Venue: Seminar room 2, Economics Research Annex(Kojima Hall), The University of Tokyo
Date：Friday, June 10, 10:00-11:30
Speaker: Professor François Lévêque（Cerna, Centre d’Economie Industrielle MINES ParisTech）
Open to all, upon registration
How do past observations inform us of the future risks of major nuclear accidents? How did the catastrophe at the Fukushima Dai-ichi nuclear power plant change the expected frequency for such events? There has been little consensus in answering these questions. While opponents of nuclear power claim that the probability of a serious accident is very high, the industry ensures that it is negligible. Furthermore, when facing such ambiguity, or multiple sources of information, how should policy-makers behave regarding these rare but catastrophic risks? The aim of the presentation is to present two methods developed in CERNA-Mines ParisTech that try to shed light on these questions. We will first present a Bayesian method which tries to determine the effect of the Fukushima Dai-ichi accident on the probability of witnessing future major nuclear accidents. Second, we will present a non-Bayesian method which tries to account for the ambiguity that characterizes the risks of nuclear power accidents.
Lévêque and Rangel (2014, Safety Science), and on Bizet and Lévêque (2016, Working Paper)
Science, Technology, and Innovation Governance(STIG) ,
The University of Tokyo