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Modeling Damages in Climate Policy Models: Temperature-Based or Carbon-Based?

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  • Charles F. Mason
  • Neil Wilmot

Abstract

Economists have analyzed potential for damages from climate change from theoretical analyses and with Integrated Assessment Models (IAMs). Analytical models typically write damages as a function of the carbon stock, while IAMs typically view damages as based on temperatures. In this paper, we evaluate the implications for adapting analytic models to include two state variables—temperature and carbon stocks. We first provide an analytical comparison of a model where damages are based on carbon stocks against a model where damages are based on temperatures. When damages are based on carbon stocks, the time path of optimal emissions is described by a first-order differential equation; when damages are based on temperatures, the time path of optimal emissions is described by a second-order differential equation. We then proceed to an empirical analysis of the link between temperatures and carbon stocks. Our empirical analysis strongly supports a relation between levels of carbon stocks and changes in temperatures, and indicates the virtual absence of a linkage between levels of carbon and levels of temperature. As such, it is broadly supportive of a more elaborate modeling structure, under which two state variables are included in the analytical framework.

Suggested Citation

  • Charles F. Mason & Neil Wilmot, 2015. "Modeling Damages in Climate Policy Models: Temperature-Based or Carbon-Based?," CESifo Working Paper Series 5287, CESifo.
  • Handle: RePEc:ces:ceswps:_5287
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    1. repec:hrv:faseco:33373343 is not listed on IDEAS
    2. Grimaud, André & Rouge, Luc, 2014. "Carbon sequestration, economic policies and growth," Resource and Energy Economics, Elsevier, vol. 36(2), pages 307-331.
    3. Derek Lemoine & Christian Traeger, 2014. "Watch Your Step: Optimal Policy in a Tipping Climate," American Economic Journal: Economic Policy, American Economic Association, vol. 6(1), pages 137-166, February.
    4. Karp, Larry & Zhang, Jiangfeng, 2006. "Regulation with anticipated learning about environmental damages," Journal of Environmental Economics and Management, Elsevier, vol. 51(3), pages 259-279, May.
    5. Ulph, Alistair & Ulph, David, 1997. "Global Warming, Irreversibility and Learning," Economic Journal, Royal Economic Society, vol. 107(442), pages 636-650, May.
    6. Martin L. Weitzman, 2009. "On Modeling and Interpreting the Economics of Catastrophic Climate Change," The Review of Economics and Statistics, MIT Press, vol. 91(1), pages 1-19, February.
    7. Olli Tahvonen, 1997. "Fossil Fuels, Stock Externalities, and Backstop Technology," Canadian Journal of Economics, Canadian Economics Association, vol. 30(4), pages 855-874, November.
    8. Forster, Bruce A., 1980. "Optimal energy use in a polluted environment," Journal of Environmental Economics and Management, Elsevier, vol. 7(4), pages 321-333, December.
    9. Crost, Benjamin & Traeger, Christian P., 2013. "Optimal climate policy: Uncertainty versus Monte Carlo," Economics Letters, Elsevier, vol. 120(3), pages 552-558.
    10. Chakravorty, Ujjayant & Magne, Bertrand & Moreaux, Michel, 2006. "A Hotelling model with a ceiling on the stock of pollution," Journal of Economic Dynamics and Control, Elsevier, vol. 30(12), pages 2875-2904, December.
    11. Jouvet, Pierre-Andre & Michel, Philippe & Rotillon, Gilles, 2005. "Optimal growth with pollution: how to use pollution permits?," Journal of Economic Dynamics and Control, Elsevier, vol. 29(9), pages 1597-1609, September.
    12. Pizer, William A., 1999. "The optimal choice of climate change policy in the presence of uncertainty," Resource and Energy Economics, Elsevier, vol. 21(3-4), pages 255-287, August.
    13. Kelly, David L. & Kolstad, Charles D., 1999. "Bayesian learning, growth, and pollution," Journal of Economic Dynamics and Control, Elsevier, vol. 23(4), pages 491-518, February.
    14. Dutta, Prajit K. & Radner, Roy, 2009. "A strategic analysis of global warming: Theory and some numbers," Journal of Economic Behavior & Organization, Elsevier, vol. 71(2), pages 187-209, August.
    15. Leach, Andrew J., 2007. "The climate change learning curve," Journal of Economic Dynamics and Control, Elsevier, vol. 31(5), pages 1728-1752, May.
    16. Frederick Ploeg & Cees Withagen, 2014. "Growth, Renewables, And The Optimal Carbon Tax," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 55, pages 283-311, February.
    17. Mikhail Golosov & John Hassler & Per Krusell & Aleh Tsyvinski, 2014. "Optimal Taxes on Fossil Fuel in General Equilibrium," Econometrica, Econometric Society, vol. 82(1), pages 41-88, January.
    18. Bård Harstad, 2012. "Buy Coal! A Case for Supply-Side Environmental Policy," Journal of Political Economy, University of Chicago Press, vol. 120(1), pages 77-115.
    19. Philippe Michel & Gilles Rotillon, 1995. "Disutility of pollution and endogenous growth," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 6(3), pages 279-300, October.
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    Cited by:

    1. Jean-Pierre Amigues & Michel Moreaux, 2018. "Converting Primary Resources into Useful Energy: The Pollution Ceiling Efficiency Paradox," Annals of Economics and Statistics, GENES, issue 132, pages 5-32.
    2. Amigues, Jean-Pierre & Moreaux, Michel, 2019. "Energy Conversion Rate Improvements, Pollution Abatement Efforts and Energy Mix: The Transition toward the Green Economy under a Pollution Stock Constraint," TSE Working Papers 19-994, Toulouse School of Economics (TSE).
    3. Amigues, Jean-Pierre & Moreaux, Michel, 2016. "Pollution Abatement v.s. Energy Efficiency Improvements," TSE Working Papers 16-626, Toulouse School of Economics (TSE).
    4. Jean-Pierre Amigues & Michel Moreaux, 2016. "From Primary Resources to Useful Energy: The Pollution Ceiling Efficiency Paradox," Working Papers 2016.10, FAERE - French Association of Environmental and Resource Economists.

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    Keywords

    climate change; damage function;

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