Abstract
This study examines the importance of accounting for rare but catastrophic events even if the probability of occurrence is extremely low, which is often ignored when expected utility is considered. To provide empirical evidence for this, we present the land price change related to the Japanese government’s report on the damage of catastrophic earthquakes and tsunamis whose probability of occurrence is extremely low. While this relationship has been studied in previous research, there are some notable shortcomings. Firstly, the control of the attributes between the treatment group, namely the land in the area where information is updated, and the control group is insufficient. Secondly, the link between rational behavior and the estimation result is not established enough. This study addresses these two points and updates the findings in this regard. We find that the estimated results presented herein match those proposed by previous works, confirming that the established link between the data and rational behavior suggests the importance of accounting for such catastrophic events even if their probability of occurrence is extremely low.
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Notes
Levitt and List (2007) state that laboratory experiments may not be generalizable to the real world and find that the lack of real data leads to the absence of convincing evidence that supports economic theories for evaluating catastrophes.
In this paper, the word “rare” is used to indicate that the probability of occurrence is too small to assign objective or subjective probability.
The number of deaths is calculated to be at least 32,000 when an earthquake hits Kyusyu or Shikoku, even when waterproof fences work properly, the ratio of early evacuation is high, and other fortunate conditions. The figure of 32,000 is 1.73 times larger than that of the Great East Japan Earthquake (sum of dead and missing was 18,468 as of June 10, 2015). The maximum number of deaths is calculated to be 229,000 in the Kyushu scenario and 323,000 in the Tokai scenario. These numbers are taken from http://www.bousai.go.jp/jishin/nankai/taisaku/pdf/20120829_higai.pdf (in Japanese).
An NT earthquake is a hypothetical occurrence of Tokai, Tonankai, and Nankai earthquakes replicable by using conventional earthquake models.
The matching method does not work if the covariates do not overlap.
Nakanishi (2014) presents the local treatment effect \(E(P_{2013} \left( 1 \right) -P_{2013} \left( 0 \right) |r=1,x_1 ,x_2 )\) under similar conditions to those in Eq. (15). However, because it is difficult to interpret \(E(P_{2013} \left( 1 \right) -P_{2013} \left( 0 \right) |r=1,v)\), the link between expected utility and the estimation is insufficiently established.
We remove East Kanto and Tohoku from the analysis to ensure the validity of this assertion.
Naoi et al. (2009) analyze changes in the perception of earthquake risk by using the link between the derivative of the price function and maximization of expected utility.
Nakanishi (2014) points out the difference between Eqs. (6) and (13). However, the estimated local effect \(E\left( P_{2013} \left( 1 \right) -P_{2013} \left( 0\right) |r=1,v\right) \) is not linked to the derivative of the price function because the estimated linear price function cannot capture the local change in the price function’s derivative.
The estimation results for the different bandwidth parameters are available on request.
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Acknowledgments
I am grateful to the editor and two referees for their comments that greatly improved the paper. I also thank Graciela Chichilnisky, Christopher F. Parmeter, Noboru Hidano, participants at 2013 SEEPS conference and seminars at Kyoto University, and Tokyo Institute of Technology for useful discussions. Financial support from the Japan Society for the Promotion of Science (JSPS) (12J09136) is gratefully acknowledged.
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Nakanishi, H. Quasi-experimental evidence for the importance of accounting for fear when evaluating catastrophic events. Empir Econ 52, 869–894 (2017). https://doi.org/10.1007/s00181-016-1084-6
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DOI: https://doi.org/10.1007/s00181-016-1084-6