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dc.contributor.authorGillingham, K.
dc.contributor.authorNordhaus, W.
dc.contributor.authorAnthoff, D.
dc.contributor.authorBlanford, G.
dc.contributor.authorBosetti, V.
dc.contributor.authorChristensen, P.
dc.contributor.authorMcJeon, H.
dc.contributor.authorReilly, J.
dc.contributor.authorSztorc, P.
dc.date.accessioned2016-05-23T15:17:11Z
dc.date.available2016-05-23T15:17:11Z
dc.date.issued2015-12
dc.identifier.urihttp://hdl.handle.net/1721.1/102614
dc.description.abstractThe 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.en_US
dc.language.isoen_USen_US
dc.publisherMIT Joint Program on the Science and Policy of Global Changeen_US
dc.relation.ispartofseriesMIT Joint Program Report Series;290
dc.titleModeling Uncertainty in Climate Change: A Multi-Model Comparisonen_US
dc.typeTechnical Reporten_US
dc.typeWorking Paperen_US
dc.identifier.citationReport 290en_US


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