LAUSR

Most existing studies empirically investigated the impact of rail transit on housing prices using the traditional hedonic price model, which is based on ordinary least squares (OLS). This method can estimate only the average implicit prices of housing characteristics and may ignore possible heterogeneous impacts of rail transit at different housing price levels. As a useful supplement to OLS regression, quantile regression can measure how implicit prices of explanatory variables vary across different price levels, thereby providing a comprehensive picture of the relationship between housing characteristics and prices. By using Hangzhou, China as an example, this study adopts the traditional hedonic price model and quantile regression model to investigate the capitalization effect of a new subway line on housing prices. Empirical results suggest the significant impacts of accessibility to subway stations. The average housing price within 2 km of the station is 2.1% to 6.1% higher than those outside. We also find that the impacts of the subway differ significantly across the distribution of housing prices, wherein the absolute value of estimated coefficients increased from 0.023 for the 15th quantile to 0.086 for the 95th quantile. The subway opening strengthens the capitalization effect of traffic accessibility. The absolute value of price elasticity increases from 0.044 to 0.053, and the range of influence is expanded from 1500 m to 2000 m.