Risk and aversion in the integrated assessment of climate change
AbstractWe analyze the impact of damage uncertainty on optimal mitigation policies in the integrated assessment of climate change. Usually, these models analyzeuncertainty by averaging deterministic paths. In contrast, we build a consistentmodel deriving optimal policy rules under persistent uncertainty. For this purpose,we construct a close relative of the DICE model in a recursive dynamic programming framework. Our recursive approach allows us to disentangle effects of risk, risk aversion, and aversion to intertemporal substitution. We analyze different ways how damage uncertainty can affect the DICE equations. We compare the optimal policies to those resulting from the wide-spread ex-ante uncertainty approach averaging deterministic paths.
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Bibliographic InfoPaper provided by University of California at Berkeley, Department of Agricultural and Resource Economics and Policy in its series CUDARE Working Paper Series with number 1104R.
Length: 41 pages
Date of creation: 2010
Date of revision: Jul 2011
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Postal: University of California, Giannini Foundation of Agricultural Economics Library, 248 Giannini Hall #3310, Berkeley CA 94720-3310
Other versions of this item:
- Crost, Benjamin & Traeger, Christian P., 2011. "Risk and aversion in the integrated assessment of climate change," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt1562s275, Department of Agricultural & Resource Economics, UC Berkeley.
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