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Interaction of Public Transport Accessibility and Residential Property Values Using Smart Card Data

Author

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  • Amarin Siripanich

    (Research Centre for Integrated Transport Innnovation (rCIIT), UNSW Sydney, Sydney 2035, Australia)

  • Taha Hossein Rashidi

    (Research Centre for Integrated Transport Innnovation (rCIIT), UNSW Sydney, Sydney 2035, Australia)

  • Emily Moylan

    (Research Centre for Integrated Transport Innnovation (rCIIT), UNSW Sydney, Sydney 2035, Australia
    School of Civil Engineering, University of Sydney, Sydney 2006, Australia)

Abstract

This study examines the relationship between residential property values and accessibility indicators derived from transit smart card data. The use of smart card data to estimate accessibility indicators for explaining the housing market has not yet been explored in the literature. Hence, this paper employs information from Brisbane, Australia’s “go card” and corresponding property data to develop residential property hedonic pricing models using an ordinary least square (OLS) model, a spatial lagged model (SL), a spatial error model (SE), and a geographically weighted regression (GWR). Due to the systematic coincidence between location and price similarities, these spatial econometric models yield superior goodness-of-fit over the OLS model. Using the proposed definition of public transit accessibility in this study, it was found that properties located in well-connected, well-serviced, and accessible locations generally experience premiums in their values. The results indicate that there is value added to the property market from the public investment in public transport services and infrastructure, which supports the adoption of transit funding mechanisms, such as value-capture taxes. Furthermore, the analysis of spatial interactions between transport accessibility and the housing market could be of use to policy makers to ensure a just distribution of capital investment in future infrastructure projects.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:9:p:2709-:d:230669
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    3. Rennert, Lindiwe, 2022. "A meta-analysis of the impact of rail stations on property values: Applying a transit planning lens," Transportation Research Part A: Policy and Practice, Elsevier, vol. 163(C), pages 165-180.
    4. Zolnik, Edmund, 2021. "Geographically weighted regression models of residential property transactions: Walkability and value uplift," Journal of Transport Geography, Elsevier, vol. 92(C).
    5. Sangwan Lee & Liming Wang, 2022. "Intermediate Effect of the COVID-19 Pandemic on Prices of Housing near Light Rail Transit: A Case Study of the Portland Metropolitan Area," Sustainability, MDPI, vol. 14(15), pages 1-17, July.
    6. 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.
    7. Yakubu Suleiman & Adeyemi Ajayi & Sule Abass & Ogunbajo Rukaiyyat, 2020. "The Relationship Between Road Infrastructure Budgetary Expenditures and Commercial Property Investment Returns. Case Study of Fadikpe Area Minna, Nigeria," Baltic Journal of Real Estate Economics and Construction Management, Sciendo, vol. 8(1), pages 187-196, January.

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