The (Literally) Steepest Slope: Spatial, Temporal, and Elevation Variance Gradients in Urban Spatial Modelling
This paper presents an analysis of elevation gradient and temporal future-station effects in urban real estate markets. Using an extraordinary dataset from the Hong Kong publicly-constructed housing sector, we find enormous housing price effects caused by levels of terrain incline between apartments and subway stations. Ceteris paribus, two similar apartments with closest metro stations of the same walking distance may sell at a difference of up to 20% because of differences in the apartment-station slope alone. Anticipatory effects are similarly robust: apartment buyers regard a future, closer metro station as being 60% present when making purchases two years prior to its opening.
Economic Research Initiatives at Duke (ERID)