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Earthquake Risk Embedded in Property Prices: Evidence From Five Japanese Cities

  • Masako Ikefuji
  • , Roger J.A. Laeven*
  • , Jan R. Magnus
  • , Yuan Yue
  • *Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

We analyze the impact of short-run (90 days) and long-run (30 years) earthquake risk on real estate transaction prices in five Japanese cities (Tokyo, Osaka, Nagoya, Fukuoka, and Sapporo), using quarterly data over the period 2006–2015. We exploit a rich panel dataset (331,343 observations) with property characteristics, ward attractiveness information, macroeconomic variables, and long-run seismic hazard data, supplemented with short-run earthquake probabilities generated from a seismic excitation model using historical earthquake occurrences. We design a hedonic property price model that allows for subjective probability weighting, employ a multivariate error components structure, and develop associated maximum likelihood estimation and variance computation procedures. Our approach enables us to identify the total compensation for earthquake risk embedded in property prices, to decompose this into pieces stemming from short-run and long-run risk, and to distinguish between objective and subjectively weighted (“distorted”) earthquake probabilities. We find that objective long-run earthquake probabilities have a statistically significant negative impact on property prices, whereas short-run earthquake probabilities become statistically significant only when we allow them to be distorted. The total compensation for earthquake risk amounts to an average –2.0% of log property prices, slightly more than the annual income of a middle-income Japanese household. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.

Original languageEnglish
Pages (from-to)82-93
Number of pages12
JournalJournal of the American Statistical Association
Volume117
Issue number537
Early online date23 Jul 2021
DOIs
Publication statusPublished - 2022

Bibliographical note

Funding Information:
This research was supported in part by the Japan Society for the Promotion of Science (JSPS) under grant 16K03565 (Ikefuji) and the Netherlands Organization for Scientific Research (NWO) under grant VIDI (Laeven). We are very grateful to the editor, associate editor and three referees for thoughtful comments and suggestions that have significantly improved the article. Earlier versions of this article were presented at Keio University in Tokyo, the Technische Universit?t Wien, the Universities of Oxford, Madrid and Fudan, and at the 2018 Econometric Society Australasian Meeting in Auckland and the 2018 China Meeting of the Econometric Society in Shanghai. We thank the participants and in particular Yoshitsugu Kanemoto for helpful comments.

Publisher Copyright:
© 2021 The Author(s). Published with license by Taylor & Francis Group, LLC.

Funding

This research was supported in part by the Japan Society for the Promotion of Science (JSPS) under grant 16K03565 (Ikefuji) and the Netherlands Organization for Scientific Research (NWO) under grant VIDI (Laeven). We are very grateful to the editor, associate editor and three referees for thoughtful comments and suggestions that have significantly improved the article. Earlier versions of this article were presented at Keio University in Tokyo, the Technische Universit?t Wien, the Universities of Oxford, Madrid and Fudan, and at the 2018 Econometric Society Australasian Meeting in Auckland and the 2018 China Meeting of the Econometric Society in Shanghai. We thank the participants and in particular Yoshitsugu Kanemoto for helpful comments.

FundersFunder number
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Econometric Society Australasian Meeting in Auckland
Keio University in Tokyo
Econometric Society in Shanghai
Technische Universität Wien
Japan Society for the Promotion of Science23K20145, 16K03565

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 11 - Sustainable Cities and Communities
      SDG 11 Sustainable Cities and Communities

    Keywords

    • Earthquake risk
    • Hedonic pricing
    • House price
    • Multivariate error components
    • Probability weighting
    • Seismic excitation

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