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Hedonic modeling of commercial property values: distance decay from the links and nodes of rail and highway infrastructure

Kihwan Seo (), Deborah Salon (), Michael Kuby () and Aaron Golub ()
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Kihwan Seo: Korea Research Institute for Human Settlements
Deborah Salon: Arizona State University
Michael Kuby: Arizona State University
Aaron Golub: Portland State University

Transportation, 2019, vol. 46, issue 3, 859-882

Abstract: Abstract This study investigates the impacts of positive and negative externalities of highways and light rail on commercial property values in Phoenix, Arizona. We hypothesize that the positive externality (i.e., accessibility) of highway and light rail accrues at exits and stations, whereas nodes and links of highways and light rail emanate negative effects. Positive and negative effects decay with increasing distance and are captured by multiple distance bands. Hypotheses are tested using a spatial error regression model. Results show that commercial property values are positively and significantly associated with the accessibility benefits of transport nodes. The distance-band coefficients form a typical distance decay curve for both modes with no detectable disamenity donut effect immediately around the nodes. Unexpectedly, impacts of light rail stations extend farther than those of highway exits. Only the links of light rail are negatively associated with property values, as hypothesized. When the sample is subdivided by type of commercial property, the magnitude and distance extent of impacts are surprisingly consistent, with light rail stations having stronger impacts than highway exits on all three classes of commercial property: industrial, office, and retail and service. Rail links have a significant negative relationship with price for all three types of commercial property, but highways have a significant negative relationship only with industrial properties.

Keywords: Highway; Light rail; Spatial error model; Node; Link; Commercial property value (search for similar items in EconPapers)
Date: 2019
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