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Bootstraps for Meta-Analysis with an Application to the Impact of Climate Change

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  • Richard Tol
Abstract
Bootstrap and smoothed bootstrap methods are used to estimate the uncertainty about the total impact of climate change, and to assess the performance of commonly used impact functions. Kernel regression is extended to include restrictions on the functional form. Impact functions do not describe the primary estimates of the economic impacts very well, and monotonic functions do particularly badly. The impacts of climate change do not significantly deviate from zero until 2.5–3.5 $$^{\circ }\hbox {C}$$ ∘ C warming. The uncertainty is large, and so is the risk premium. The ambiguity premium is small, however. The certainty equivalent impact is a negative 1.5 % of income for $$2.5\,^{\circ }\hbox {C}$$ 2.5 ∘ C , rising to 15 % (50 %) for $$5.0\,^{\circ }\hbox {C}$$ 5.0 ∘ C for a rate of risk aversion of 1 (2). Copyright Springer Science+Business Media New York 2015

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  • Richard Tol, 2015. "Bootstraps for Meta-Analysis with an Application to the Impact of Climate Change," Computational Economics, Springer;Society for Computational Economics, vol. 46(2), pages 287-303, August.
  • Handle: RePEc:kap:compec:v:46:y:2015:i:2:p:287-303
    DOI: 10.1007/s10614-014-9448-5
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    Cited by:

    1. Richard S.J. Tol, 2018. "The impact of climate change and the social cost of carbon," Working Paper Series 1318, Department of Economics, University of Sussex Business School.
    2. Howard, Peter & Sterner, Thomas, 2014. "Loaded DICE: Refining the Meta-analysis Approach to Calibrating Climate Damage Functions," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169952, Agricultural and Applied Economics Association.
    3. Tsigaris, Panagiotis & Wood, Joel, 2016. "A simple climate-Solow model for introducing the economics of climate change to undergraduate students," International Review of Economics Education, Elsevier, vol. 23(C), pages 65-81.
    4. Howard, Peter H. & Sylvan, Derek, 2015. "The Economic Climate: Establishing Consensus on the Economics of Climate Change," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205761, Agricultural and Applied Economics Association.
    5. Richard Tol, 2014. "Objective versus subjective assessments: The IPCC treatment of the total economic impact of climate change," Working Paper Series 6914, Department of Economics, University of Sussex Business School.
    6. Howard, Peter H. & Derek, Sylvan, 2016. "The Wisdom of the Economic Crowd: Calibrating Integrated Assessment Models Using Consensus," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235639, Agricultural and Applied Economics Association.
    7. Tol, Richard S.J., 2024. "A meta-analysis of the total economic impact of climate change," Energy Policy, Elsevier, vol. 185(C).
    8. Richard S. J. Tol, 2016. "The Impacts Of Climate Change According To The Ipcc," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 7(01), pages 1-20, February.
    9. Tsigaris, Panagiotis & Wood, Joel, 2019. "The potential impacts of climate change on capital in the 21st century," Ecological Economics, Elsevier, vol. 162(C), pages 74-86.

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    More about this item

    Keywords

    Impacts of climate change; Kernel regression; Bootstrap; Risk aversion; Ambiguity aversion; C14; Q54;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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