Affiliation:
1. Opendoor Technologies, and Stanford HAI Digital Economy Lab Stanford USA
2. Department of Economics Duke University Durham USA
Abstract
AbstractUsing a novel geospatial panel combined with data from the 2015 American Community Survey (ACS), we investigate the effect of topography—altitude and terrain unevenness—on income segregation at the neighborhood level. Specifically, we perform large‐scale counterfactual simulations by estimating household preferences for topography, altering the topographical profile of each city, and observing the resulting neighborhood sorting outcome. We find that unevenness contributes to the segmentation of markets: in the absence of hilliness, rich and poor households experience greater mixing. Hillier cities are more income‐segregated because of their unevenness; the opposite is true for flatter cities.