If you build it, they will change: Evaluating the impact of commuter rail stations on real estate values and neighborhood composition in the Rotterdam–The Hague metropolitan area, the Netherlands
Keywords:Urban rail transit, Transit-Oriented Development, Property value, Socio-spatial transformation, Difference-in-Differences Model, RandstadRail, The Netherlands
In many metropolitan regions, transit-oriented developments are built to motivate the use of sustainable travel by promoting urban growth within walking distances of public transport stations. Changes in residential property values are a common way to assess the success of transit-oriented developments. However, studies that focus on property values alone have reported mixed effects. This paper attempts to evaluate the land value impact around commuter rail stations by analyzing the change in property values within the context of the transformation of socio-spatial neighborhood attributes. The study sets out to estimate the effect of Randstad Rail stations using real estate transaction data of residential properties and neighborhood socio-spatial attributes in the Rotterdam–the Hague metropolitan area of the Netherlands covering a period from 1985 to 2018. Adopting a quasi-experimental design, the effect is estimated for properties within different catchment zones around three commuter rail stations using a Difference-in-Differences Model and Multivariate Analysis of Variance. The results demonstrate the overall negative effect of the Randstad Rail on the value of residential properties at a distance equal to or less than 400 meters from the selected rail stations in the range of -18.8% to -11.5%. In contrast, a positive effect is observed for the residential properties located within a radius of 400 to 800 meters from the rail stations, which is estimated to be +15% to +33.2%. The findings also indicate a considerable socio-spatial transformation in the neighborhood composition after the opening of the rail stations in terms of neighborhood population density, land-use density, housing characteristics, and car ownership, which significantly affect the magnitude and direction of the impact.
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