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Optimal Technological Portfolios for Climate-Change Policy under Uncertainty: A Computable General Equilibrium Approach


  • David F. Bradford
  • Seung-Rae Kim
  • Klaus Keller


When exploring solutions to long-term environmental problems such as climate change, it is crucial to understand how the rates and directions of technological change may interact with environmental policies in the presence of uncertainty. This paper analyzes optimal technological portfolios for global carbon emissions reductions in an integrated assessment model of the coupled social-natural system. The model used here is a probabilistic, two-technology extension of Nordhaus" earlier model (Nordhaus and Boyer, 2000) by incorporating endogenous technological choice between conventional and carbon-free technologies. Taking into account the possible competitions among the technological options, we address the issues of optimal timing, costs and burden-sharing of optimal carbon mitigation strategies in the inherently uncertain world. We perform various analyses related to the major uncertainties about natural, socioeconomic and technological parameters, and investigate the effects of uncertainties resolution, risks and alternative political preferences. The results show that analyses ignoring uncertainty could lead to inefficient and biased technology-policy recommendations for the future.

Suggested Citation

  • David F. Bradford & Seung-Rae Kim & Klaus Keller, 2004. "Optimal Technological Portfolios for Climate-Change Policy under Uncertainty: A Computable General Equilibrium Approach," Computing in Economics and Finance 2004 140, Society for Computational Economics.
  • Handle: RePEc:sce:scecf4:140

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    References listed on IDEAS

    1. McDonald, Alan & Schrattenholzer, Leo, 2001. "Learning rates for energy technologies," Energy Policy, Elsevier, vol. 29(4), pages 255-261, March.
    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. 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.
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    Cited by:

    1. Seung-Rae Kim, 2005. "Uncertainty, Learning, and Optimal Technological Portfolios: A Dynamic General Equilibrium Approach to Climate Change," Computing in Economics and Finance 2005 54, Society for Computational Economics.

    More about this item


    Integrated assessment modeling; Global Warming; Uncertainty; Endogenous technological portfolios;

    JEL classification:

    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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