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Journal of Risk and Uncertainty

, Volume 59, Issue 1, pp 85–124 | Cite as

Learning from extreme catastrophes

  • Shinichi KamiyaEmail author
  • Noriyoshi Yanase
Article

Abstract

This article studies the effects of direct and indirect loss experience of extreme catastrophes on expectations concerning the likelihood of future events by investigating the earthquake insurance take-up of Japanese households after the two costliest disasters in history. Direct loss experiences caused the strongest reactions to extreme catastrophes, whereas risk belief updates were a nationwide phenomenon. Sharing personalized information contributed to strong and persistent indirect experience effects. Investigating the effect of past quake experience on reaction to a new major quake, we find that both availability bias and representativeness help explain the effect of past loss experiences. Furthermore, the gambler’s fallacy, as proposed by Tversky and Kahneman (Psychological Bulletin 76(2), 105–110, 1971), appears to play an important role after an indirect experience with a 1000-year earthquake.

Keywords

Catastrophe Earthquake Insurance Risk belief Availability bias Representativeness Peer effects 

JEL classifications

D12 D81 D83 G2 

Notes

Acknowledgements

The authors acknowledge the gracious support from the Insurance Risk and Finance Research Centre (IRFRC) at the Nanyang Business School and Japan Society for the Promotion of Science under “KAKENHI” Grant Number JP18H00874 (Grant-in-Aid for Scientific Research (B)). The authors also thank the anonymous referee, the Editor Kip Viscusi, Richard Butler, David Eckles, Gene Lai, Richard Lu, Stefan Trautmann, Soichiro Moridaira, Hisashi Nakamura, and Takashi Yamasaki for their helpful comments on our previous draft.

Supplementary material

11166_2019_9310_MOESM1_ESM.docx (71 kb)
ESM 1 (DOCX 70 kb)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Nanyang Technological UniversitySingaporeSingapore
  2. 2.Keio UniversityTokyoJapan

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