Unveiling the Spatial Heterogeneity of Macroeconomic Factors for Real Estate Investment : A Comprehensive Analysis Based on City-level Data Analysis in China

This paper investigates the macroeconomic factors driving real estate investments, focusing on variations across different regions in China. Recognizing the significance of location in real estate and building upon existing literature that addresses spatial dependence through spatial econometrics, this study further explores the issue of spatial non-stationarity by employing the Multi-scale Geographical Weighted Regression model (MGWR). The MGWR approach processes city-level cross-sectional data through subsampling to yield individual coefficients for each city, thereby uncovering the degree of spatial non-stationarity present. The findings suggest that income levels, the student-to-population ratio, and per capita government expenditure have consistently impact on real estate investments, albeit with minor variations. Conversely, factors such as population size, the presence of real estate agents, and green coverage have a more variable influence across different regions.