Study On Capitalization Effect Of Rail Transit In Shanghai Housing Price Based On Spatial Measurement

With the rapid rise of housing price and the development of rail transit industry, more and more homebuyers began to focus on the condition of rail transport around the property when they were signing their contract. However, the development of residence and the construction of the public facilities get spatial heterogeneity themselves. As a result, part of the homebuyers’ demand of public traffic will not be satisfied, which leads the spatial imbalance of residents’ demand of rail transit. According to the capitalization theory, the public revenue will be capitalized to local housing price after all. Actually, the more the capitalization rate a community gets, the more demand the community’s traffic demand is.As the studies in Shanghai has not considered about the spatial factors in these fields, which were recognized by the researchers in recently years, this paper will use the spatial econometrics to research the capitalization effect of the rail transit in Shanghai’s housing price. Based on the hedonic model, this paper build a series of models to research the capitalization effect of the rail transit in Shanghai’s housing price in different ways, which conclude OLS model, SAR model, GWR models and SQR models. From GWR models, we can get analysis of the capitalization effect’s price heterogeneity, and in SQR models, we perform the spatial heterogeneity in the effect.The empirical results show that the capitalization effect of the rail transit in Shanghai’s housing price does exist. In OLS model, it concludes that the more distance of the property and the railway platform gets, the less the housing price will be. Also OLS model showed that the distance between 500 meters and 1000 meters does more contributions to the change of the housing price, which makes resident more sensitive to this section. In the conclusion of spatial heterogeneity, the center properties get lower capitalization effect than the suburbs. Further, after measuring the significance of communities’ capitalization effect, this paper concludes that there is some relevance between the distance to the city’s center and the significance, which is the increasing distance lead to the more significance. When adding the spatial factor the hedonic models, we use SAR models to prove the positive relevance of the housing price in Shanghai, and the auto-relevance coefficient is 0.32. Different from the average regression, quantile regression shows that capitalization effect is quite different in different quartiles, the cheaper houses get a negative relevance on the distance to railway platform, and the dear properties get positive relevance instead.At last, this paper gives some suggestions on the plan of the new railway construction and the new properties to avoid the imbalance on the public service according to the empirical results. What’s more, as the housing price soars in recent days, this paper also gives some policy suggestions about the land value capture on collection taxes and the finance and investment to limit the constant increase on the housing price.