The Effect of a Subway on House Prices: Evidence from Shanghai

Zhou, Zhengyi; Chen, Hong; Han, Liang; Zhang, Anming

doi:10.1111/1540-6229.12275

Cited by 49 publications

(24 citation statements)

References 47 publications

(77 reference statements)

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“…This study includes the variable of access to subway stations for the analysis. Access to subway stations is a significant factor in land prices [50][51][52]. In Korea, a concept of "access to subway stations" has been used as the name of the "station catchment area" [53], and several studies have been conducted on how access to subway stations affects local land prices [54,55].…”

Section: • Access To Subway Stationsmentioning

confidence: 99%

Neighborhood Walkability and Housing Prices: A Correlation Study

Kim

2020

Sustainability

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This study aims to examine the relationship between the level of walkability and housing prices in Seoul, Korea. The average transaction price per square meter for each apartment complex was set as a dependent variable and the walkability score was used as an independent variable. This study divided a total of 5986 apartment complexes into areas with high and low housing prices for analysis. Based on the strong spatial autocorrelations of housing prices, this study employed spatial regression models in addition to the Ordinary Least Squares (OLS) model. Results showed that housing prices positively correlated with the walkability score in areas with low housing prices, whereas no significant association was observed in areas with high housing prices. Additional findings showed that housing prices were associated with building age (−), number of households in the complex (+), slope (−), and greenness (+) in both subsamples. Results also showed that high school quality had a different association with housing prices depending on the subsample (e.g., the sign was positive in areas with high housing prices and no significance in areas with low housing prices). The results herein support public policy proposals relevant to urban planning, environmental design, and housing policies.

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Section: • Access To Subway Stationsmentioning

confidence: 99%

Neighborhood Walkability and Housing Prices: A Correlation Study

Kim

2020

Sustainability

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“…The convenience lies in the time savings brought by subways. Using subway Line 6 in Shanghai as an example, Zhou et al ( 2021 ) show that the subway reduces residents’ commuting time to major employment centers, which leads to house price appreciation in the vicinity of the subway. The local demand for subway service is large.…”

Section: Hypothesis Development and Econometric Approachmentioning

confidence: 99%

“…Second, the benefits and costs of bike sharing are both obvious in Shanghai. On the one hand, Shanghai has the world’s largest rapid transit (subway) system by route length (Zhou et al, 2021 ). Since bikes are not allowed on subways, the value of bike sharing as a complement to the public transportation network is potentially high.…”

Section: Introductionmentioning

confidence: 99%

Does Bike Sharing increase House Prices? Evidence from Micro-level Data and the Impact of COVID-19

Zhou

Zhang

2022

J Real Estate Finan Econ

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With unique datasets, this paper studies the effects of dockless bike sharing on house prices. We find that in neighborhoods relatively far from subway stations, house prices increase with the usage intensity of shared bikes. This indicates a positive value of bike sharing as a complement to the subway network. Meanwhile, shared bike usage intensity also has a negative impact on house prices. The negative effect is mitigated for luxury neighborhoods and neighborhoods near City Management Teams, suggesting that the negative effect is related to bike misplacement. Since the breakout of COVID-19, both the positive and negative price impacts have become more evident. This is consistent with the fact that the user base of shared bikes, which allow for social distancing in an open space, has increased during the pandemic. This may enhance people’s confidence in the long survival of the bike sharing industry.

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“…We contribute further by investigating the interplay between the ownership market 1 See Dewees (1976) for Toronto, McDonald and Osuji (1995); McMillen and McDonald (2004); Diao, Leonard, and Sing (2017) for Chicago, Cervero and Duncan (2002) for San Jose, Lin and Hwang (2004) for Taipei, Hess and Almeida (2007) for Buffalo, sixteen cities among which Atlanta, Boston, Chicago, Portland, and Washington DC by Kahn and Baum-Snow (2005), Zheng and Kahn (2013) for Beijing, Fesselmeyer and Liu (2018) for Singapore, and Zhou, Chen, Han, and Zhang (2020) for Shanghai. Also see the structural analysis of transit improvements in Heblich, Redding, and Sturm (2018) for historic London and Ahlfeldt, Redding, Sturm, and Wolf (2015) for post-reunification Berlin.…”

Section: Literature Reviewmentioning

confidence: 99%

Take the Q Train: Value Capture of Public Infrastructure Projects

Gupta¹,

Nieuwerburgh²,

Kontokosta³

2019

SSRN Journal

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Transit infrastructure is a critical asset for economic activity yet costly to build in dense urban environments. We measure the benefit of the Second Avenue Subway extension in New York City, the most expensive urban transit infrastructure project in recent memory, by analyzing local real estate prices which capitalize the benefits of transit spillovers. We find 8% price increases, creating $6 billion in new property value. Using cell phone ping data, we document substantial reductions in commuting time especially among subway users, offering a plausible mechanism for the price gains. The increase in prices reflects both higher rents and lower risk. Infrastructure improvements lower the riskiness of real estate investments. Only 30% of the private value created by the subway is captured through higher property tax revenue, and is insufficient to cover the cost of the subway. Targeted property tax increases may help governments capture more of the value created, and serve as a useful funding tool.

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The Effect of a Subway on House Prices: Evidence from Shanghai

Cited by 49 publications

References 47 publications

Neighborhood Walkability and Housing Prices: A Correlation Study

Neighborhood Walkability and Housing Prices: A Correlation Study

Does Bike Sharing increase House Prices? Evidence from Micro-level Data and the Impact of COVID-19

Take the Q Train: Value Capture of Public Infrastructure Projects

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