Scientific Ambiguity and Climate Policy

Economic evaluation of climate policy traditionally treats uncertainty by appealing to expected utility theory. Yet our knowledge of the impacts of climate policy may not be of sufficient quality to be described by unique probabilistic beliefs. In such circumstances, it has been argued that the axioms of expected utility theory may not be the correct standard of rationality. By contrast, several axiomatic frameworks have recently been proposed that account for ambiguous knowledge. In this paper, we apply static and dynamic versions of a smooth ambiguity model to climate mitigation policy. We obtain a general result on the comparative statics of optimal abatement and ambiguity aversion, and then extend our analysis to a more realistic, dynamic setting, where we introduce scientific ambiguity into the well-known DICE model of the climate-economy system. For policy-relevant exogenous mitigation policies, we show that the value of emissions abatement increases as ambiguity aversion increases, and that this ‘ambiguity premium’ can in some plausible cases be very An earlier version of this paper appeared as NBER Working Paper no. 16050. We thank Martin Weitzman, Christian Traeger, Larry Karp, Cameron Hepburn, seminar participants at Columbia, Harvard, Berkeley, Stanford, AERE, EAERE, and the 12th Occasional California Workshop on Environmental Economics, and two anonymous referees for helpful comments. We are grateful to Malte Meinshausen for supplying us with the empirical estimates of the climate sensitivity distributions. A. Millner (B) Department of Agricultural and Resource Economics, University of California, Berkeley, Berkeley, CA, USA e-mail: [email protected] A. Millner · S. Dietz Grantham Research Institute on Climate Change and the Environment, London School of Economics and Political Science, London, UK e-mail: [email protected] S. Dietz Department of Geography and Environment, London School of Economics and Political Science, London, UK G. Heal Columbia Business School, Columbia University, New York, NY, USA