Affordable Housing Law and Policy in an Era of Big Data

Abstract

Every year, federal, state, and local governments invest more than $50 billion to provide housing for people who cannot otherwise afford shelter and policymakers also make a variety of choices that impact the landscape of affordable housing. These investments and policies can make a profound difference, but are too often undertaken with only the vaguest, visceral sense of consequences beyond the bare facts of putting roofs over people's heads. Affordable housing policy, however, is beginning to experience a shift in perspective. In recent years, researchers and policymakers have begun to evaluate the results of policy interventions for people in subsidized housing on measures such as income, educational achievement, physical and mental health, and even subjective wellbeing. This emphasis on outcome measures reflects a broader embrace of the use of data for decision making by managers and policymakers across the private and public sectors. The ability to collect data in a more rigorous and systematic way and the development of tools to make that information actionable is beginning to change a range of decisional processes. This Essay examines a range of new data tools that are starting to sharpen policy in the realm of affordable housing, creating a positive feedback loop in which agencies provide data to grantees to shape how they implement policy, gather more information about outcomes, and then share all of that information with other regulators or advocates to help advance other legal mandates, notably around enforcement and private rights of action. From these examples, the Essay offers some observations about what this reveals about the role of law in generating data and deploying data.