Using single-family home transactions and commuter rail data from 2014, we estimate hedonic price models using two-stage spatial quantile regression to capture variations across price segments. The results are significant and robust across different model specifications and across the different price segments, but the price effect of proximity to a commuter train station is strongest in lower price segments of the housing market. These price segment effects are also valid for proximity to highways, as well as for several other property attributes. Results also reveal that the largest of the three regional labour markets in our study has a greater effect on prices. Furthermore, the study introduces property-specific neighbourhood data from raster data, showing that population density has a negative impact on property prices at the neighbourhood level while population size has a positive impact at the municipal level.