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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.

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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2004 with number 140.

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Date of creation: 11 Aug 2004
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Handle: RePEc:sce:scecf4:140
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  1. 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.
  2. 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.
  3. McDonald, Alan & Schrattenholzer, Leo, 2001. "Learning rates for energy technologies," Energy Policy, Elsevier, vol. 29(4), pages 255-261, March.
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