Modeling uncertainty in climate change : a multi-model comparison

Kenneth Gillingham (Yale University, New Haven), William Nordhaus (Yale University, New Haven), David Anthoff (University of California, Berkeley), Valentina Bosetti (Bocconi University, Milan), Haewon McJeon (PNNL, College Park), Geoffrey Blanford (EPRI, USA), Peter Christensen (Aarhus University, Denmark), John Reilly (MIT, Cambridge, MA), Paul Sztorc (Yale University, New Haven)

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.

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Year of publication:	2016
Authors:	Gillingham, Kenneth ; Nordhaus, William D. ; Anthoff, David ; Bosetti, Valentina ; McJeon, Haewon C. ; Blanford, Geoffrey J. ; Christensen, Peter Ove ; Reilly, John M. ; Sztorc, Paul
Publisher:	Milano : Fondazione Eni Enrico Mattei
Subject:	Climate Change \| Integrated Assessment Models \| Klimawandel \| Climate change \| Modellierung \| Scientific modelling \| Risiko \| Risk \| Bevölkerung \| Population \| Produktivität \| Productivity \| Welt \| World