Publication
Modeling Uncertainty in Integrated Assessment of Climate Change: A Multimodel Comparison
Kenneth Gillingham and 7 other contributors
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OCT
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Citation
Gillingham, K. ., Nordhaus, W. ., Anthoff, D. ., Blanford, G. ., , Christensen, P. ., … Reilly, J. . (2018). Modeling Uncertainty in Integrated Assessment of Climate Change: A Multimodel Comparison. JOURNAL OF THE ASSOCIATION OF ENVIRONMENTAL AND RESOURCE ECONOMISTS, 5(4), 791-826. https://doi.org/10.1086/698910 (Original work published 2024)
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.