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An abrupt stochastic damage function to analyse climate policy benefits

Author

Listed:
  • Minh Ha-Duong

    (CIRED - centre international de recherche sur l'environnement et le développement - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - EHESS - École des hautes études en sciences sociales - AgroParisTech - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique)

  • Patrice Dumas

    (CIRED - centre international de recherche sur l'environnement et le développement - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - EHESS - École des hautes études en sciences sociales - AgroParisTech - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique)

Abstract

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-benefits 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.

Suggested Citation

  • Minh Ha-Duong & Patrice Dumas, 2004. "An abrupt stochastic damage function to analyse climate policy benefits," Post-Print halshs-00002451, HAL.
    • Handle: RePEc:hal:journl:halshs-00002451
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00002451
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    Citations

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    Cited by:

    1. Vincent Gitz & Jean-Charles Hourcade & Philippe Ciais, 2006. "The Timing of Biological Carbon Sequestration and Carbon Abatement in the Energy Sector Under Optimal Strategies Against Climate Risks," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 113-134.
    2. Vincent Gitz & Jean Charles Hourcade & Philippe Ciais, 2006. "The timing of biological carbon sequestration and carbon abatement in the energy sector under optimal strategies against climate risks," Working Papers halshs-00009338, HAL.
    3. Brian C. O'Neill & Paul Crutzen & Arnulf Gr�bler & Minh Ha Duong & Klaus Keller & Charles Kolstad & Jonathan Koomey & Andreas Lange & Michael Obersteiner & Michael Oppenheimer & William Pepper & Warre, 2006. "Learning and climate change," Climate Policy, Taylor & Francis Journals, vol. 6(5), pages 585-589, September.
      • Brian C. O'Neill & Paul Crutzen & Arnulf Grübler & Minh Ha-Duong & Klaus Keller & Charles Kolstad & Jonathan Koomey & Andreas Lange & Michael Obersteiner & Michael Oppenheimer & William Pepper & Warre, 2006. "Learning and climate change," Post-Print halshs-00134718, HAL.
    4. Valentina Bosetti & Laurent Gilotte, 2005. "Carbon Capture and Sequestration: How Much Does this Uncertain Option Affect Near-Term Policy Choices?," Working Papers 2005.86, Fondazione Eni Enrico Mattei.
    5. Agustin Molina Morales & Miguel Guerrero, 2006. "The European union as first mover in the market for greenhouse gas emissions permits," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 49(4), pages 533-553.
    6. Muller-Furstenberger, Georg & Wagner, Martin, 2007. "Exploring the environmental Kuznets hypothesis: Theoretical and econometric problems," Ecological Economics, Elsevier, vol. 62(3-4), pages 648-660, May.
    7. Vincent Gitz & Jean Charles Hourcade & Philippe Ciais, 2005. "The timing of biological carbon sequestration and carbon abatement in the energy sector under optimal strategies against climate risks," Working Papers hal-00866426, HAL.
    8. Andrei Bazhanov, 2012. "A Closed-Form Solution to Stollery’s Problem with Damage in Utility," Computational Economics, Springer;Society for Computational Economics, vol. 39(4), pages 365-386, April.

    More about this item

    Keywords

    Changement climatique; modélisation intégrée;

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