An Abrupt Stochastic Damage Function to Analyze Climate Policy Benefits

  • Patrice Dumas
  • Minh Ha-Duong
Part of the Advances in Global Change Research book series (AGLO, volume 22)


This paper studies uncertainty about the non-linearity of climate change impact. The DIAM 2.3 model is used to compute the sensitivity of optimal CO2 emissions paths with respect to damage function parameters. This builds upon results of the EMF–14 uncertainty subgroup study by explicitly allowing for the possibility of threshold effects and hockey stick damage functions. It also extends to the cost-benefit framework previous studies about inertia of energy systems. Results show that the existence of a threshold in the damage function is critical to precautionary action. Optimal path are much less sensitive to uncertainty on the scale of the damages than on the threshold values.


Emission Reduction Damage Function Abatement Level Optimal Emission Impact Function 
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  1. Broecker, Wallace (1997). Thermohaline circulation, the Achille’s heel of our climate system: Will man-made CO2 upset the current balance. Science, 278(5343):1582–1588.CrossRefGoogle Scholar
  2. Dalton, Michael G. (1997). The welfare bias fom omitting climatic variability in economic studies of global warming. Journal of Environmental Economicsand Management, 33:221–239.CrossRefGoogle Scholar
  3. Dixit, Avinash K. and Pindyck, Robert S. (1994). The timing of environmental policy, chapter 12.3, pages 412–418. Princeton University Press, Princeton, New Jersey.Google Scholar
  4. Gjerde, Jon, Grepperud, Sverre, and Kverndokk, Snorre (1999). Optimal climate policy under the possibility of a catastrophe. Resource and Energy Economics, 21:289 317.Google Scholar
  5. Ha-Duong, Minh (1998). Comment tenir compte de l’irréversibilité dans l’véaluation intégrée du changement climatique ? Thèse de doctorat, École des hautes Études en Sciences Sociales, Paris.Google Scholar
  6. Ha-Duong, Minh, Grubb, Michael J., and Hourcade, Jean-Charles (1997). Influence of socioeconomic inertia and uncertainty on optimal CO2-emission abatement. Nature, 390:270 274.Google Scholar
  7. IPCC (2001). Climate Change 2001: Synthesis Report. A contribution of Working Groups I, II, and III to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press.Google Scholar
  8. Keller, Klaus, Bolker, Benjamin M., and Bradford, David F. (2004). Uncertain climate tresholds and economic optimal growth. Journal of Environmental Economics and Management, 48(1):723–741.CrossRefGoogle Scholar
  9. Manne, Alan S. (1996). Hedging strategies for global carbon dioxide abatement. A summary of poll results. Working paper of the EMF 14 Subgroup Analysis for Decisions under Uncertainty.Google Scholar
  10. Narain, Urvashi and Fisher, Anthony C. (1998). Irreversibility and catastrophic global warming. In First World Congress of Environmental and Resource Economists, Venice, Italy. EAERE, AERE. Deposited electronically at the GNEE archive.Google Scholar
  11. Nordhaus, William D. (1994). Managing the Global Commons. MIT Press.Google Scholar
  12. Peck, Stephen C. and Teisberg, Thomas J. (1993). The importance of nonlin-earities in global warming damage costs. In Darmstadter, Joel and Toman, Michael A., editors, Assessing Surprises and Nonlinearities in Greenhouse Warming. Ressources For the Future.Google Scholar
  13. Yohe, Gary and Wallace, Rodney (1996). Near term mitigation policy for global change under uncertainty: minimizing expected cost of meeting unknown concentration tresholds. Environmental Modeling and Assessment, 1:47–57.CrossRefGoogle Scholar

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© Springer 2005

Authors and Affiliations

  • Patrice Dumas
  • Minh Ha-Duong

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