The Impact of Railway Stations on Residential and Commercial Property Value: A Meta-analysis

By G. Debrezion, Eric Pels, Piet Rietveld. 2007

734 citations recorded by the source corpus.

Railway stations function as nodes in transport networks and places in an urban environment. They have accessibility and environmental impacts, which contribute to property value. The literature on the effects of railway stations on property value is mixed in its finding in respect to the impact magnitude and direction, ranging from a negative to an insignificant or a positive impact. This paper attempts to explain the variation in the findings by meta-analytical procedures. Generally the variations are attributed to the nature of data, particular spatial characteristics, temporal effects and methodology. Railway station proximity is addressed from two spatial considerations: a local station effect measuring the effect for properties with in 1/4 mile range and a global station effect measuring the effect of coming 250 m closer to the station. We find that the effect of railway stations on commercial property value mainly takes place at short distances. Commercial properties within 1/4 mile rang are 12.2% more expensive than residential properties. Where the price gap between the railway station zone and the rest is about 4.2% for the average residence, it is about 16.4% for the average commercial property. At longer distances the effect on residential property values dominate. We find that for every 250 m a residence is located closer to a station its price is 2.3% higher than commercial properties. Commuter railway stations have a consistently higher positive impact on the property value compared to light and heavy railway/Metro stations. The inclusion of other accessibility variables (such as highways) in the models reduces the level of reported railway station impact.

Subfields: Building and Construction, Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/b71e405cf455eb19f021ab99955d83dcf1123a60

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Citations in the corpus

A HOUSE PRICE VALUATION BASED ON THE RANDOM FOREST APPROACH: THE MASS APPRAISAL OF RESIDENTIAL PROPERTY IN SOUTH KOREA (2020, background): “Dubin and Sung (1990) conducted a non-nested test to determine which set of neighborhood variables most accurately explained the variation in housing prices. To reveal the relationship between accessibility to a CBD and house prices, various measures have been proposed (Adair, McGreal, Smyth, Cooper”
The Use (and Abuse) of Meta-Analysis in Environmental and Natural Resource Economics: An Assessment (2009, neutral): “Previous analyses in environmental economics that calculate FES weighted-means are Daniel et al. (2007), Debrezion et al. (2007), and Nelson (2004).”
Forty years of modelling rapid transit’s land value uplift in North America: moving beyond the tip of the iceberg (2016, methodology): “the present paper should follow Debrezion et al. (2007) and Mohammad et al.”
Supply, Demand and the Value of Green Buildings (2014, background): “The physical distances for tube stations, local roads and motorways have in the past had inconsistent impacts on commercial rents and prices (Debrezion et al., 2007), but may have an economically significant impact on prices for London.”
A meta-analysis of the impact of rail projects on land and property values (2013, background): “Debrezion et al. (2007) considered a larger set of study-design factors in a meta-analysis model; including type of property, type of public transport system, type of empirical model, time period of the analysis, accessibility to different transport modes, and demographic variables.”