Impact of a new subway line on housing values in Daegu, Korea: Distance from existing lines

Im, Jun-Hong; Hong, Sung Hyo

doi:10.1177/0042098017741412

Cited by 22 publications

(11 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In transport-related intervention studies, a controlled interrupted time series research design is widely used, and the DID model is the statistical tool to estimate the treatment effect by comparing housing outcome variables between treatment and control groups before and after the intervention (Melser, 2020). In general, housing around new metro stations that receives improved transit accessibility is the treatment group (Im and Hong, 2018). The control group comprises housing without exposure to the new stations; this group is assumed to have a similar housing value change pattern (Murray and Bardaka, 2021).…”

Section: Causal Inference In Housing Premiums From Transit Proximitymentioning

confidence: 99%

New metro and housing price and rent premiums: A natural experiment in China

He,

Sun,

et al. 2023

Urban Studies

View full text Add to dashboard Cite

Causal evidence of housing premiums of new metro lines is indispensable for financing and governing infrastructure investments. Previous studies have investigated the housing effects of urban rail transit with varying methods, while causality remains unsettled. This study used a natural experiment to estimate the causal effects of the new metro interventions on housing premiums in Shenzhen, China. We used metro planning knowledge, reasoning on pursuits in land finance and engineering efficiency to verify the as-if randomness of the treatment–control group assignment in the natural experiment to reinforce the power of causal inference. We applied hedonic difference-in-difference (DID) models to estimate the average treatment effects based on the longitudinal housing price and rent data. We found that housing rents increased significantly and consistently after the metro entered operation, but the price premium varied. In addition, the rent premiums around new metro lines showed a price gradient over the distance to stations. Our findings provide scientific evidence for designing value capture mechanisms (e.g. value-added property tax and rent revenue) to recover metro investment costs in China.

show abstract

Section: Causal Inference In Housing Premiums From Transit Proximitymentioning

confidence: 99%

New metro and housing price and rent premiums: A natural experiment in China

He,

Sun,

et al. 2023

Urban Studies

View full text Add to dashboard Cite

show abstract

“…From 1950 to the present, theories on the interaction between urban roads and urban society and other elements mainly focused on the biological environment and landscape [1][2][3][4][5][6], urban agglomeration and urbanization [7][8][9][10][11][12], industrial transformation [13][14][15][16], land agglomeration use [17][18][19][20][21], real estate development [22][23][24][25][26][27][28], location [29][30][31][32][33][34][35][36][37], mixed land use [38][39][40][41], and property right [42,43]. Based on quantitative models, scholars have conducted a lot of research mainly on the interaction between economy, social demand [44,45], land and transportation [46].…”

Section: Literature Reviewmentioning

confidence: 99%

The External Characteristics and Mechanism of Urban Road Corridors to Agglomeration: Case Study for Guangzhou, China

Jia

Luo

et al. 2022

Land

View full text Add to dashboard Cite

Existing research on the agglomeration effect of urban roads mainly focuses on land use but ignores the differences between various locations, types, and directions of roads. Few studies have been conducted on the built buildings which can represent the actual utility, and land use as a kind of government authorization may not necessarily represent actual needs. This research provides an analytical framework and an empirical analysis to study the differences in impacts of different urban roads on land use and to identify its internal dynamic mechanism. Guangzhou, being the research object, is one of the five major central cities in China. By using the techniques of GIS and SPSS, together with the methods of corridor effect, correlation analysis, and geographic detector, we analyze the external characteristics of office buildings and land gathering along both sides of the roads, explore the urban characteristics of corridor effect, then analyze the relationship with urban traffic flow and bus network density in order to find out the internal motivation of corridor effect. The fundamental conclusion can be drawn that the corridor effect on the land used for commercial offices is mostly unnoticeable, and roads of different locations, types, and directions display various scope and intensity of corridor effects. The agglomeration power is mainly caused by private transportation and has no relationship with public transport. The article concludes the model of the corridor effect and provides some policy suggestions to the government in order to strengthen the linkage development of transportation and land and to promote the improvement of land use efficiency.

show abstract

“…Zhang (2014) examined housing prices statistics near Nanjing Lines one and two from a distance-based research perspective and discovered that rail has a positive influence on housing prices, with the results indicating that the stimulative effect of rail on housing prices growth is greatest when the distance between rail and residential is less than 500 m. Once the distance between rail and residential reaches 2,000 m, the growth effect ceases to be significant. Im and Hong (2018) examined the difference in housing prices in Daegu, South Korea, before and after the opening of the rail transit line. They discovered that housing prices within 500 m of the proximate station on the new line increased by approximately USD 96.3 per square foot.…”

Section: Influence Of Rail Station Proximity On Housing Pricesmentioning

confidence: 99%

Do hospital and rail accessibility have a consistent influence on housing prices? Empirical evidence from China

Chen

Lin²,

Cao³

et al. 2022

Front. Environ. Sci.

View full text Add to dashboard Cite

This study investigates the interaction between the accessibility of various urban public facilities and the price of urban space by analysing the influence of urban hospitals and rail accessibility on housing prices. In recent years, with the development of social civilisation and the influence of COVID-19, people have become increasingly interested in the quality of hospitals in their living environment. This makes medical convenience (hospital accessibility) a crucial element in determining housing prices. At the same time, people regard rail as one of the important means to access hospitals. Therefore, demonstrating the intrinsic value of accessibility to hospitals and rail in residential areas is essential. As a point of reference, this paper presents an empirical analysis of Fuzhou, Fujian Province, China, a city in a developing nation with relatively widespread access to hospitals during a significant rail construction period. The study demonstrates the interaction between hospital and rail accessibility and their moderate influence on housing prices, which is geographically heterogeneous. The study also determines the optimal metric model for assessing geographical interaction based on the significance and stability of the interaction in geographic space. It concludes with a discussion of the findings and social recommendations.

show abstract

Impact of a new subway line on housing values in Daegu, Korea: Distance from existing lines

Cited by 22 publications

References 16 publications

New metro and housing price and rent premiums: A natural experiment in China

New metro and housing price and rent premiums: A natural experiment in China

The External Characteristics and Mechanism of Urban Road Corridors to Agglomeration: Case Study for Guangzhou, China

Do hospital and rail accessibility have a consistent influence on housing prices? Empirical evidence from China

Contact Info

Product

Resources

About