This article introduces readers to policy surveillance as a method to create empirical legal datasets, using two examples from the field of housing law. The first is a cross-sectional state-level dataset covering fair housing protections in all 50 states and Washington, D.C., as of August 1, 2017. The second is a cross-sectional city-level dataset covering nuisance property ordinances in the 40 most populous cities in the U.S., as of August 1, 2017. These types of empirical legal datasets identify gaps and trends in policy and facilitate evaluation studies exploring the impact of law on housing outcomes.
Thursday, April 4, 2019