of Greenhouse Gas Emissions Reductions," NCEE Working Paper Series 200806, National Center for Environmental Economics, U.S. Environmental Protection Agency, revised Mar 2009.
  • Handle: RePEc:nev:wpaper:wp200806
    as

    Download full text from publisher

    File URL: https://www.epa.gov/environmental-economics/working-paper-climate-response-uncertainty-and-expected-benefits-greenhouse
    File Function: First version, 2009
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kolstad, Charles D., 1996. "Learning and Stock Effects in Environmental Regulation: The Case of Greenhouse Gas Emissions," Journal of Environmental Economics and Management, Elsevier, vol. 31(1), pages 1-18, July.
    2. Keller, Klaus & Bolker, Benjamin M. & Bradford, D.F.David F., 2004. "Uncertain climate thresholds and optimal economic growth," Journal of Environmental Economics and Management, Elsevier, vol. 48(1), pages 723-741, July.
    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. Robert S. Pindyck, 2013. "Climate Change Policy: What Do the Models Tell Us?," Journal of Economic Literature, American Economic Association, vol. 51(3), pages 860-872, September.
    2. Pindyck, Robert S., 2012. "Uncertain outcomes and climate change policy," Journal of Environmental Economics and Management, Elsevier, vol. 63(3), pages 289-303.
    3. 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.
    4. Robert S. Pindyck, 2011. "Fat Tails, Thin Tails, and Climate Change Policy," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 5(2), pages 258-274, Summer.
    5. Kelly, David L. & Tan, Zhuo, 2015. "Learning and climate feedbacks: Optimal climate insurance and fat tails," Journal of Environmental Economics and Management, Elsevier, vol. 72(C), pages 98-122.
    6. Iverson, Terrence, 2012. "Communicating Trade-offs amid Controversial Science: Decision Support for Climate Policy," Ecological Economics, Elsevier, vol. 77(C), pages 74-90.
    7. Joseph E. Aldy & Alan J. Krupnick & Richard G. Newell & Ian W. H. Parry & William A. Pizer, 2010. "Designing Climate Mitigation Policy," Journal of Economic Literature, American Economic Association, vol. 48(4), pages 903-934, December.
    8. Golub, Alexander & Lubowski, Ruben & Piris-Cabezas, Pedro, 2017. "Balancing Risks from Climate Policy Uncertainties: The Role of Options and Reduced Emissions from Deforestation and Forest Degradation," Ecological Economics, Elsevier, vol. 138(C), pages 90-98.
    9. 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, Kiel Institute for the World Economy (IfW), vol. 5, pages 1-24.
    10. van den Bremer, Ton & van der Ploeg, Frederick, 2018. "Pricing Carbon Under Economic and Climactic Risks: Leading-Order Results from Asymptotic Analysis," CEPR Discussion Papers 12642, C.E.P.R. Discussion Papers.
    11. 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.
    12. Williams, Galina & Rolfe, John, 2017. "Willingness to pay for emissions reduction: Application of choice modeling under uncertainty and different management options," Energy Economics, Elsevier, vol. 62(C), pages 302-311.
    13. Gerst, Michael D. & Howarth, Richard B. & Borsuk, Mark E., 2010. "Accounting for the risk of extreme outcomes in an integrated assessment of climate change," Energy Policy, Elsevier, vol. 38(8), pages 4540-4548, August.
    14. 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.

    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 & 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. Baker, Erin, 2005. "Uncertainty and learning in a strategic environment: global climate change," Resource and Energy Economics, Elsevier, vol. 27(1), pages 19-40, January.
    3. Lontzek, Thomas S. & Narita, Daiju, 2009. "The effect of uncertainty on decision making about climate change mitigation: a numerical approach of stochastic control," Kiel Working Papers 1539, Kiel Institute for the World Economy (IfW).
    4. Bosetti, Valentina & Carraro, Carlo & Sgobbi, Alessandra & Tavoni, Massimo, 2008. "Delayed Action and Uncertain Targets. How Much Will Climate Policy Cost?," CEPR Discussion Papers 6973, C.E.P.R. Discussion Papers.
    5. Vogt-Schilb, Adrien & Meunier, Guy & Hallegatte, Stéphane, 2018. "When starting with the most expensive option makes sense: Optimal timing, cost and sectoral allocation of abatement investment," Journal of Environmental Economics and Management, Elsevier, vol. 88(C), pages 210-233.
    6. Baker, Erin & Shittu, Ekundayo, 2008. "Uncertainty and endogenous technical change in climate policy models," Energy Economics, Elsevier, vol. 30(6), pages 2817-2828, November.
    7. van Wijnbergen, Sweder & Willems, Tim, 2015. "Optimal learning on climate change: Why climate skeptics should reduce emissions," Journal of Environmental Economics and Management, Elsevier, vol. 70(C), pages 17-33.
    8. 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.
    9. 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.
    10. Rolf Groeneveld & Michael Springborn & Christopher Costello, 2014. "Repeated Experimentation to Learn About a Flow-Pollutant Threshold," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 58(4), pages 627-647, August.
    11. 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.
    12. Baker, Erin & Adu-Bonnah, Kwame, 2008. "Investment in risky R&D programs in the face of climate uncertainty," Energy Economics, Elsevier, vol. 30(2), pages 465-486, March.
    13. Baker, Erin & Shittu, Ekundayo, 2006. "Profit-maximizing R&D in response to a random carbon tax," Resource and Energy Economics, Elsevier, vol. 28(2), pages 160-180, May.
    14. 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.
    15. Bommier, Antoine & Lanz, Bruno & Zuber, Stéphane, 2015. "Models-as-usual for unusual risks? On the value of catastrophic climate change," Journal of Environmental Economics and Management, Elsevier, vol. 74(C), pages 1-22.
    16. Proost, Stef & Van Dender, Kurt, 2012. "Energy and environment challenges in the transport sector," Economics of Transportation, Elsevier, vol. 1(1), pages 77-87.
    17. Joseph E. Aldy & William A. Pizer, 2009. "Issues in Designing U.S. Climate Change Policy," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 179-210.
    18. Narain, Urvashi & Fisher, Anthony, 1998. "Irreversibility, Uncertainty, and Catastrophic Global Warming," CUDARE Working Papers 198662, University of California, Berkeley, Department of Agricultural and Resource Economics.
    19. Romera, Rosario & Casas, Omar J., 2011. "The international stock pollutant control: a stochastic formulation with transfers," DES - Working Papers. Statistics and Econometrics. WS ws112217, Universidad Carlos III de Madrid. Departamento de Estadística.
    20. Baker, Erin & Bosetti, Valentina & Salo, Ahti, 2016. "Finding Common Ground when Experts Disagree: Belief Dominance over Portfolios of Alternatives," MITP: Mitigation, Innovation and Transformation Pathways 243147, Fondazione Eni Enrico Mattei (FEEM).

    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:nev:wpaper:wp200806. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/nepgvus.html .

    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: Cynthia Morgan (email available below). General contact details of provider: https://edirc.repec.org/data/nepgvus.html .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.