Dispossessed
The Size and Census Coverage of the U.S. Homeless Population
Bruce Meyer, Angela Wyse & Kevin Corinth
NBER Working Paper, June 2022
Abstract:
Despite widespread concern about homelessness, fundamental questions about the size and characteristics of this hard to study population are unresolved, in large part because it is unclear whether existing data are sufficiently complete and reliable. We examine these questions as well as the coverage of new microdata sources that are designed to be nationally representative and will allow pathbreaking new analyses. We compare three restricted use data sources that have been largely unused to study homelessness to less detailed public data. In doing this triangulation of sources, we examine the completeness and accuracy of available data and improve our understanding of the size of the homeless population and its inclusion in household surveys. Specifically, we compare restricted data from the 2010 Census, American Community Survey (ACS), and Homeless Management Information System (HMIS) to HUD's public-use point-in-time (PIT) estimates and the Housing Inventory Count (HIC) at the national, city and county, and person level. We explore the extent to which definitions, weighting, frame completeness, and seasonality explain discrepancies between sources. We also link HMIS shelter-use data to the Census to evaluate the usefulness of these microdata to study this population. Our analyses suggest that on a given night there are 500,000-600,000 people experiencing homelessness in the U.S., about one-third of whom are sleeping on the streets and two-thirds in shelters. About 80-95 percent of those in shelters were counted in the Census. Despite employing substantially different methods, the Census, ACS, and PIT arrive at similar estimates after accounting for definitional differences, ambiguity in the classification of certain facilities, and differences arising from the timeframe of Census response. The coverage of these sources is surprisingly good given the difficulties of surveying this population. By establishing the broad coverage and reliability of the new data sources, this paper lays the foundation for pathbreaking future work on the characteristics, income, safety net participation, mortality, migration, geographic distribution, and housing status transitions of the U.S. homeless population.
How Effective Is (More) Money? Randomizing Unconditional Cash Transfer Amounts in the US
Ania Jaroszewicz et al.
Harvard Working Paper, July 2022
Abstract:
We randomized over 5,000 US individuals in poverty to one of three conditions during the first year of the COVID-19 pandemic: receiving a one-time $500 unconditional cash transfer (UCT; half a month's worth of total household income for the median participant; N=1,374), a $2,000 UCT (two months' income; N=699), or nothing (N=3,170). We measured the effects of the UCTs on participants' financial well-being, psychological well-being, cognitive capacity, and physical health through surveys administered one week, six weeks, and 15 weeks after cash receipt. For 43% of our sample, we also observe bank account balances and financial transactions. While the cash transfers increased expenditures for a few weeks, we find no evidence that they had positive impacts on our pre-specified survey outcomes at any time point. We further find no significant differences between the $500 and $2,000 groups. These findings stand in stark contrast to the (incentivized) predictions of both experts and a nationally representative sample of laypeople, who -- depending on the treatment group, outcome, and time period -- estimated treatment effect sizes of +0.16 to +0.65 SDs. We test several explanations for these unexpected results, including via two survey experiments embedded in our trial. The data are most consistent with the notion that receiving some but not enough money made participants' needs -- and the gap between their resources and needs -- more salient, which in turn generated feelings of distress.
The Distributional Impact of the Minimum Wage in the Short and Long Run
Erik Hurst et al.
NBER Working Paper, July 2022
Abstract:
We develop a framework with rich worker heterogeneity, firm monopsony power, and putty-clay technology to study the distributional impact of the minimum wage in the short and long run. Our production technology is disciplined to be consistent with the small estimated employment effects of the minimum wage in the short run and the large estimated elasticities of substitution across inputs in the long run. We find that in the short run, a large increase in the minimum wage has a small effect on employment and therefore increases the labor income of the workers who were earning less than the new minimum wage. In the long run, however, the minimum wage has perverse distributional implications in that it reduces the employment, income, and welfare of precisely the low-income workers it is meant to help. Nonetheless, these long-run effects take time to fully materialize because firms slowly adjust their mix of inputs. Existing transfer programs, such as the earned income tax credit (EITC), are more effective at improving long-run outcomes for workers at the low end of the wage distribution. But combining existing programs with a modest increase in the minimum wage generates even larger welfare gains for low-earning workers.
SNAP Work Requirements Increase Mental Health Care Use
Lindsay Allen, Diana Henry & Alicia Atwood
Health Services Research, forthcoming
Data Sources and Study Setting:
We used 2015-2018 West Virginia Medicaid and SNAP data.
Study Design:
Nine counties were exposed to SNAP work requirements. Using an event study framework, we assessed how this changed the probability and number of visits for depression and anxiety in the treatment versus the control group.
Principal Findings:
At baseline, the probability of having a mood disorder visit was 6.1% among women and 5.3% among men, rising by 0.9 percentage points (SE 0.4, relative change +14.1%) among women and 0.7 percentage points (SE 0.3, relative change +13.0%) among men after exposure to work requirements. The probability of having an anxiety visit rose by 1.0 (SE 0.4) percentage points among women, a 17.8% relative increase over baseline of 5.8%. Among men, the likelihood of having an anxiety visit increased by 1.0 percentage points (SE 0.5), a relative change of 24.3% over a baseline probability of 5.0%, though this effect occurred much more gradually compared to women.
The Price of Inclusion: Evidence from Housing Developer Behavior
Evan Soltas
Review of Economics and Statistics, forthcoming
Abstract:
In many cities, incentives and regulations lead developers to integrate low-income housing into market-rate buildings. How cost-effective are these policies? I study take-up of a tax incentive in New York City using a model in which developers trade off between tax savings and pre-tax income. Estimating the model using policy variation and microdata on development from 2003 to 2015, I find a citywide marginal fiscal cost of $1.6 million per low-income unit. Differences in neighborhoods, not developer incidence, explain the cost premium over other housing programs. Weighing costs against estimates of neighborhood effects, I conclude middle-class neighborhoods offer "opportunity bargains."
Wealthier Neighbors and Higher Rents: The Rental Assistance Demonstration and Gentrification
Warren Lowell & Imari Smith
Urban Affairs Review, forthcoming
Abstract:
Public housing redevelopment is associated with the gentrification of neighborhoods. However, the Rental Assistance Demonstration (RAD), the largest redevelopment program in the U.S. to date, encourages preservation and introduces tenant protections that potentially limit gentrification-related displacement. In the first nationwide study of RAD's impact on neighborhoods, we linked administrative housing data with the American Community Survey and conducted difference-in-differences analyses of 1,141 neighborhoods across the U.S. to ask if RAD has induced changes associated with gentrification. We find that neighborhoods with redevelopment experienced larger gains in middle-class residents and larger losses in very low-income residents compared to similar, untreated neighborhoods. Neighborhoods with RAD also saw larger increases in rental housing costs, and these increases were largest in neighborhoods where redevelopment was extensive. These findings suggest that RAD contributes to gentrification. We use these findings to argue that policymakers must consider the housing stability of public housing's neighbors when planning redevelopment.
The Choice to Discriminate: How Source of Income Discrimination Constrains Opportunity for Housing Choice Voucher Holders
Forrest Hangen & Daniel O'Brien
Urban Affairs Review, forthcoming
Abstract:
The "choice" in the Housing Choice Voucher (HCV) program signals the mobility offered to voucher holders. However, some landlords use source of income (SOI) discrimination to exclude voucher holders-limiting their locational choices. We propose several factors likely to influence this landlord strategy including, market competitiveness, stereotypes, and racial discrimination. We examine the prevalence of express SOI discrimination and the effectiveness of SOI antidiscrimination laws. We utilize a novel dataset of 1,107,110 rental listings from the Craigslist pages of 77 mid-sized US cities. We find significant amounts of express SOI discrimination, even where there are SOI antidiscrimination laws. Using multilevel models, we find that landlords are more likely to expressly discriminate in lower-opportunity neighborhoods and when they own market-competitive units. We also find that these factors are moderated by the concentration of voucher holders. These findings underscore how landlord strategies can combine to undermine the choice afforded to voucher holders.