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Estimation of nonlinear functions using coarsely discrete measures in panel data: The relationship between land prices and earthquake risk in the Tokyo Metropolitan District

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  • Gu, Tao
  • Nakagawa, Masayuki
  • Saito, Makoto
  • Yamaga, Hisaki

Abstract

This paper proposes a simple method to estimate a nonlinear function using only coarsely discrete explanatory variables in panel data. The basic premise is to distinguish carefully between two types of discrete variables by assuming that if the variable changes between two points in time, it increases (decreases) marginally from near the upper (lower) bound one rank below (above). The dynamic pricing behavior at the boundary between two consecutive ranks is then properly approximated. Applying the proposed method, we estimate the nonlinear relationship between land prices and earthquake risk, with the latter being assessed over only five ranks. The panel datasets used comprise some two thousand fixed places over time in the Tokyo Metropolitan District. We interpret the estimated nonlinear land pricing functions using prospect theory from behavioral economics.

Suggested Citation

  • Gu, Tao & Nakagawa, Masayuki & Saito, Makoto & Yamaga, Hisaki, 2021. "Estimation of nonlinear functions using coarsely discrete measures in panel data: The relationship between land prices and earthquake risk in the Tokyo Metropolitan District," Discussion Paper Series 729, Institute of Economic Research, Hitotsubashi University.
  • Handle: RePEc:hit:hituec:729
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    References listed on IDEAS

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    1. Mehra, Rajnish & Prescott, Edward C., 1985. "The equity premium: A puzzle," Journal of Monetary Economics, Elsevier, vol. 15(2), pages 145-161, March.
    2. Levon Barseghyan & Francesca Molinari & Ted O'Donoghue & Joshua C. Teitelbaum, 2013. "The Nature of Risk Preferences: Evidence from Insurance Choices," American Economic Review, American Economic Association, vol. 103(6), pages 2499-2529, October.
    3. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    4. Bali, Turan G. & Cakici, Nusret & Whitelaw, Robert F., 2011. "Maxing out: Stocks as lotteries and the cross-section of expected returns," Journal of Financial Economics, Elsevier, vol. 99(2), pages 427-446, February.
    5. Naoi, Michio & Seko, Miki & Sumita, Kazuto, 2009. "Earthquake risk and housing prices in Japan: Evidence before and after massive earthquakes," Regional Science and Urban Economics, Elsevier, vol. 39(6), pages 658-669, November.
    6. Brian Boyer & Todd Mitton & Keith Vorkink, 2010. "Expected Idiosyncratic Skewness," The Review of Financial Studies, Society for Financial Studies, vol. 23(1), pages 169-202, January.
    7. Masayuki Nakagawa & Makoto Saito & Hisaki Yamaga, 2009. "Earthquake Risks And Land Prices: Evidence From The Tokyo Metropolitan Area," The Japanese Economic Review, Japanese Economic Association, vol. 60(2), pages 208-222, June.
    8. Tao Gu & Masayuki Nakagawa & Makoto Saito & Hisaki Yamaga, 2018. "Public Perceptions of Earthquake Risk and the Impact on Land Pricing: The Case of the Uemachi Fault Line in Japan," The Japanese Economic Review, Japanese Economic Association, vol. 69(4), pages 374-393, December.
    9. Gu, Tao & 顧, 濤 & Nakagawa, Masayuki & 中川, 雅之 & Saito, Makoto & 齊藤, 誠 & Yamaga, Hisaki, 2012. "Public perceptions of earthquake risk and its impact on land pricing: The case of the Uemachi fault line in Japan," Discussion Papers 2012-07, Graduate School of Economics, Hitotsubashi University.
    10. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
    11. Iwasaki, Keiko & Lee, Myoung-jae & Sawada, Yasuyuki, 2019. "Verifying reference-dependent utility and loss aversion with Fukushima nuclear-disaster natural experiment," Journal of the Japanese and International Economies, Elsevier, vol. 52(C), pages 78-89.
    12. repec:cup:judgdm:v:10:y:2015:i:4:p:365-385 is not listed on IDEAS
    13. Zhang, Wenlang & Semmler, Willi, 2009. "Prospect theory for stock markets: Empirical evidence with time-series data," Journal of Economic Behavior & Organization, Elsevier, vol. 72(3), pages 835-849, December.
    14. Page, Lionel & Savage, David A. & Torgler, Benno, 2014. "Variation in risk seeking behaviour following large losses: A natural experiment," European Economic Review, Elsevier, vol. 71(C), pages 121-131.
    15. Nicholas C. Barberis, 2013. "Thirty Years of Prospect Theory in Economics: A Review and Assessment," Journal of Economic Perspectives, American Economic Association, vol. 27(1), pages 173-196, Winter.
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    More about this item

    JEL classification:

    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns
    • R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

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