Reexamining the nonlinear effects of public services on housing prices from the lenses of proximity, availability and quality

Understanding the complex interplay between public services and housing markets is essential for building inclusive and sustainable cities. However, existing studies on the housing price effects of public services are limited because they overlook multidimensional public service characteristics. In this study, the nonlinear effects of public services on housing prices are reexamined within a three-dimensional framework that considers proximity, availability and quality. The gradient boosting decision tree (GBDT) algorithm is applied to infer the nonlinear effects of four types of public services (education, healthcare, parks and metros) on housing prices in Beijing. The results reveal that (1) the quality and availability of public services are the primary influencing factors of housing prices, whereas the importance of proximity to facilities might be overstated in existing studies. (2) Generally, the proximity to and the quality of public services positively influence housing prices, but the “not in my backyard” (NIMBY) effect occurs within a relatively short distance from healthcare facilities and middle schools. The association between availability and housing price shows an “M-shaped” relationship. (3) Interactive effect analyses reveal that high quality and high availability can amplify the effect of proximity on housing prices. The findings have implications for equitable urban public service provision and the planning of inclusive and sustainable cities.