Verifying reference-dependent utility and loss aversion with Fukushima nuclear-disaster natural experiment

Keiko Iwasaki, Myoung-jae Lee, Yasuyuki Sawada

Research output: Contribution to journalArticle

Abstract

We verify prospect theory with natural experimental data by adopting regression kink design. Our data were collected in 2013 and 2014 from residents displaced by the Fukushima Nuclear Disaster in 2011. We examine how a sudden gain/loss affects stress/utility in four dimensions/resources: family size, health, house size, and income. We find that (i) there is a higher sensitivity to losses from a reference point than to gains (i.e., loss aversion) in health, and possibly in income as well, (ii) the reference point may change over time, and (iii) value function is not separable in the four dimensions/resources. These findings have a few implications. First, in view of the loss aversion, a sufficient—apparently more than enough—compensation should be provided to those who lost so that they can regain the original utility. Second, if the reference point is lowered, the victims must be over-compensated for their loss to recover the original utility. Third, separable value functions should be used with caution.

Original languageEnglish
Pages (from-to)78-89
Number of pages12
JournalJournal of the Japanese and International Economies
Volume52
DOIs
Publication statusPublished - 2019 Jun 1

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natural disaster
experiment
income
family size
health
resources
disaster
resident
regression
Natural experiment
Loss aversion
Reference point
Disaster
Value function
Health
Resources
Income
time
Prospect theory
Family size

ASJC Scopus subject areas

  • Finance
  • Economics and Econometrics
  • Political Science and International Relations

Cite this

Verifying reference-dependent utility and loss aversion with Fukushima nuclear-disaster natural experiment. / Iwasaki, Keiko; Lee, Myoung-jae; Sawada, Yasuyuki.

In: Journal of the Japanese and International Economies, Vol. 52, 01.06.2019, p. 78-89.

Research output: Contribution to journalArticle

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