Bolstering the housing safety net: The promise of automatic stabilizers



While social insurance programs help to buffer the effects of economic downturns, these programs have many gaps in coverage. In the face of income losses and unexpected expenses, households are not able to quickly adjust housing consumption. Homeowners cannot immediately sell homes and face large transaction costs in refinancing and modifying mortgages. While renters are more mobile, they typically hold leases that commit them to paying rent over a full year. Furthermore, low-income housing production programs in the United States tend to be pro-cyclical.

This paper proposes a set of policy reforms that would add automatic stabilizers to federal housing programs, helping both renters and homeowners stay in their homes during economic downturns and ensuring continued support for the construction and renovation of affordable housing. Specifically, we propose creating new emergency rental assistance accounts for low-income households to address the income and financial shocks that can trigger housing instability; an automatic homeownership stabilization program, consisting of a three-month forbearance period for vulnerable mortgage borrowers in response to a triggering event of elevated local unemployment; and a permanent tax credit exchange program that allows states to exchange tax credits for direct subsidies at a fiscally neutral price when demand from tax credit investors falls. We discuss several design and implementation questions, and acknowledge limitations. Nevertheless, and despite these limitations, these proposals would go a long way toward stabilizing households and housing markets during the next crisis.


  • Acknowledgements and disclosures

    We would like to thank Kristen Broady, Wendy Edelberg, and other participants in The Hamilton Project’s author conference for thoughtful comments on our paper. We also thank Mark Willis, Kathy O’Regan, Mark Shelburne, and Stockton Williams for helpful insights and suggestions. Finally, we thank Jorge Luis Tello Garza for excellent research assistance.