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The perception of climate sensitivity: Revealing priors from posteriors

Author

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  • Masako Ikefuji

    (University of Tsukuba)

  • Jan R. Magnus

    (Vrije Universiteit Amsterdam)

Abstract

A Bayesian typically uses data and a prior to produce a posterior. In practice, the data and the posterior are often observed but not the prior. We shall follow the opposite route, using data and the posterior information to reveal the prior. We then apply this theory to (equilibrium) climate sensitivity as reported by the Intergovernmental Panel on Climate Change in an attempt to get some insight into their prior beliefs. It appears that the IPCC scientists have agreed a priori on a value for the climate equilibrium between 3.0-4.0 degrees Celsius, while judging the occurrence of a real disaster much more likely than the previous report predicts.

Suggested Citation

  • Masako Ikefuji & Jan R. Magnus, 2020. "The perception of climate sensitivity: Revealing priors from posteriors," Tinbergen Institute Discussion Papers 20-046/III, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20200046
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    References listed on IDEAS

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    1. 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.
    2. Magne Aldrin & Marit Holden & Peter Guttorp & Ragnhild Bieltvedt Skeie & Gunnar Myhre & Terje Koren Berntsen, 2012. "Bayesian estimation of climate sensitivity based on a simple climate model fitted to observations of hemispheric temperatures and global ocean heat content," Environmetrics, John Wiley & Sons, Ltd., vol. 23(3), pages 253-271, May.
    3. Antony Millner & Simon Dietz & Geoffrey Heal, 2013. "Scientific Ambiguity and Climate Policy," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 55(1), pages 21-46, May.
    4. Roger M Cooke & Bruce Wielicki, 2018. "Probabilistic reasoning about measurements of equilibrium climate sensitivity: combining disparate lines of evidence," Climatic Change, Springer, vol. 151(3), pages 541-554, December.
    5. William Brock & Anastasios Xepapadeas, 2019. "Regional Climate Policy under Deep Uncertainty: Robust Control, Hot Spots and Learning," DEOS Working Papers 1903, Athens University of Economics and Business.
    6. William Brock & Anastasios Xepapadeas, 2019. "Regional Climate Policy under Deep Uncertainty," DEOS Working Papers 1901, Athens University of Economics and Business.
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    More about this item

    Keywords

    Revealed prior; climate sensitivity; IPCC;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: 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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