The Urban Institute created a multicity panel dataset of land-use reforms using machine learning algorithms to analyze newspaper articles across eight metropolitan regions from 2000 to 2019. The newspaper articles were accessed from Access World News, a comprehensive database of major national and international newspapers. We collected data on reforms related to six regulations: accessory dwelling units, density or floor-area-ratio requirements, minimum lot sizes, minimum setback requirements, mixed residential developments, and nonresidential developments. For each reform, we classify whether it increased or decreased allowed residential density and what time of regulation it fell under.
This dataset was produced with funding from the Smith Richardson Foundation.