Urban Structure, Subway Systemand Housing Price: Evidence from Beijing and Hangzhou, China

Abstract

Using housing market data of Beijing and Hangzhou, China, we conduct a case study to detect how the difference of urban structure can affect the relationship between the subway system and housing prices. To quantify the characteristics of urban structure, we propose a constrained clustering method, which can not only reveal the spatial heterogeneity of the housing market, but also provides a link between heterogeneity and the underlying urban structure. Applying constrained clustering to Beijing and Hangzhou, we find that the relationship between accessibility to metro stations and housing prices is weak and vulnerable, while the improvement of commuting efficiency, measured by a key variable, the metro index, does have a robust connection to metro premium on housing units. In particular, only a large metro index can be associated with a positive metro premium. Structural features, such as the size of urban core and the existence of multiple sub-centers, influence the metro premium by affecting the value and spatial distribution of the metro index. The evidence from Beijing and Hangzhou supports that in a mono-centric city, the size of the urban core is positively associated with the metro index and the metro premium, while in a poly-centric city with a small urban core, the metro index tends to be lower in the core region and higher in the satellite regions, which enforces the metro premium to be negative in the core while positive outside of the core.

Transport Mode and the Value of Accessibility–A Potential Input for Sustainable Investment Analysis

“…On the other hand, the results by [32,33] show only weak evidence that a new suburban transportation station increases retail activity measured as retail employment and no effects in a central location. Another explanation, which is also studied by [25], is that neighborhoods with different socio-economic structures will value accessibility differently.…”

Property Price Modelling, Market Segmentation and Submarket Classifications: A Review

“…Employing GIS and spatial analytical tools, the study found that housing market dynamics are better captured by the combined structural and spatial housing attributes effects. The contained clustering method was also used by Zhang et al (2019) to identify heterogeneity in the housing market in the underlying urban structure.…”

Impact of Transit-Oriented Development on Residential Property Values around Urban Rail Stations

“…Pan and Zhang found that property values increased in Shanghai by 152 yuan (1 yuan = $0.14 in Feburary 2020) per square meter for every 100 m closer to a transit station (20). Some studies have also considered spatial heterogeneity in relation to TOD impact: Zhang et al introduced the metro index and proposed a constrained clustering method as a link between spatial heterogeneity and urban structure to measure the true impact of transit stations on housing prices; they found that the effects of metro systems on housing prices tended to be positive in satellite regions and negative in core regions in polycentric cities such as Beijing and Hangzhou (21).…”