Case study of property value transfer attributed to transit: spatial and temporal hedonic price impact of light rail in Minnesota’s Twin Cities

Abstract

Does the proximity of transit increase property values, and can one example apply to another? Using a spatial and temporal hedonic price framework, a study of light rail transit’s impact on residential property values compares the station area property impacts of the Green and Blue lines in Saint Paul and Minneapolis. The study also points to when “value transfer” (used here to describe the comparison and application of property value impacts near transit) is appropriate, and what practitioners should keep in mind to maximize the effectiveness of the exercise. In the case of value transfer for transit, the study finds that intimate local knowledge matters more than special modeling specifications to appropriately capture the impacted properties and transfer the return of investment.

Urban Rail Transit in Bangkok: Chronological Development Review and Impact on Residential Property Value

“…Moreover, the appropriate timing of value capture must be carefully considered. This study found that the impact is not immediately known right before or after the project implementation, as also supported by the findings in [43].…”

“…In addition to the spatial effect, it was also found that the impact was sometimes not stable over time; for example, the purple line impact on the nearby residential development was significant only before the opening of the service. Proper timing of value capture must be carefully considered, as is also supported by the findings in [43].…”

“…The dependent variable, which is the property value, could be the listing price of the property [29,32], the assessed property value [38], or the actual transaction price [21,[39][40][41][42][43]. The price in different years would be adjusted for inflation and other external factors [30].…”

“…The price in different years would be adjusted for inflation and other external factors [30]. The value of the property price may be considered as the total price [24,25,27,28,33,36,37,[43][44][45][46] or the price per unit area, i.e., price per square foot or per square meter of the area [6,20,22,23,26,31,34,35,39,[47][48][49][50][51][52].…”

“…The functional form could be linear [23,25,26,31,33,43,47,48,51,53], semi-log [20,24,[27][28][29][30][34][35][36][37]41,42,44,46,49,50,52], or log-linear (log-log) [6,21,22,39,45,55]. Temporal dimension could be incorporated in the model by adding a dummy variable of year [25,31].…”