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Estimating land value uplift around light rail transit stations in Greater Kuala Lumpur: An empirical study based on geographically weighted regression (GWR)

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  • Dziauddin, Mohd Faris

Abstract

Introducing a rail transit system into an urban region is expected to increase land values, and subsequently, residential property values. Despite this general belief, little is known about the spatial distributional effects of land value uplift. Thus, the goal of this paper is to provide new insights on how proximity to light rail transit stations may affect residential property values in Greater Kuala Lumpur, Malaysia using geographically weighted regression (GWR). The results provide information on spatial variations in the effects of a light rail transit system on residential property values. This study utilises GWR to account for spatial heterogeneity and spatial dependence. The results suggest that residential property values benefit from the provision of a light rail transit system but with considerable spatial variation over a geographical area. Evidently, proximity to the nearest light rail transit station gives positive premiums of up to 8% for a majority of properties located in lower-middle and upper-middle income neighbourhoods such as Wangsa Maju, Setapak, Keramat, Setiawangsa, Ampang and Sentul. In contrast, the impact of proximity to the nearest light rail transit station for properties located in high-income neighbourhoods such as Petaling Jaya was found to be non-significant. These findings can assist policy makers to better understand how properties around light rail transit stations accrue benefits. However, since the benefit of a light rail transit system on nearby properties varies over a geographical area (and where a positive premium can swing from positive to negative depending on the area), it may be difficult for policy makers to impose a single-value tax if there is a land value capture policy to be considered for implementation.

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  • Dziauddin, Mohd Faris, 2019. "Estimating land value uplift around light rail transit stations in Greater Kuala Lumpur: An empirical study based on geographically weighted regression (GWR)," Research in Transportation Economics, Elsevier, vol. 74(C), pages 10-20.
  • Handle: RePEc:eee:retrec:v:74:y:2019:i:c:p:10-20
    DOI: 10.1016/j.retrec.2019.01.003
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    Cited by:

    1. Rémy Le Boennec & Julie Bulteau & Thierry Feuillet, 2022. "The role of commuter rail accessibility in the formation of residential land values: exploring spatial heterogeneity in peri-urban and remote areas," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 69(1), pages 163-186, August.
    2. Jonas Eliasson & Fredrik Kopsch & Svante Mandell & Mats Wilhelmsson, 2020. "Transport Mode and the Value of Accessibility–A Potential Input for Sustainable Investment Analysis," Sustainability, MDPI, vol. 12(5), pages 1-14, March.
    3. Lilis Laome & I Nyoman Budiantara & Vita Ratnasari, 2022. "Estimation Curve of Mixed Spline Truncated and Fourier Series Estimator for Geographically Weighted Nonparametric Regression," Mathematics, MDPI, vol. 11(1), pages 1-13, December.
    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. Yang, Linchuan & Chau, K.W. & Wang, Xu, 2019. "Are low-end housing purchasers more willing to pay for access to basic public services? Evidence from China," Research in Transportation Economics, Elsevier, vol. 76(C).
    6. Pengyu Ren & Zhaoji Li & Weiguang Cai & Lina Ran & Lei Gan, 2021. "Heterogeneity Analysis of Urban Rail Transit on Housing with Different Price Levels: A Case Study of Chengdu, China," Land, MDPI, vol. 10(12), pages 1-15, December.
    7. 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).
    8. Suchi Kapoor Malhotra & Howard White & Nina Ashley O. Dela Cruz & Ashrita Saran & John Eyers & Denny John & Ella Beveridge & Nina Blöndal, 2021. "Studies of the effectiveness of transport sector interventions in low‐ and middle‐income countries: An evidence and gap map," Campbell Systematic Reviews, John Wiley & Sons, vol. 17(4), December.
    9. Maysen Yen, 2024. "Does Rapid Transit and Light Rail Infrastructure Improve Labor Market Outcomes?," Working Papers 24-22, Center for Economic Studies, U.S. Census Bureau.
    10. Erez Buda & Dani Broitman & Daniel Czamanski, 2021. "Urban Structure in Troubled Times: The Evolution of Principal and Secondary Core/Periphery Gaps through the Prism of Residential Land Values," Sustainability, MDPI, vol. 13(10), pages 1-12, May.
    11. Doan, Quang Cuong, 2023. "Determining the optimal land valuation model: A case study of Hanoi, Vietnam," Land Use Policy, Elsevier, vol. 127(C).
    12. Zijia Wang & Lei Cheng & Yongxing Li & Zhiqiang Li, 2020. "Spatiotemporal Characteristics of Bike-Sharing Usage around Rail Transit Stations: Evidence from Beijing, China," Sustainability, MDPI, vol. 12(4), pages 1-19, February.
    13. Zhang, Min, 2023. "Value uplift from transit investment-Property value or land value? A case study of the Gold Coast light rail system in Australia," Transport Policy, Elsevier, vol. 132(C), pages 88-98.
    14. Ke Zhang & Hao Sun & Xiangyu Li, 2022. "Aging Population Spatial Distribution Discrepancy and Impacting Factor," Sustainability, MDPI, vol. 14(15), pages 1-22, August.
    15. Li, Jianyi & Huang, Hao, 2020. "Effects of transit-oriented development (TOD) on housing prices: A case study in Wuhan, China," Research in Transportation Economics, Elsevier, vol. 80(C).
    16. Bohman, Helena, 2021. "Same, same but different? Neighbourhood effects of accessibility on housing prices," Transport Policy, Elsevier, vol. 107(C), pages 52-60.

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    More about this item

    Keywords

    Geographically weighted regression (GWR); Hedonic pricing model; Land value uplift; Light rail transit; Land value capture; Greater Kuala Lumpur;
    All these keywords.

    JEL classification:

    • R1 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics
    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location
    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics

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