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Determining Transit’s Impact on Seoul Commercial Land Values: An Application of Spatial Econometrics

Author

Listed:
  • Jin Kim

    (Texas A&M University, Hensel Dr. #Y2C, College Station, TX 77840-3137)

  • Ming Zhang

    (University of Texas at Austin, University Station B7500, Austin, TX 78712-0222)

Abstract

Literature regarding transit’s impact on land values reports mixed results concerning the economic benefits of accessibility to subway stations, specifically regarding commercial properties. After examining 731 commercial land values in Seoul, Korea, this study suggests a possible explanation for the mixed results: transit’s discrimination impact on land values by location in a built-up urban area. The regression coefficient for distance to station in the central business district is the highest, the subcenters are next, and other areas are lowest – apparently a strong correlation with higher centrality and development densities of submarkets. Also, the inclusion of spatial lag and error term variables greatly improves the goodness of fit of the regression equations lowering the spatial autocorrelation in the ordinary least squares residuals as well as reduces overestimation of value premiums in association with rail transit stations, which enables a regression model to produce a more accurate and efficient estimator for transit’s impact on commercial land values.

Suggested Citation

  • Jin Kim & Ming Zhang, 2005. "Determining Transit’s Impact on Seoul Commercial Land Values: An Application of Spatial Econometrics," International Real Estate Review, Global Social Science Institute, vol. 8(1), pages 1-26.
  • Handle: RePEc:ire:issued:v:08:n:01:2005:p:1-26
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    Cited by:

    1. Luhui Qi & Liqi Jia & Yubin Luo & Yuanyi Chen & Minggang Peng, 2022. "The External Characteristics and Mechanism of Urban Road Corridors to Agglomeration: Case Study for Guangzhou, China," Land, MDPI, vol. 11(7), pages 1-17, July.
    2. Han-Jang No & Dai-Won Kim & Jung-Suk Yu, 2017. "Do Reserve Prices Yield Reference Price Effects in Korean Court Auctions of Residential Real Estate?," International Real Estate Review, Global Social Science Institute, vol. 20(1), pages 75-104.
    3. Usman Hamza & Lizam Mohd & Adekunle Muhammad Usman, 2020. "Property Price Modelling, Market Segmentation and Submarket Classifications: A Review," Real Estate Management and Valuation, Sciendo, vol. 28(3), pages 24-35, September.
    4. Huang, Zhonghua & Du, Xuejun, 2021. "How does high-speed rail affect land value? Evidence from China," Land Use Policy, Elsevier, vol. 101(C).
    5. Shengxiao Li & Luoye Chen & Pengjun Zhao, 2019. "The impact of metro services on housing prices: a case study from Beijing," Transportation, Springer, vol. 46(4), pages 1291-1317, August.
    6. Zhijunjie Zhai & Minfeng Yao & Yueying Li, 2022. "Evaluation of Land-Use Layout of the Rail Station Area Based on the Difference in Noise Sensitivity to Rail Transit, Taking a Suburb of Tokyo as an Example," Sustainability, MDPI, vol. 14(13), pages 1-23, June.
    7. Seungwoo Chin & Matthew E. Kahn & Hyungsik Roger Moon, 2020. "Estimating the Gains from New Rail Transit Investment: A Machine Learning Tree Approach," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 48(3), pages 886-914, September.
    8. Saad AlQuhtani & Ardeshir Anjomani, 2021. "Do Rail Transit Stations Affect the Population Density Changes around Them? The Case of Dallas-Fort Worth Metropolitan Area," Sustainability, MDPI, vol. 13(6), pages 1-21, March.
    9. Ahn, Kwangwon & Jang, Hanwool & Song, Yena, 2020. "Economic impacts of being close to subway networks: A case study of Korean metropolitan areas," Research in Transportation Economics, Elsevier, vol. 83(C).
    10. Ayesha Khalid & Ali Iqtedar Mirza, 2020. "Monitoring the Spatial Structure of land values in Lahore Metropolitan area," International Journal of Innovations in Science & Technology, 50sea, vol. 2(3), pages 80-94, September.
    11. Xu, Tao & Zhang, Ming & Aditjandra, Paulus T., 2016. "The impact of urban rail transit on commercial property value: New evidence from Wuhan, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 223-235.
    12. Rodríguez, Daniel A. & Mojica, Carlos H., 2009. "Capitalization of BRT network expansions effects into prices of non-expansion areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(5), pages 560-571, June.
    13. Cohen, Jeffrey P. & Brown, Mike, 2017. "Does a new rail rapid transit line announcement affect various commercial property prices differently?," Regional Science and Urban Economics, Elsevier, vol. 66(C), pages 74-90.
    14. AlQuhtani, Saad & Anjomani, Ardeshir, 2019. "Do rail transit stations affect housing value changes? The Dallas Fort-Worth metropolitan area case and implications," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    15. Yuchen Qin & Yikang Zhang & Minfeng Yao & Qiwei Chen, 2023. "How to Measure the Impact of Walking Accessibility of Suburban Rail Station Catchment Areas on the Commercial Premium Benefits of Joint Development," Sustainability, MDPI, vol. 15(6), pages 1-29, March.
    16. Qingchun Liu & Peixiong Zhao & Yan Xiao & Xin Zhou & Jun Yang, 2022. "Walking Accessibility to the Bus Stop: Does It Affect Residential Rents? The Case of Jinan, China," Land, MDPI, vol. 11(6), pages 1-17, June.
    17. Azad, Mojdeh & Abdelqader, Dua & Taboada, Luis M. & Cherry, Christopher R., 2021. "Walk-to-transit demand estimation methods applied at the parcel level to improve pedestrian infrastructure investment," Journal of Transport Geography, Elsevier, vol. 92(C).
    18. Zhang, Dapeng & Wang, Xiaokun (Cara), 2014. "Transit ridership estimation with network Kriging: a case study of Second Avenue Subway, NYC," Journal of Transport Geography, Elsevier, vol. 41(C), pages 107-115.
    19. Singhal Shaleen & Tyagi Yogesh, 2021. "Analyzing the Influence of Metro Stations on Commercial Property Values in Delhi: A Hedonic Approach," Real Estate Management and Valuation, Sciendo, vol. 29(4), pages 10-22, December.

    More about this item

    Keywords

    transit impact; transit-oriented development (TOD); land value; spatial autocorrelation; geographic information systems (GIS); spline regression;
    All these keywords.

    JEL classification:

    • L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services

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