Quantity or structure? Asset or burden? Causal evidence of street greenery’s impact on housing prices from sequential data

Abstract

Street greenery, as critical green infrastructure, provides extensive ecosystem services, and accurately evaluating its value benefits urban greening strategies and funding decisions. Previous studies relying on cross-sectional data and hedonic regression models are limited by confounding factors, thus failing to accurately measure the net effects of street greenery characteristics on housing prices. To address this limitation, hedonic regression, propensity score matching and difference-in-differences methodologies were employed based on housing price and built environment data from 2017 to 2022 to analyze how street greenery quantity and vegetation structure affect housing prices. Results indicated that street greenery impacts differ significantly between the central area and the expanded central area, revealing a negative price effect defined as the “Green Burden Effect” in expanded central area. Additionally, greenery quantity changes exerted stronger and more stable price impacts compared to vegetation structure. The DID analysis further clarified temporal changes in these relationships. Employing multiple econometric models revealed the complex spatial-temporal relationships between street greenery and housing prices, emphasizing the importance of spatially targeted greening strategies to optimize residential values and promote equitable urban development.