Economic benefits are sometimes used to justify transport investments. Such was the case with the River Line of southern New Jersey, USA, which broke ground in 2000 and began operating in 2004. Recently, the line has been performing near full capacity and there is evidence that it has spurred development. Disaggregate data on owned-home appreciation are used to investigate the initial economic impacts of the line, looking carefully at non-linearity in the appreciation gradient, differential effects of station ridership and parking, redistribution of property appreciation gains and differences by property and neighbourhood type. At this time, the net impact of the line on the owned housing market is neutral to slightly negative. While lower-income census tracts and smaller houses seem to appreciate near the station, this may be a value transfer from farther-away properties not favoured with access. Few studies have previously looked for such effects.

Abstract. This paper analyses the impact of the Hudson-Bergen Light Rail (HBLR) on residential property prices. Unlike similar studies that use a hedonic model with cross-sectional data, this one uses repeat-sales data of properties that sold at least twice between 1991 and 2009. It shows how proximity to the nearest HBLR station, relative accessibility gains across stations, and anticipation of the commencement date of the HBLR station influence home price change. Our results show that properties near the two commuting stations farthest from the revitalized central business district experienced high appreciation. It also reveals that different accessibility gains across areas were produced based on the availability of existing public transportation options. Using a negative-exponential gradient, we find that these higher appreciation rates tended to dissipate about 1/4 mile (402 m) from stations. This supports that properties around urban commuting stations enjoy higher marginal benefits through improved transit accessibility and reduced transportation costs as Alonso's model predicts.JEL classification: R14, R21, R42

No abstract

No abstract