This paper introduces the market price of house rent in SUUMO as an example of applications for big data utilization. The market price using average or median of house rent may not be appropriate with respect to the stabilization. This paper investigates the possibility of the market price using statistical models using linear regression or random forests to make the market price to be stabilized. This analysis uses the data of houses listed in SUUMO from August 2016 to October 2016 and the number of houses are about three million. The result shows that the market price using random forest with smoothing is the most appropriate in our case.

This paper focused on a method of data cleansing for used condominium database that is open to the public by the Ministry of Land, Infrastructure, Transport and Tourism. By identifying and removing error records, which are not transaction outliers, it enables us to analyze this dataset appropriately. In this study, we proposed two methods to deal with serious error, that is suspect of “Fat finger error”. In addition, as a result of noise removal, the analysis results using the hedonic model have improved significantly.

国内の商業用不動産はデフレやCOVID-19の影響がありながらも価格指数は増大している．一方，不動産需要は供給が対応できないとビジネスチャンスを逸してしまう危険性があり，できるだけ早めに需要の増大を把握することが必要となる．本研究では，ある不動産関連企業が収集した近畿圏内の不動産需要について，これに関係する株式取引銘柄を発見し，その出来高を利用して，需要量を予測する重回帰モデルを構築する．また，これらの株式銘柄をその取引状況の類似性でクラスタリングを行い，各クラスタに共通したキーワードのタクソノミを構築することで，どのような事業内容の企業の動向が当該需要に影響を与えるかを明確化する．

This paper proposes the compensation for siting nuisance facilities applying adjustable strike put options. This option provides future rights to residents living near a nuisance facility to sell their property at an appropriate price that corresponds to the property that has no nuisance facility near it. I built a model to evaluate the value of the option and developed a trial to compute the value in the Tokyo metropolitan area. As a result, the value of the option is 5.03% of the initial land price; almost the same value as the difference of the expected land value in the future between a nuisance siting area and a no nuisance area. The advantage of the compensation with this option is that the residents near the facility can expect the appropriate operation of the facility and the environmental management around the facility after the siting, because the facility manager will be urged to avoid the loss brought by the option exercise.

It is often said that real estate price information in Japan is less sufficient than that in the US. Especially, we need price estimates of a specific real estate that reflects local characteristics. In this paper, we suggest a local price estimate method using GWR and a web system for publification.

This article reviews several studies that have examined the impact of collateral value of real estate on firms’investment and financing and emphasizes the importance of firm-level data employed for analysis. It first reviews two seminal studies, Gan（ 2007） for Japan and Chaney et al.（ 2012） for the United States, to point out their contributions as well as potential identification problems. It then explains that Uesugi et al. （2018） address some of these identification issues by taking advantage of exogenous shocks to real estate values caused by a natural disaster. Lastly, the article provides a few suggestions of data sources for future research.

Based on the expressed preference data of condominium buyers and inverse probability weight, this study examined the influence of their perceptions of the state of maintenance on internal reference prices. According to the findings, maintaining good maintenance conditions not only increases the aspiration prices of buyers, but it also increases the lower limit of price negotiations. Meanwhile, in the price judgment process, buyers who perceive that the state of maintenance and management is good tend to carefully search for properties. We also found that it is important to raise awareness regarding the appropriateness of purchase prices.

This paper discusses the future of cities in the With/After Corona, focusing on the conflicting concepts of “dispersion” and “aggregation” of urban structures. As a result of the analysis, the demand for real estate is shifting from offices to housing, and it became clear that it is important to improve the quality of living areas in the neighborhood of the residence.

The data utilised for the analyses of real estate market can be classified into two categories; revealed preference data （RP） and stated preference data （SP）. In practice, RP have been already used for wide range of analyses, including composition of real estate price and rent indices. Besides, in order to assess real estate market trend correctly, observation of such indices is sometimes inadequate, because indices tend to be distorted in specific cases. Hence it is desirable to complement RP with SP. This essay gives some empirical examples of the existing researches and literatures which deal with SP in real estate field, and the author suggests advantages of utilising SP as information resources.