Impact of neighborhood features on housing resale prices in Zhuhai (China) based on an (M)GWR model

Abstract

ABSTRACT The paper aims at exploring the relationship between housing resale prices and neighborhood features in Zhuhai, as well as structure and location characteristics. Thirteen neighborhood features are collected to analyze their influence on average community-level apartment resale prices in 2018. Six neighborhood features, structural and location characteristics, are selected according to their statistical significance and multicollinearity test results from an OLS model. Regression analysis is performed by OLS, GWR, and MGWR to compare their performance in housing price research at community level. The comparison of the three models also demonstrates that the GWR (66%) and MGWR (68%) models perform much better than OLS model (52%). MGWR is not significantly different from GWR in areas with few sample points, and the optimal bandwidth at different spatial scales is hard to be captured in a city-level study area. The regression parameter indicates that building age is the most important factor among all influencing factors. Proximity to schools and factories have positive and negative significant effects on housing resale prices, respectively. The spatial pattern of neighborhood features is also detected at town level. GWR and MGWR models accurately demonstrate local spatial heterogeneity of the housing resale market, which provides better results than the traditional OLS model in the goodness of fit and parameter estimates when spatial dependency is present. The results provide references for local planning departments, helping to reveal the complicated relationship and spatial patterns between housing price and determinants over space.