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Public Assistance and Neighborhood Choice

Paper Session

Saturday, Jan. 6, 2018 8:00 AM - 10:00 AM

Loews Philadelphia, Washington C
Hosted By: American Real Estate and Urban Economics Association
  • Chair: Ingrid Gould Ellen, New York University

Neighbors and Networks: The Role of Social Interactions on the Residential Choices of Housing Choice Voucher Holders

Michael Suher
,
New York University
Ingrid Gould Ellen
,
New York University
Gerard Torrats-Espinosa
,
New York University

Abstract

The housing choice voucher program aims to reduce housing cost burdens but is also intended to enable recipients to move to a broader diversity of neighborhoods. Evidence suggests voucher recipients still end up in neighborhoods with relatively high poverty rates and low performing schools. These constrained neighborhood choices can in part be attributed to rent levels and landlord discrimination. In this paper, we consider an additional explanation: the role of information and social influence in determining the effective set of potential housing choices. Using a strategy based on proximity of households in origin tracts, we find evidence consistent with social influence effects being present in the neighborhood choices of voucher holders. Pairs of households living within the same or adjacent buildings are significantly more likely to relocate to the same neighborhood as each other than are more distant households within the same origin neighborhood. Further, we show that voucher holders whose relocation decisions had a greater potential to be socially influenced end up on average in higher poverty neighborhoods in both absolute terms and relative to non-influenced voucher holders from their same origin tract.

Neighborhood Choices, Neighborhood Effects and Housing Vouchers

Morris Davis
,
Rutgers University
Jesse Gregory
,
University of Wisconsin
Daniel Hartley
,
Federal Reserve Bank of Cleveland
Kegon Tan
,
University of Wisconsin

Abstract

We study how households choose neighborhoods, how neighborhoods affect child ability, and how housing vouchers influence neighborhood choices and child outcomes. We use two new panel data sets with tract-level detail for Los Angeles county to estimate a dynamic model of optimal tract-level location choice for renting households and, separately, the impact of living in a given tract on child test scores (which we call “child ability” throughout). We simulate optimal location choices and changes in child ability of the poorest households in our sample under various housing-voucher policies. We demonstrate that a Moving-to-Opportunity type voucher, in which people residing in high poverty tracts are given a voucher to move to low-poverty tracts, does not affect child ability as households use the voucher to move to relatively inexpensive, low-impact neighborhoods. When vouchers are restricted such that they can only be applied in tracts with large effects on children, we demonstrate the total benefits of any voucher less than $700 per month exceed the costs and the voucher that maximizes total social surplus is $300 per month.

Waiting for Affordable Housing

Chamna Yoon
,
Sungkyunkwan University
Holger Sieg
,
University of Pennsylvania

Abstract

We develop a new dynamic equilibrium model of housing markets for low- and
moderate-income households, which is consistent with the key supply restrictions and search frictions that arise in rental markets for public and affordable housing. We estimate the model using data collected by the New York Housing Vacancy Survey in 2011. We find that having access to rent stabilized or affordable housing increases household welfare by up to $55,000. Our policy simulations suggest that increasing the supply of affordable housing by ten percent significantly improves the welfare of all renters in the city. As a consequence our model provides a compelling explanation why affordable housing policies are popular at the ballot box with the vast majority of urban renters.

Long-Run Outcomes of HOPE VI Public Housing Demolitions for Children

Henry Pollakowski
,
Harvard University
John Haltiwanger
,
University of Maryland
Mark Kutzbach
,
Federal Deposit Insurance Corporation
Giordano Palloni
,
International Food Policy Research Institute
Matthew Staiger
,
University of Maryland
Daniel Weinberg
,
U.S. Census Bureau

Abstract

We combine administrative data on subsidized housing participation and adult earnings with information on HOPE VI funded public housing project demolitions to test whether demolitions (and the consequent forced moves) affect the long-term earnings of resident children. The data enable us to identify children who are between the ages of 10 and 18 at the time of a demolition from 160 HOPE VI projects and over 5,000 non-HOPE VI projects, and to observe how their subsidized housing participation, neighborhood characteristics, and earnings evolve over time. Since HOPE VI demolitions are drawn from the “worst” public housing projects, the aim of our methodology is to use data for a large number of other public housing projects to control for differences between the HOPE VI demolitions and the wider set of public housing projects. We use stratification with regression (Rosenbaum and Rubin, 1983, 1984) to classify projects into strata based on a project-level propensity score, estimate within-stratum treatment effects using individual-level ordinary least squares regressions, and aggregate up the stratum-level results to produce an estimate of the overall treatment effect on the treated. The results suggest that, on average, children in HOPE VI projects earn nearly 36% more at age 26 relative to children in comparable non-demolished projects. We exploit the heterogeneity in HOPE VI projects and in demographic characteristics to explore how the treatment effect differs across diverse contexts.
Discussant(s)
Amanda Ross
,
University of Alabama
Eric Chyn
,
University of Virginia
Juan Pantano
,
University of Chicago
Katherine O'Regan
,
New York University
JEL Classifications
  • R2 - Household Analysis
  • C3 - Multiple or Simultaneous Equation Models; Multiple Variables