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The Impact of Rail Transport on Real Estate Prices

Author

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  • Ghebreegziabiher Debrezion
  • Eric Pels
  • Piet Rietveld

    ()

Abstract

A hedonic pricing model is estimated based on sales data from three metropolitan areas in the Netherlands (Amsterdam, Rotterdam and Enschede) to analyse the effect of railway accessibility on house prices. Railway accessibility is measured by both the distance to a railway station and an index of quality of railway services provided at the station. Two railway station considerations were taken: the nearest railway station and the most frequently chosen railway station. Correcting for a wide range of other determinants, the model based on the most frequently chosen station outperforms the model based on the nearest railway station in estimating the effect of railway accessibility. The dissimilarity between the results of the two models increases with the increase in the urbanisation level of the metropolitan area.

Suggested Citation

  • Ghebreegziabiher Debrezion & Eric Pels & Piet Rietveld, 2011. "The Impact of Rail Transport on Real Estate Prices," Urban Studies, Urban Studies Journal Limited, vol. 48(5), pages 997-1015, April.
  • Handle: RePEc:sae:urbstu:v:48:y:2011:i:5:p:997-1015
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    Cited by:

    1. Karolien De Bruyne & Jan Van Hove, 2013. "Explaining the spatial variation in housing prices: an economic geography approach," Applied Economics, Taylor & Francis Journals, vol. 45(13), pages 1673-1689, May.
    2. Alicia N. Rambaldi & Cameron S. Fletcher & Kerry Collins & Ryan R.J. McAllister, 2013. "Housing Shadow Prices in an Inundation-prone Suburb," Urban Studies, Urban Studies Journal Limited, vol. 50(9), pages 1889-1905, July.
    3. Wenjie Wu, 2012. "Does Public Investment Spur the Land Market?: Evidence from Transport Improvement in Beijing," SERC Discussion Papers 0116, Spatial Economics Research Centre, LSE.
    4. Mitra, Suman K. & Saphores, Jean-Daniel M., 2016. "The value of transportation accessibility in a least developed country city – The case of Rajshahi City, Bangladesh," Transportation Research Part A: Policy and Practice, Elsevier, vol. 89(C), pages 184-200.
    5. Chen, Zhenhua & Xue, Junbo & Rose, Adam Z. & Haynes, Kingsley E., 2016. "The impact of high-speed rail investment on economic and environmental change in China: A dynamic CGE analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 232-245.
    6. Dubé, Jean & Legros, Diègo & Thériault, Marius & Des Rosiers, François, 2014. "A spatial Difference-in-Differences estimator to evaluate the effect of change in public mass transit systems on house prices," Transportation Research Part B: Methodological, Elsevier, vol. 64(C), pages 24-40.
    7. repec:eee:regeco:v:67:y:2017:i:c:p:64-77 is not listed on IDEAS
    8. repec:gam:jsusta:v:10:y:2018:i:3:p:593-:d:133452 is not listed on IDEAS
    9. Wang, Yiming & Feng, Suwei & Deng, Zhongwei & Cheng, Shuangyu, 2016. "Transit premium and rent segmentation: A spatial quantile hedonic analysis of Shanghai Metro," Transport Policy, Elsevier, vol. 51(C), pages 61-69.
    10. Dubé, Jean & Thériault, Marius & Des Rosiers, François, 2013. "Commuter rail accessibility and house values: The case of the Montreal South Shore, Canada, 1992–2009," Transportation Research Part A: Policy and Practice, Elsevier, vol. 54(C), pages 49-66.

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