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Modeling Uncertainty in Integrated Assessment of Climate Change: A Multimodel Comparison

Author

Listed:
  • Kenneth Gillingham
  • William Nordhaus
  • David Anthoff
  • Geoffrey Blanford
  • Valentina Bosetti
  • Peter Christensen
  • Haewon McJeon
  • John Reilly

Abstract

The economics of climate change involves a vast array of uncertainties, complicating our understanding of climate change. This study explores uncertainty in baseline trajectories using multiple integrated assessment models commonly used in climate policy development. The study examines model and parametric uncertainties for population, total factor productivity, and climate sensitivity. It estimates the probability distributions of key output variables, including CO2 concentrations, temperature, damages, and social cost of carbon (SCC). One key finding is that parametric uncertainty is more important than uncertainty in model structure. Our resulting distributions provide a useful input into climate policy discussions.

Suggested Citation

  • Kenneth Gillingham & William Nordhaus & David Anthoff & Geoffrey Blanford & Valentina Bosetti & Peter Christensen & Haewon McJeon & John Reilly, 2018. "Modeling Uncertainty in Integrated Assessment of Climate Change: A Multimodel Comparison," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 5(4), pages 791-826.
    • Handle: RePEc:ucp:jaerec:doi:10.1086/698910
    DOI: 10.1086/698910
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