Using Natural Language Processing to Construct a National Zoning and Land Use Database.

In the United States, zoning and land use policies have been linked to high housing costs and residential segregation. Yet almost all zoning and land use data come from a handful of cross-sectional surveys, which are costly, time intensive, subject to low response rates and measurement error and are quickly dated. As an alternative, we construct the National Zoning and Land Use Database using natural language processing techniques on publicly available administrative data.