蔡荣等：Policy-driven education-led gentrification and its spatiotemporal dynamics: Evidence from Shanghai, China

蔡荣助理教授与合作者Shenjing He, Lirong Hu的研究论文发表在SSCI地理类优秀期刊The Geographical Journal

摘要：

As a highly sought-after resource by parents, quality schools exert a strong influence on the housing market and other aspects of social life worldwide. Given the long-lasting prominence of education in urban society, scholars extensively explored the interplay between education and housing dynamics and their sociospatial implications, among which the scholarship on education-led gentrification offers a prominent and productive conceptual lens. While the literature on education-led gentrification in developed economies is proliferating, little is known about the dynamic linkages between school choice and residential segregation in developing contexts, including China. Drawing on a longitudinal housing transaction (2011–2020) dataset covering 762 residential neighbourhoods in Shanghai, the largest and most developed city in China, this research quantitatively examines the process of gentrification driven by the accessibility to educational resources and its spatiotemporal dynamics. Based on analyses employing hedonic price models and a geographically and temporally weighted regression model, this study reveals the uneven evolution of education-led gentrification across space and time. Specifically, this study argues that the spatial variations in education-led gentrification in Shanghai and its temporal changes are largely policy driven. This finding foregrounds schools as an important driver of gentrification rather than merely a ‘downstream effect’ of the existing gentrification process, especially in recently gentrifying suburbs. Therefore, this study adds novel conceptual and empirical insights to the scholarship of education-led gentrification in non-Western contexts in particular and the literature on the geographies of education in general.

关键词：

education-led gentrification, school choice, residential segregation, hedonic housing price model, geographically and temporally weighted regression, Shanghai

论文链接： https://rgs-ibg.onlinelibrary.wiley.com/doi/10.1111/geoj.12440