Targeting In-Kind Transfers through Market Design: A Revealed Preference Analysis of Public Housing Allocation

In-kind transfer programs aim to provide valuable resources to beneficiaries while targeting those who most need assistance. This problem is particularly challenging for public housing authorities (PHAs), which allocate apartments to applicants who may differ in their outside options as well as their preferred apartment types. PHAs in the U.S. differ widely in the priority systems they use and how much choice they give potential tenants over where to live. This paper evaluates how these choice and priority systems affect two competing objectives: efficiency and redistribution. I use data on the submitted choices of public housing applicants to estimate a structural model of preferences for public housing in Cambridge, MA. I find substantial heterogeneity in applicants’ preferred housing developments and in their values of obtaining assistance. Counterfactual simulations suggest that the range of mechanisms used by PHAs involves a large trade-off between efficiency and redistribution. When applicants are allowed to choose where they live, tenants enjoy welfare gains equivalent to cash transfers of more than $6,500 per year. Removing choice would house applicants with worse outside options but provide low match quality, causing cost-adjusted welfare gains to fall by 30 percent. Prioritizing low-income applicants while allowing choice would improve targeting without lowering match quality. While several combinations of choice and priority are on the frontier of efficiency and redistribution, some commonly used mechanisms, such as prioritizing higher-income applicants without allowing choice, are never optimal. ∗I am very grateful to Nikhil Agarwal, Parag Pathak, Michael Whinston, and Amy Finkelstein for invaluable guidance and support. This paper benefited from feedback from Zarek Brot-Goldberg, Alonso Bucarey, Sydnee Caldwell, Glenn Ellison, Chishio Furukawa, Andrey Fradkin, Colin Gray, Arda Gitmez, Ingrid Gould Ellen, Jonathan Gruber, Ray Kluender, Jacob Leshno, Benjamin Marx, Pooya Molavi, Anders Munk-Nielsen, Scott Nelson, Alan Olivi, Christina Patterson, Otis Reid, Nancy Rose, Peng Shi, Michael Stepner, Neil Thakral, Heidi Williams, and Ariel Zucker, as well as seminar participants at the MIT Industrial Organization and Public Finance lunches. The Cambridge Housing Authority generously provided the applicant and tenant data used in this paper, with special thanks to Tara Aubuchon, Tito Evora, Michael Johnston, Jay Leslie, Hannah Lodi, and John Ziniewicz. All analysis and views expressed in this paper are my own and do not represent the views of the Cambridge Housing Authority. †MIT Economics. Email: dwalding@mit.edu. All mistakes are my own.

[1]  D. McFadden Conditional logit analysis of qualitative choice behavior , 1972 .

[2]  Daniel A. Ackerberg A new use of importance sampling to reduce computational burden in simulation estimation , 2001 .

[3]  F. Bourguignon On the Measurement of Inequality , 2003 .

[4]  Daniel I. Tannenbaum,et al.  Does Eviction Cause Poverty? Quasi-Experimental Evidence from Cook County, Il , 2019, SSRN Electronic Journal.

[5]  J. Ludwig,et al.  Low-Income Housing Policy , 2015 .

[6]  N. Agarwal An Empirical Model of the Medical Match , 2014, The American economic review.

[7]  Edgar O. Olsen,et al.  The Cost-Effectiveness of Alternative Methods of Delivering Housing Subsidies , 2000 .

[8]  Yusuke Narita Match or Mismatch: Learning and Inertia in School Choice , 2016 .

[9]  Fredrik W. Andersson,et al.  Childhood Housing and Adult Earnings: A Between-Siblings Analysis of Housing Vouchers and Public Housing , 2013 .

[10]  Beyond Truth-Telling: Preference Estimation with Centralized School Choice and College Admissions , 2019 .

[11]  Yinghua He,et al.  Beyond Truth-Telling: Preference Estimation with Centralized School Choice and College Admissions , 2019, American Economic Review.

[12]  Matthew Desmond,et al.  Neighborhood and Network Disadvantage among Urban Renters , 2015 .

[13]  A. Atkinson,et al.  The design of tax structure: Direct versus indirect taxation , 1976 .

[14]  D. Pollard,et al.  Simulation and the Asymptotics of Optimization Estimators , 1989 .

[15]  M. Deshpande,et al.  Who is Screened Out? Application Costs and the Targeting of Disability Programs , 2017, American Economic Journal: Economic Policy.

[16]  Holger Sieg,et al.  Estimating a model of excess demand for public housing , 2013 .

[17]  Erzo F. P. Luttmer,et al.  The Misallocation of Housing Under Rent Control , 1997 .

[18]  W. Dijk,et al.  The socio-economic consequences of housing assistance , 2018 .

[19]  R. Zeckhauser,et al.  Targeting Transfers through Restrictions on Recipients , 1982 .

[20]  Jacob D. Leshno Dynamic Matching in Overloaded Waiting Lists , 2019, American Economic Review.

[21]  Raj Chetty,et al.  The Effects of Exposure to Better Neighborhoods on Children: New Evidence from the Moving to Opportunity Experiment , 2015, The American economic review.

[22]  Robert Joseph Taylor,et al.  All Our Kin: Strategies for Survival in a Black Community , 2000 .

[23]  Matthew J. Notowidigdo,et al.  Take-Up and Targeting: Experimental Evidence from Snap , 2018, The Quarterly Journal of Economics.

[24]  D. McFadden A Method of Simulated Moments for Estimation of Discrete Response Models Without Numerical Integration , 1989 .

[25]  Francis Bloch,et al.  Dynamic Assignment of Objects to Queuing Agents , 2017 .

[26]  Itay P. Fainmesser,et al.  The Public-Housing Allocation Problem : Theory and Evidence from Pittsburgh , 2016 .

[27]  Holger Sieg,et al.  Waiting for Affordable Housing in New York City , 2019, Quantitative Economics.

[28]  Lawrence F. Katz,et al.  Long-Term Neighborhood Effects on Low-Income Families: Evidence from Moving to Opportunity , 2013 .

[29]  Steven Berry,et al.  Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car Market , 1998, Journal of Political Economy.

[30]  M. D. Reviewed Disposable Ties and the Urban Poor Author ( s ) : , 2012 .

[31]  Ethan M. J. Lieber,et al.  Targeting with In-Kind Transfers: Evidence from Medicaid Home Care. , 2019, The American economic review.

[32]  Justine S. Hastings,et al.  Heterogeneous Preferences and the Efficacy of Public School Choice , 2008 .

[33]  J. V. Ommeren,et al.  Households' willingness to pay for public housing , 2016 .

[34]  Parag A. Pathak,et al.  The New York City High School Match , 2005 .

[35]  George A. Akerlof American Economic Association The Economics of " Tagging " as Applied to the Optimal Income Tax , Welfare Programs , and Manpower Planning , 2007 .

[36]  Nick Arnosti,et al.  Design of Lotteries and Waitlists for Affordable Housing Allocation , 2017 .

[37]  J. Ludwig,et al.  The Effects of Housing Assistance on Labor Supply: Evidence from a Voucher Lottery , 2008 .

[38]  Thierry Magnac,et al.  Gaming the Boston School Choice Mechanism in Beijing , 2012 .