Abstract
In this chapter, the author examines whether there was an excess demand for housing after the Great East Japan Earthquake and Tsunami. In other words, this chapter investigates the possibility of using the housing market data as one of the proxies for socio-economic recovery activity indicators (RQ1b). As described in Chap. 3, various studies related to the housing market after a large-scale disaster have been conducted. However, to the author’s best knowledge, there is a paucity of research on investigating whether the housing market data could be a proxy of one of the socio-economic recovery activity indicators. Thus, this chapter examines the housing market data between one year before and three years after the disaster in the disaster-stricken area. Findings of this chapter show that the prices of houses leased close to the building damage zone and located in the plains increased after the disaster, indicating that there was the excess demand for those leased houses. The price of houses within 3 km to the building damage zone and located in the plains started to increase particularly four months after the disaster until fifteen months after the disaster. This suggests that people in the disaster area needed to rent housing which are close to where they used to live before the disaster but are not inundated even if the prices were a bit higher. In addition, because related studies have recognized that housing is one of the key factor for life recovery as described in Chap. 1, the author argues that the results support the appropriateness of using the housing market data as a proxy of one of the socio-economic recovery activities. The rest of the chapter is constructed as follows. First, the target data is introduced in Sect. 5.1. In Sect. 5.2, the model and variables are explained. In Sect. 5.3, the results of the analysis are described, and the results are discussed in Sect. 5.4. Finally, 5.5 concludes the results.
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Notes
- 1.
This chapter is a revised version of Shibuya and Tanaka (2019). The study is supported by Joint Research Program No. 823 at CSIS, University of Tokyo (“Real Estate Database 1999–2016” by At Home Co., Ltd.).
- 2.
Average of 2010 = 100,
http://www.mlit.go.jp/totikensangyo/totikensangyo_tk5_000085.html (accessed September 21st, 2018, in Japanese).
- 3.
Tohoku region includes Miyagi and Iwate prefectures.
- 4.
If a property does not have the information regarding the nearest station, the author manually checked and used the nearest station based on its address.
- 5.
http://www.mlit.go.jp/toshi/toshi-hukkou-arkaibu.html (accessed September 30th, 2018, in Japanese).
- 6.
This study considers Hirono-cho, Kuji-city, Noda-village, Fudai-village, Tanohata-village, Iwaizumi-town, Miyako-city, Yamada-town, Otsuchi-town, Ofunato-city, Rikuzen-Takata-city, Kesenuma-city, Minami-sanriku-town, Onagawa-town, and Ishinomaki-city as located in the “Sanriku Coast” based on https://ja.wikipedia.org/wiki/%E4%B8%89%E9%99%B8%E6%B5%B7%E5%B2%B8.
- 7.
For example, the lower 95% confidence limit of the first half of May in 2011 is compared with the upper 95% confidence limit of the first half of May in 2010. The lower 95% confidence limit of first-half of May in 2012 is also compared with the upper 95% confidence limit of first-half of May in 2010.
- 8.
Effect size of \(D_{k}\) is calculated by \(Cohens \quad f\). \(Cohen's\quad f=(((R\times 1\times 2)^{2}-(R\times 1)^{2} ))/((1-(R\times 1\times 2)^{2} ) )\) where \((R\times 1\times 2)^2\) is the Eq. (5.1) with all of the variables, and \((R\times 1)^2\) is the model without all \(D_k\).
- 9.
After the disaster, the housing lease program for those who lost their houses was implemented, and it supplied private rental houses as temporary housing. Only in Sendai city, 8,437 houses were rented under the housing lease program, while the number of temporary prefabrication house was 1,486 and public apartments were 713 (Meno 2013). To analyze the impact of the housing lease program, on the housing market, the author applied the sampled monthly numbers of apartments that were leased under the lease support program in Sendai (Personal Support Center 2012) (which was, to the author’s best knowledge, the only available detailed data regarding the program) to the Eq. (5.1) as a new variable (the number of leased houses were recalculated based on the portion of the dataset’s each area’s number). However, no statistically significant effect of the number of apartments leased under the program was found when the equation mentioned above was applied to properties in proprieties in the plains and within 3 km to the building damage zone (\(D_2\)) between the first half of March and September in 2011.
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Shibuya, Y. (2020). The Excess Demand for Housing. In: Social Media Communication Data for Recovery. Springer, Singapore. https://doi.org/10.1007/978-981-15-0825-7_5
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DOI: https://doi.org/10.1007/978-981-15-0825-7_5
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