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Global CO2 Emission Mitigation Through the Looking Glass of ROA

  • Benoit Morel
Chapter
Part of the Springer Climate book series (SPCL)

Abstract

Except for a few loonies, most agree that there is an imperative not to let the atmospheric load of CO2 grow indefinitely. “Doing nothing implies that risks are negligible. That position implies an absurd degree of certainty” [Wolf, Financial Times (27 Oct 2015)]. As some like to say, there is no planet B. The economics of climate change is far, far behind its science. Given the important role of uncertainty in climate change policy and the debilitating limitations of alternatives such as NPV or the “neoclassical” approach, i.e., the “integrated assessment models,” when it comes to uncertainty, the detour of ROA is unavoidable. The interface between ROA and climate change turns out to be rather explosive and reveals how deep the need for a response to climate change goes.

References

  1. Baker, M.B., Roe, G.H.: Science. 318, 629–632 (2007)CrossRefGoogle Scholar
  2. Geman, D., Geman, H., Taleb, N.N.: Tail risk constraints and maximum entropy, entropy. 17, 3724–3737 (2015)CrossRefGoogle Scholar
  3. Hansen, J., Kharecha, P., Sato, M., Masson-Delmotte, V., Ackerman, F., et al.: Assessing “dangerous climate change”: required reduction of carbon emissions to protect young people, future generations and nature. PLoS One. 8(12), e81648 (2013).  https://doi.org/10.1371/journal.pone.0081648CrossRefGoogle Scholar
  4. Held, I.M.: The Vertical Scale of an unstable baroclinic wave and its importance for Eddy heat flux parameterization. J. Atmos. Sci. 35, 572 (1978). http://journals.ametsoc.org/doi/pdf/10.1175/1520-0469%281978%29035%3C0572%3ATVSOAU%3E2.0.CO%3B2CrossRefGoogle Scholar
  5. IMF: Climate, environment, and the IMF. http://www.imf.org/external/np/exr/facts/enviro.htm (2015)
  6. Jaynes, E.T.: How should we use entropy in economics? Saint John’s College, Cambridge (1991)Google Scholar
  7. Kullback, S., Leibler, R.A.: On information and sufficiency. Ann. Math. Stat. 22(1), 79–86 (1951)CrossRefGoogle Scholar
  8. McNeil, A.J., Frey, R., Embrecht, P.: Quantitative Risk management, concepts, techniques and tools. Princeton University Press, Princeton (2005)Google Scholar
  9. Meinshausen, M., Meinshausen, N., Hare, W., Raper, S.C.B., Frieler, K., Knutti, R., Frame, D.J., Allen, M.R.: Nature. 458, 1158 (2009)CrossRefGoogle Scholar
  10. Nordhaus, W.: The Dynamic Integrated Climate Economic model (DICE). http://www.econ.yale.edu/~nordhaus/homepage/documents/DICE_Manual_100413r1.pdf
  11. Phillips, N.A.: Tellus. 6, 273–286 (1954)CrossRefGoogle Scholar
  12. Stone, P.H.: Baroclinic adjustment. J. Atmos. Sci. 35, 561 (1978). http://eaps4.mit.edu/research/papers/Stone_1978.pdfCrossRefGoogle Scholar
  13. Villani, C.: Optimal transport, old and new. Springer, Berlin (2008). http://cedricvillani.org/wp-content/uploads/2012/08/preprint-1.pdfGoogle Scholar
  14. Weitzman, M.: On modeling and interpreting the economics of catastrophic climate change. 680 Harvard Preprint. http://www.economics.harvard.edu/faculty/weitzman/papers_weitzman (2008)
  15. Weitzman, M.: Rev. Environ. Econ. Policy. 5(2), 275–292 (2011)CrossRefGoogle Scholar
  16. Weitzman, M.: Precautionary tale about uncertain fat tail flattening, NBER, Working Paper 18144 683 (2012)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Benoit Morel
    • 1
  1. 1.Carnegie Mellon UniversityPittsburghUSA

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