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.
Highlights
Research on the influence of subways on housing price began in the 1970s when mass construction of rail transport began around the world [1,2]
The positive sign agrees with the results reported in previous empirical studies [5,13,31], and is consistent with the positive sign of the metro index and the theoretical point of view that the positive premium comes from the improvement of transportation convenience
K ≥ 1 where βS,m represents the estimated coefficients of the metro index for a cluster S, PβS,m is the P-value associated with that coefficient, and α denotes the significance level, which will be taken as 0.1; we did not select a finer significance level because all that is needed is just to exclude the negative premium induced by the metro index, and it is totally admissible that there is no significant connection between the subway system and housing prices given that a housing unit is far away from subways
Summary
Research on the influence of subways on housing price began in the 1970s when mass construction of rail transport began around the world [1,2]. Except for a few papers [1,14,15,16], previous studies focused mainly on accessibility to metro stations, which is measured by the distance to metro stations and/or the dummy variables derived from distance, such as whether there is a metro station within the range of one mile [13,17,18,19,20] These studies ignore the heterogeneity among different metro stations and might over-estimate the positive effect of the subway system on housing prices.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
