This study aims to examine the spatial relationship between sustainable urban development and housing prices across 120 metropolitan statistical areas (MSAs) in 28 countries, 2010–2023.
Grounded in hedonic pricing, urban land-use and spatial dependence theory, a composite Green Urban Development Index (GUDI) is built via principal component analysis (PCA) across five sustainability dimensions. Spatial lag and spatial error models are estimated by quasi-maximum likelihood within a spatial panel framework, complemented by geographically weighted regression (GWR) on a 42-city subsample and two-stage least squares (2SLS).
A ten-point GUDI increase is associated with an 11.8%–12.7% rise in median housing prices (spatial lag model ß = 0.118***; 2SLS ß = 0.118–0.127***), consistent with a causal interpretation once spatial dependence and endogeneity are addressed. Ordinary least squares estimates (0.142***) are 14%–21% higher, consistent with upward endogeneity bias. Housing prices show strong spatial dependence (Moran’s I = 0.61, p < 0.01), with GWR estimates indicating stronger effects in denser, higher-income areas; diagnostics confirm robustness across specifications.
The analysis relies on available institutional data sets and may not fully capture micro-level heterogeneity within cities; GWR estimates draw on a 42-city subsample rather than the full 120-MSA panel.
Findings suggest that sustainable urban development investment is associated with higher property values, offering evidence relevant to policymakers, urban planners, and real estate stakeholders, though distributional effects on affordability warrant careful attention.
This study contributes a PCA-based composite index (GUDI) and integrates spatial econometric and instrumental-variable methods to provide cross-national evidence on the sustainability–housing price relationship.
