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Understanding spatial variations in the impact of accessibility on land value using geographically weighted regression

Author

Listed:
  • Du, Hongbo

    (Dongguan Institute of Urban Planning and Construction)

  • Mulley, Corinne

    (University of Sydney)

Abstract

This paper aims to understand the spatial variability in house prices and accessibility. The motivation for understanding the connection between accessibility and house prices stems from the increasing attention given in recent years to the potential for funding transport infrastructure by land value capture policies. Establishing whether there is identifiable land value uplift, and further quantifying this uplift, is a prerequisite to sensible discussions on the potential for land value capture. Although there has been substantial related research in the United States, not only have there been fewer studies in the United Kingdom, but these have concentrated on London. London, as a capital city, differs in many respects from other cities. Large conurbations such as Manchester, Sheffield, and Tyne and Wear are more typical of British cities. This study focuses on the Tyne and Wear area, which has an extensive public transport system, with a light rail system—the Tyne and Wear Metro—forming the backbone of the public transport system. The investigation reported in this paper is underpinned by the use of Geographically Weighted Regression (GWR) methodology with property prices as the dependent variable, which in turn is explained by independent variables designed to standardize for household features and spatially defined factors including the transport accessibility of the house location. This methodology allows for estimation of the importance of transport accessibility in determining house prices. The empirical results show that, on average, the internal factors of the property and the socio-economic classification of its location are dominant determinants of property prices, but transport accessibility variables are also significant. However, the local model approach of GWR shows a significant spatially varying relationship between property prices and transport accessibility to be identified. This study contributes to a quantification of the impact of accessibility on house prices. Moreover, the paper demonstrates the application of a relatively new methodology in the transport field that takes account of the spatial nature of the data required in this process.

Suggested Citation

  • Du, Hongbo & Mulley, Corinne, 2012. "Understanding spatial variations in the impact of accessibility on land value using geographically weighted regression," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 5(2), pages 46-59.
  • Handle: RePEc:ris:jtralu:0081
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    References listed on IDEAS

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    Cited by:

    1. Pasha, Obed & Wyczalkowski, Chris & Sohrabian, Dro & Lendel, Iryna, 2020. "Transit effects on poverty, employment, and rent in Cuyahoga County, Ohio," Transport Policy, Elsevier, vol. 88(C), pages 33-41.
    2. Faghih Imani, Ahmadreza & Miller, Eric J. & Saxe, Shoshanna, 2019. "Cycle accessibility and level of traffic stress: A case study of Toronto," Journal of Transport Geography, Elsevier, vol. 80(C).
    3. Pearson, Jonathan & Muldoon-Smith, Kevin & Liu, Henry & Robson, Simon, 2022. "How does the extension of existing transport infrastructure affect land value? A case study of the Tyne and Wear Light Transit Metro system," Land Use Policy, Elsevier, vol. 112(C).
    4. Lin, Jen-Jia & Cheng, Yu-Chun, 2016. "Access to jobs and apartment rents," Journal of Transport Geography, Elsevier, vol. 55(C), pages 121-128.
    5. Gao, Qishuo & Shi, Vivien & Pettit, Christopher & Han, Hoon, 2022. "Property valuation using machine learning algorithms on statistical areas in Greater Sydney, Australia," Land Use Policy, Elsevier, vol. 123(C).
    6. Boisjoly, Geneviève & El-Geneidy, Ahmed M., 2017. "The insider: A planners' perspective on accessibility," Journal of Transport Geography, Elsevier, vol. 64(C), pages 33-43.
    7. Zhong, Haotian & Li, Wei, 2016. "Rail transit investment and property values: An old tale retold," Transport Policy, Elsevier, vol. 51(C), pages 33-48.
    8. Garza, Nestor & Gonzalez, Ivan, 2021. "An urban system assessment of Land Value Capture: The Colombian case," Land Use Policy, Elsevier, vol. 109(C).
    9. Abelson, Peter & Joyeux, Roselyne & Mahuteau, Stephane, 2012. "NILS Working paper no 181. Modelling house prices across Sydney with estimates for access, property size, public transport, urban density and crime," NILS Working Papers 26086, National Institute of Labour Studies.
    10. 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.
    11. Corinne Mulley, 2014. "Accessibility and Residential Land Value Uplift: Identifying Spatial Variations in the Accessibility Impacts of a Bus Transitway," Urban Studies, Urban Studies Journal Limited, vol. 51(8), pages 1707-1724, June.
    12. Amarin Siripanich & Taha Hossein Rashidi & Emily Moylan, 2019. "Interaction of Public Transport Accessibility and Residential Property Values Using Smart Card Data," Sustainability, MDPI, vol. 11(9), pages 1-24, May.
    13. Merkebe Getachew Demissie & Lina Kattan, 2022. "Understanding the temporal and spatial interactions between transit ridership and urban land-use patterns: an exploratory study," Public Transport, Springer, vol. 14(2), pages 385-417, June.
    14. Qianyao Li & Junwu Wang & Judith Callanan & Binbin Lu & Zeng Guo, 2021. "The spatial varying relationship between services of the train network and residential property values in Melbourne, Australia," Urban Studies, Urban Studies Journal Limited, vol. 58(2), pages 335-354, February.
    15. Barzegar, Maryam & Rajabifard, Abbas & Kalantari, Mohsen & Atazadeh, Behnam, 2021. "A framework for spatial analysis in 3D urban land administration – A case study for Victoria, Australia," Land Use Policy, Elsevier, vol. 111(C).
    16. Mulley, Corinne & Tsai, Chi-Hong (Patrick) & Ma, Liang, 2018. "Does residential property price benefit from light rail in Sydney?," Research in Transportation Economics, Elsevier, vol. 67(C), pages 3-10.
    17. Wang, Chih-Hao & Chen, Na, 2017. "A geographically weighted regression approach to investigating the spatially varied built-environment effects on community opportunity," Journal of Transport Geography, Elsevier, vol. 62(C), pages 136-147.

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    More about this item

    Keywords

    Geographically Weighted Regression; housing prices; transport accessibility;
    All these keywords.

    JEL classification:

    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General

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