Modeling Uncertainty in Climate Change: A Multi-Model Comparison

Kenneth Gillingham, William Nordhaus, David Anthoff (), Geoffrey Blanford, Valentina Bosetti, Peter Christensen, Haewon McJeon, John Reilly and Paul Sztorc

No 21637, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: The economics of climate change involves a vast array of uncertainties, complicating both the analysis and development of climate policy. This study presents the results of the first comprehensive study of uncertainty in climate change using multiple integrated assessment models. The study looks at model and parametric uncertainties for population, total factor productivity, and climate sensitivity. It estimates the pdfs of key output variables, including CO2 concentrations, temperature, damages, and the social cost of carbon (SCC). One key finding is that parametric uncertainty is more important than uncertainty in model structure. Our resulting pdfs also provide insights on tail events.

JEL-codes: O44 Q48 Q54 (search for similar items in EconPapers)
Date: 2015-10
New Economics Papers: this item is included in nep-ene and nep-env
Note: EEE
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Citations: View citations in EconPapers (28)

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Related works:
Working Paper: Modeling Uncertainty in Climate Change: A Multi-Model Comparison (2016)
Working Paper: Modeling Uncertainty in Climate Change: A Multi-Model Comparison (2016)
Working Paper: Modeling Uncertainty in Climate Change: A Multi-Model Comparison (2016)
Working Paper: Modeling Uncertainty in Climate Change: A Multi-Model Comparison (2015)
Working Paper: Modeling Uncertainty in Climate Change: A Multi-Model Comparison (2015)
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