Conference Agenda
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Climate Policy Under Uncertainty Location: B127 Session Chair: Louis Daumas, EIEE | |
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Pricing an Unknown Climate 1: Oslo Metropolitan University, Norway; 2: University of Oslo, Norway Anthropogenic climate change is subject to a multitude of highly uncertain feedback processes, making the long-run impact of current emissions also highly uncertain. At present, we cannot reliably quantify the likelihood of differing global warming scenarios. Decision theory distinguishes between known, quantifiable risks and situations of ambiguity or deep uncertainty. A fully rational decision maker can respond differently to ambiguity and to risk, and real-world decision makers frequently do. We show how aversion to ambiguity affects optimal climate policy in an integrated assessment of climate change. We derive an analytic social cost of carbon formula for an ambiguity averse decision maker in a generic integrated assessment model. We also quantify the impact of recursive smooth ambiguity aversion for a stochastic dynamic programming implementation of DICE. Previous and paralleling approaches suggest substantial ambiguity premia on the optimal carbon tax. Our results show that the ambiguity premium is very small and optimal policy deriving from the standard Bayesian model is robust to ambiguity concerns under moderately large ambiguity aversion if climate policy is endogenous and policy maker's have rational foresight. | |