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Learning and climate change

Author

Listed:
  • 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
  • Warren Sanderson
  • Michael Schlesinger
  • Nicolas Treich
  • Alistair Ulph
  • Mort Webster
  • Chris Wilson

Abstract

Learning-i.e. the acquisition of new information that leads to changes in our assessment of uncertainty-plays a prominent role in the international climate policy debate. For example, the view that we should postpone actions until we know more continues to be influential. The latest work on learning and climate change includes new theoretical models, better informed simulations of how learning affects the optimal timing of emissions reductions, analyses of how new information could affect the prospects for reaching and maintaining political agreements and for adapting to climate change, and explorations of how learning could lead us astray rather than closer to the truth. Despite the diversity of this new work, a clear consensus on a central point is that the prospect of learning does not support the postponement of emissions reductions today.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:tcpoxx:v:6:y:2006:i:5:p:585-589
    DOI: 10.1080/14693062.2006.9685623
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    • 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.

    References listed on IDEAS

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    1. Keller, Klaus & Bolker, Benjamin M. & Bradford, D.F.David F., 2004. "Uncertain climate thresholds and optimal economic growth," Journal of Environmental Economics and Management, Elsevier, vol. 48(1), pages 723-741, July.
    2. William D. Nordhaus & David Popp, 1997. "What is the Value of Scientific Knowledge? An Application to Global Warming Using the PRICE Model," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 1-45.
    3. Minh Ha-Duong & Patrice Dumas, 2004. "An abrupt stochastic damage function to analyse climate policy benefits," Post-Print halshs-00002451, HAL.
    4. Michael Grubb, Carlo Carraro and John Schellnhuber, 2006. "Technological Change for Atmospheric Stabilization: Introductory Overview to the Innovation Modeling Comparison Project," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 1-16.
    5. Gritsevskyi, Andrii & Nakicenovi, Nebojsa, 2000. "Modeling uncertainty of induced technological change," Energy Policy, Elsevier, vol. 28(13), pages 907-921, November.
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    Cited by:

    1. van Wijnbergen, Sweder & Willems, Tim, 2015. "Optimal learning on climate change: Why climate skeptics should reduce emissions," Journal of Environmental Economics and Management, Elsevier, vol. 70(C), pages 17-33.
    2. Shurojit Chatterji & Sayantan Ghosal & Sean Walsh & John Whalley, 2014. "Unilateral Emissions Mitigation, Spillovers, And Global Learning," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 5(03), pages 1-16.
    3. Pizer, William A., 1997. "Optimal Choice of Policy Instrument and Stringency Under Uncertainty: The Case of Climate Change," Discussion Papers 10582, Resources for the Future.

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