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）
Language：English
Open to all, upon registration
Abstract:
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.
References:
Lévêque and Rangel (2014, Safety Science), and on Bizet and Lévêque (2016, Working Paper)
Hosted by:
Science, Technology, and Innovation Governance(STIG) ,
The University of Tokyo
STIG@pp.u-tokyo.ac.jp
06.03.2016