67 Pages Posted: 25 Sep 2015
Date Written: September 23, 2015
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.
Keywords: Climate change, Modeling, Uncertainty, Statistics, Integrated assessment models
JEL Classification: Q4, Q5, C6, H4
Suggested Citation: Suggested Citation
Gillingham, Kenneth and Nordhaus, William D. and Anthoff, David and Blanford, Geoffrey J. and Bosetti, Valentina and Christensen, Peter and McJeon, Haewon and Reilly, John M. and Sztorc, Paul, Modeling Uncertainty in Climate Change: A Multi‐Model Comparison (September 23, 2015). Cowles Foundation Discussion Paper No. 2022. Available at SSRN: https://ssrn.com/abstract=2664693 or http://dx.doi.org/10.2139/ssrn.2664693