Reconstructing Social Segregation in Danwei: An Examination of High-Quality Education Resources’ Impact on Housing Prices in Nanjing, China

Abstract

This study investigates the impact of capitalizing educational resources on housing prices. As housing has gradually transitioned from a basic social right to a means of accumulating individual and familial wealth, it has emerged as a significant indicator of social stratification and has increasingly become a crucial tool for the intergenerational reproduction of social class. This paper takes Nanjing, China, as a case study and uses the geographically weighted regression model (GWR) and the hedonic pricing model (HPM) to investigate the impact of high-quality primary schools on housing prices. The results show that high-quality educational resources have become the most significant influencing factor on residential prices in Nanjing. The analysis in the mechanism section further indicates that the uneven distribution of educational resources in China is a continuation of the “danwei” system. Moreover, during the urbanization process, these high-quality educational resources are often leveraged by the government and developers, who see them as essential tools to attract investment and inflate housing prices. Therefore, the current overlap of the school district system and the marketization of housing in China not only intensifies residential segregation within the city, leading to severe residential inequality but also rebuilds social segregation within “danwei” and facilitates its reproduction.

Hedonic Approach to Vertical Residential Rentals in the Brazilian Amazon: The Case of Belém, Pará

“…Finally, the qualities of the neighborhood refer to the characteristics of the neighborhood or surrounding area that can affect the price of the property. These include the quality of public transport facilities [19], the quality of schools [13,39], the presence of green amenities [22], the presence of landscape amenities [35,40], and the presence of sports facilities [41], among others. Some authors, seeking to emphasize other analyzed characteristics, establish other categorizations: transport attributes [15,36], traffic conditions [17], landscape amenities [40], green areas [22], environmental characteristics [20], educational characteristics [13], and socioeconomic factors [42].…”