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The value of information for integrated assessment models of climate change

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  • Newbold, Stephen C.
  • Marten, Alex L.

Abstract

We estimate the value of information (VOI) for three key parameters of climate integrated assessment models (IAMs): marginal damages at low temperature anomalies, marginal damages at high temperature anomalies, and equilibrium climate sensitivity. Most empirical studies of climate damages have examined temperature anomalies up to 3°C, while some recent theoretical studies emphasize the risks of “climate catastrophes,” which depend on climate sensitivity and on marginal damages at higher temperature anomalies. We use a new IAM to estimate the VOI for each parameter over a range of assumed levels of study precision based on prior probability distributions calibrated using results from previous studies. We measure the VOI as the maximum fixed fraction of consumption that a social planner would be willing to pay to conduct a new study before setting a carbon tax. Our central results suggest that the VOI is greatest for marginal damages at high temperature anomalies.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:jeeman:v:68:y:2014:i:1:p:111-123
    DOI: 10.1016/j.jeem.2014.01.002
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    Cited by:

    1. Gerard Meijden & Frederick Ploeg & Cees Withagen, 2017. "Frontiers of Climate Change Economics," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 68(1), pages 1-14, September.
    2. 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.
    3. Ahlvik, Lassi & Hyytiäinen, Kari, 2015. "Value of adaptation in water protection — Economic impacts of uncertain climate change in the Baltic Sea," Ecological Economics, Elsevier, vol. 116(C), pages 231-240.
    4. Lindley, Sarah & Albeke, Shannon & Viers, Joshua & Parsons, George & Johnston, Robert & Newbold, Stephen C., 2022. "Valuing Satellite Data for Harmful Algal Bloom Early Warning Systems," RFF Working Paper Series 22-23, Resources for the Future.
    5. Vinent, Orencio Duran & Johnston, Robert J. & Kirwan, Matthew L. & Leroux, Anke D. & Martin, Vance L., 2019. "Coastal dynamics and adaptation to uncertain sea level rise: Optimal portfolios for salt marsh migration," Journal of Environmental Economics and Management, Elsevier, vol. 98(C).
    6. Newbold, Stephen C. & Johnston, Robert J., 2020. "Valuing non-market valuation studies using meta-analysis: A demonstration using estimates of willingness-to-pay for water quality improvements," Journal of Environmental Economics and Management, Elsevier, vol. 104(C).
    7. Richard S. J. Tol, 2021. "Estimates of the social cost of carbon have increased over time," Papers 2105.03656, arXiv.org, revised Aug 2022.
    8. Peter H. Howard & Thomas Sterner, 2017. "Few and Not So Far Between: A Meta-analysis of Climate Damage Estimates," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 68(1), pages 197-225, September.
    9. 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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    More about this item

    Keywords

    Climate change; Integrated assessment model; Value of information; Uncertainty; Climate sensitivity;
    All these keywords.

    JEL classification:

    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects

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