The Impact Of Urban Rail Transit On Real Estate Values

With the urbanization of China, rapid growth of urban population and large expansion of city borders have led to more and more serious traffic problems. Urban Rail Transit, as a fast, punctual, clean, large transport volume, and low accident rate public transport facility, is a good way to ease traffic pressure. The construction and operation of Urban Rail Transit may influce the real estate values. Studies about identifying the impact of Urban Rail Transit on real estate values are important to the development of real estate market and the whole city. However, most domestic studies have used Hedonic Price Model based on Ordinary Linear Regression (OLR), ignoring spatial non-stationary effects.This paper firstly summarizes recent studies, then analyzes the influence of Urban Rail Transit on real estate values in theory, identifys the applicability and science of Hedonic Price Model, and then takes Hangzhou as an example, building Hedonic Price Model based on OLR and Geographically Weighted Regression (GWR), and using 950 housing samples to empirically analyze the overall and local impact of Hangzhou Linel on the housing values, and clearly showing spatial differences by pictures. The models suggest that, Hangzhou Linel has positive influence on the surrounding housing prices. With the distance reducing by lkm, the average housing prices increase by 739 yuan/m2. Models also reveal obvious spatial differences. In the CBD, if the distance away from station reduces by 1km, the housing unit price increases by 556～872 yuan/m2. In the sub-center area, houses to the nearest station are closer by 1 km, the unit price increases by 872～1188 yuan/ m2. In the suburb, while residential distance to the nearest site reduces by 1km, the unit price increases by 1188～1504 yuan/m2. Model results further suggest the trend of "highest in the remote town, followed by the downtown, and lowest in the CBD". Finally, the paper proposes the policy implications based on the conclusions. Keywords:Urban Rail Transit; Real Estate Values; Hedonic Price Model; Geographically Weighted Regression...