Article

Section 8 Vouchers and Rent Limits: Do Small Area Fair Market Rent Limits Increase Access to Opportunity Neighborhoods? An Early Evaluation

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Abstract

One critique of the U.S. Department of Housing and Urban Development (HUD)’s Housing Choice Voucher program is that its maximum rent limit is set at the metropolitan level, making more expensive neighborhoods effectively off limits to households who receive rental assistance. As a result, the design of the program limits a voucher household’s access to opportunity neighborhood. In response, HUD created the Small Area Fair Market Rent (SAFMR) demonstration program, which calculates the maximum voucher rent at the zip code level so that HUD’s rent limits more closely align with local neighborhood rents. In theory, this program should improve a voucher household’s choice set and location outcomes. Looking at changes in the location of beneficiaries in the six sites that participated in the SAFMR demonstration program, we find a significant amount of regional variation in the results. Specifically, introduction of the SAFMR rent calculations results in voucher households living in higher opportunity neighborhoods in Dallas, Texas, in lower opportunity neighborhoods in Chattanooga, Tennessee, and mixed effects in other areas. These mixed results highlight some of the potential incremental benefits of the program and reinforce the importance of viewing this policy over a longer period of time, and in the context of other constraints voucher households face in accessing neighborhood opportunity.

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... ZIP Codes were partly selected for convenience in that they are familiar to renters, landlords, and housing authorities. ZIP Codes are also sufficiently large such that rents can be estimated using the American Community Survey (ACS; Reina, Acolin, and Bostic, 2019). HUD also relied on early results from demonstrations of SAFMRs in Cook County, IL; Long Beach, CA; Chattanooga, TN; Mamaroneck, NY; Laredo, TX; and Dallas, TX, to suggest that ZIP Codes would increase access to opportunity in markets nationwide (Finkel, 2017;Reina, Acolin, and Bostic, 2019). ...
... ZIP Codes are also sufficiently large such that rents can be estimated using the American Community Survey (ACS; Reina, Acolin, and Bostic, 2019). HUD also relied on early results from demonstrations of SAFMRs in Cook County, IL; Long Beach, CA; Chattanooga, TN; Mamaroneck, NY; Laredo, TX; and Dallas, TX, to suggest that ZIP Codes would increase access to opportunity in markets nationwide (Finkel, 2017;Reina, Acolin, and Bostic, 2019). ...
... These trade-offs are important given that the few properties in highrent areas expected to become eligible under the proposed SAFMR standards are expected to be of marginal quality (assuming prices partly reflect quality). These results may explain previously observed declines in high-rent areas following the introduction of SAFMR into some markets (Reina, Acolin, and Bostic, 2019). ...
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Local public housing authorities define the payment standards-the voucher amounts paid to landlords-for renting their property under the Housing Choice Voucher (HCV) Program. Payment standards have been historically based on 40th percentile Fair Market Rents (FMRs) calculated by the U.S. Department of Housing and Urban Development (HUD) for metropolitan areas and non-metro counties. To better align payment standards with market rents, HUD has developed 40th percentile Small Area Fair Market Rents (SAFMRs) at the ZIP-Code level and have mandated their use in 24 metropolitan areas. Public housing authorities using SAFMRs in lieu of FMRs must maintain payment standards within 10 percent of the SAFMR. This study compares the efficacy of SAFMRs with rents listed for Pittsburgh, PA, by Rent Jungle, a commercial aggregator of rental data. Correlations between SAFMRs and the sampled rents were relatively low at 37 percent. Results indicate that small area markets defined using a combination of clustering and nearest neighbor algorithms are better predictors of market rents than ZIP Codes and require fewer market delineations, as shown by the adjusted R-squared exceeding 60 percent with only three clusters (compared with the 26 ZIP Codes in Pittsburgh). Results suggest that SAFMR achieves its goal of increasing the eligible units relative to FMR. Those increases were disproportionately in low-rent areas, however, where the proposed SAFMR is competitive with market rents. In contrast, in high-rent areas, the SAFMR is more than 50 percent lower than market rents, on average, resulting in few eligible units. These observations suggest SAFMRs are likely to increase the number of landlords interested in the HCV program in low-rent areas, but not in high-rent areas. To increase the use of vouchers in high-rent areas, payments to landlords should adequately compete with market rents. Otherwise, only landlords in high-rent areas that have trouble renting in the private market, such as those that offer properties of marginal quality, are likely to participate in the HCV program. 188 Small Area Fair Market Rents Blackhurst, Briem, and Deitrick
... Voucher holders tend to remain in neighborhoods with similar socioeconomic characteristics and do not fare significantly differently in terms of locational outcomes than similar renters without vouchers (Basolo & Nguyen, 2005;Devine et al., 2003;McClure, 2008;Pendall, 2000;Walter et al., 2015). Vouchers alone are thus not sufficient to improve the locational outcomes of low-income households, even with programmatic changes that have increased rent limits in more desirable neighborhoods without providing additional services to support the housing search process (Bergman et al., 2019;Reina et al., 2019). Although significant attention has been placed on the locational effects of mobility-oriented housing programs on low-income renters, only a limited strand of literature has examined neighborhood outcomes for low-and moderate-income homeowners. ...
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The impact of U.S. housing policy on household locational outcomes has primarily been studied in the context of rental housing assistance programs, but the impact of alternative homeownership models is less fully explored. In this study, we assess residential trajectories for households that have participated in shared-equity homeownership (SEH) programs such as Community Land Trusts and Limited Equity Housing Cooperatives. We examine changes in neighborhood characteristics that occur when households enter and exit SEH units, and compare those outcomes with similar households that entered traditional homeownership or continued to rent. We find that while entering SEH is associated with decreases in neighborhood opportunity measures, exiting SEH is associated with improvements in key measures including lower concentrations of poverty. We conclude that while entering SEH may entail moving to lower-opportunity neighborhoods, participation in SEH programs increases the long-term economic and socio-spatial mobility of participating households by enabling them to access a broader array of neighborhood contexts in their subsequent move.
... HUD's Small Area Fair Market Rent demonstration indexes voucher generosity to rent conditions at the zip code level (as opposed to the metro area), which may increase the likelihood that voucher recipients are successful at moving not just to less-disadvantaged neighborhoods but to high-opportunity neighborhoods. Initial results have been somewhat mixed (Reina, Acolin and Bostic 2019), suggesting that greater voucher generosity alone may not be sufficient to greatly increase moves to low-poverty neighborhoods or reduce racial disparities (Reina 2019). A recent experimental study in Seattle suggests that voucher supplements combined with financial support and assistance with moves can increase the success of similar programs (Bergman et al. 2019). ...
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Project-based housing programs and tenant-based housing programs (vouchers) may have differential effects on neighborhood outcomes for residents. Theoretically, vouchers should enhance access to low-poverty neighborhoods for low-income families thereby promoting economic mobility for children, though vouchers’ success may vary by race and ethnicity. Drawing on a national survey-administrative data linkage and a quasi-experimental approach, we examine the impact of project-based housing and vouchers on an index of socioeconomic neighborhood disadvantage among children. We find that living in project-based housing leads to greater exposure to neighborhood disadvantage while receiving vouchers leads to reduced exposure. Reductions in neighborhood disadvantage for children receiving vouchers are found only for non-Hispanic Black and Hispanic/Latino children. For non-White families, vouchers are associated with a reduced likelihood of living in high-poverty neighborhoods and increased likelihood of living in low-poverty neighborhoods, presenting an opportunity to narrow racial and ethnic differences in children's neighborhood attainment.
... Among these voucher recipients, those with Black or Hispanic household heads are more likely to live in and move to a higher poverty neighborhood (DeLuca, Garboden, & Rosenblatt, 2013;Galvez, 2010b;Reina & Winter, 2019;Wang, Larsen, & Ray, 2015). These racial disparities in locational outcomes are exacerbated by programmatic features that constrain families' housing decisions, such as the Fair Market Rent used to determine the rental voucher amount being insufficient to rent in a preferred neighborhood and the problem of voucher portability across regions (Basolo & Nguyen, 2005;Fisher, Mayberry, Shinn, & Khadduri, 2014;Reina, Acolin, & Bostic, 2019). Taken together, housing vouchers may maintain existing patterns of racial residential segregation and offer a weaker safety net for households of color compared with White households (Reina & Winter, 2019). ...
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People of color or mixed race account for more than half of all people experiencing homelessness, despite comprising less than a quarter of the total population in the United States. What are the primary drivers of this severe racial concentration of homelessness? Through a literature review of historical and contemporary research, this article highlights the extensive history of homelessness among Black, Latinx, and Native American communities and finds evidence for racialized pathways into homelessness. The literature points to three primary systems of stratification that drive racial disparities in homelessness: racial economic inequality, housing discrimination and residential segregation, and the homeless response system. These findings suggest that homelessness is tightly interwoven with institutions and social systems that maintain racial hierarchy. Structural policies that address socioeconomic and racial inequality are more likely than current approaches to make substantial progress in reducing racial disparities in homelessness.
... Data from Dallas, Texas, the first metropolitan area mandated to implement SAFMRs as part of a court settlement in 2010, indicates voucher households have been able to move out of high-poverty, unsafe neighborhoods with the implementation of SAFMRs (Collinson and Ganong, 2018). The two studies that have been conducted on the other demonstration areas, however, highlight how outcomes may vary depending on the housing market in which SAFMRs are implemented (Finkel et al., 2017;Reina, Acolin, and Bostic, 2019). ...
Article
Small Area Fair Market Rents (SAFMRs) are calculated at the 40th percentile of the U.S. postal ZIP Code instead of the metropolitan area in an effort to capture localized rents to expand choice for voucher holders to access housing in higher-opportunity neighborhoods. Existing studies on the potential and actual outcomes of SAFMRs demonstrate that findings vary for different types of housing markets. Furthermore, the decisions public housing authorities (PHAs) make in the implementation process affect PHAs' program budget and the rent burden and locational outcomes for voucher households. This study aims to address how these implementation factors are affected by local rental market conditions for three PHAs-Housing Authority of the City of Fort Lauderdale, San Antonio Housing Authority, and Seattle Housing Authority-in diverse housing markets. By comparing different sources of market rent estimates with SAFMRs in each location, we contribute new information about how this rule is likely to produce different residential outcomes in terms of increased access to low-poverty neighborhoods and adjustments to payment standards in low-rent neighborhoods. The findings reveal differences across rent measures in terms of estimated levels and relative differences across ZIP Codes. These findings suggest that housing authorities may face challenges in meeting the objectives of the SAFMR final rule without some form of local adjustments.
... SAFMRs are now being used in 24 metropolitan areas across the US. Early research on SAFMRs suggests such a change can produce positive results for program participants (Reina et al., 2019). Program recipients may use a voucher to rent a private housing or a unit funded by Low-Income Housing Tax Credits so long as that unit complies with the health and safety regulations imposed by HUD. ...
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Many countries use demand-side housing subsidies to support low-income households. Unlike public or social housing programs, demand-side subsidies require recipients to enter the private market to use their benefits. The focus of this study is the experiences of assisted households in the private housing market and the outcomes they achieve. Given the link between policy design and program outcomes and because all housing subsidy programs are not created equal, one might expect the experiences and outcomes of recipients to also vary. To examine this relationship, using data from national housing surveys, this study analyzes cross-national variation in housing support programs and compares the housing and neighbourhood outcomes of subsidized households in the US, the UK, and the Netherlands. The findings of this study highlight that market context and policy design are associated with housing outcomes. In particular, the strong tenant supports and favourable design of housing assistance in the Netherlands is associated with favourable outcomes for subsidized households. In the US and the UK, subsidized households, in general, underperform their unsubsidized peers. This article underscores the importance of institutional context and program design when public assistance programs require recipients to enter the private market to use a benefit.
... The latter has important policy ramifications as it could expand the choice sets of housing voucher holders seeking to move to higher-opportunity neighborhoods, if affordable units can be found (cf. Rosen, 2014;Schwartz et al., 2017;McLaughlin and Young, 2018;Reina et al., 2019). Practitioners, for example, could take advantage of this by broadcasting eligible-unit information online or by helping voucher holders devise online search strategies that focus on unit characteristics in higher-opportunity neighborhoods rather than familiar geographic silos. ...
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As the rental housing market moves online, the internet offers divergent possible futures: either the promise of more-equal access to information for previously marginalized homeseekers, or a reproduction of longstanding information inequalities. Biases in online listings’ representativeness could impact different communities’ access to housing search information, reinforcing traditional information segregation patterns through a digital divide. They could also circumscribe housing practitioners’ and researchers’ ability to draw broad market insights from listings to understand rental supply and affordability. This study examines millions of Craigslist rental listings across the USA and finds that they spatially concentrate and overrepresent whiter, wealthier, and better-educated communities. Other significant demographic differences exist in age, language, college enrollment, rent, poverty rate, and household size. Most cities’ online housing markets are digitally segregated by race and class, and we discuss various implications for residential mobility, community legibility, gentrification, housing voucher utilization, and automated monitoring and analytics in the smart cities paradigm. While Craigslist contains valuable crowdsourced data to better understand affordability and available rental supply in real time, it does not evenly represent all market segments. The internet promises information democratization, and online listings can reduce housing search costs and increase choice sets. However, technology access/preferences and information channel segregation can concentrate such information-broadcasting benefits in already-advantaged communities, reproducing traditional inequalities and reinforcing residential sorting and segregation dynamics. Technology platforms like Craigslist construct new institutions with the power to shape spatial economies, human interactions, and planners’ ability to monitor and respond to urban challenges.
... The latter has important policy ramifications as it could expand the choice sets of housing voucher holders seeking to move to higher-opportunity neighborhoods, if affordable units can be found (cf. McLaughlin and Young, 2018;Reina et al., 2019;Rosen, 2014;Schwartz et al., 2017). Practitioners, for example, could take advantage of this by broadcasting eligible-unit information online or by helping voucher holders devise online search strategies that focus on unit characteristics in higher-opportunity neighborhoods rather than familiar geographic silos. ...
... The latter has important policy ramifications as it could expand the choice sets of housing voucher holders seeking to move to higher-opportunity neighborhoods, if affordable units can be found (cf. Rosen, 2014;Schwartz et al., 2017;McLaughlin and Young, 2018;Reina et al., 2019). Practitioners, for example, could take advantage of this by broadcasting eligible-unit information online or by helping voucher holders devise online search strategies that focus on unit characteristics in higher-opportunity neighborhoods rather than familiar geographic silos. ...
Preprint
Full-text available
As the rental housing market moves online, the Internet offers divergent possible futures: either the promise of more-equal access to information for previously marginalized homeseekers, or a reproduction of longstanding information inequalities. Biases in online listings' representativeness could impact different communities' access to housing search information, reinforcing traditional information segregation patterns through a digital divide. They could also circumscribe housing practitioners' and researchers' ability to draw broad market insights from listings to understand rental supply and affordability. This study examines millions of Craigslist rental listings across the US and finds that they spatially concentrate and over-represent whiter, wealthier, and better-educated communities. Other significant demographic differences exist in age, language, college enrollment, rent, poverty rate, and household size. Most cities' online housing markets are digitally segregated by race and class, and we discuss various implications for residential mobility, community legibility, gentrification, displacement, housing voucher utilization, and automated monitoring and analytics in the smart cities paradigm. While Craigslist contains valuable crowdsourced data to better understand affordability and available rental supply in real-time, it does not evenly represent all market segments. The Internet promises information democratization, and online listings can reduce housing search costs and increase choice sets. However, technology access/preferences and information channel segregation can concentrate such information-broadcasting benefits in already-advantaged communities, reproducing traditional inequalities and reinforcing residential sorting and segregation dynamics. Technology platforms construct new institutions with the power to shape spatial economies and human interactions.
... The latter has important policy ramifications as it could expand the choice sets of housing voucher holders seeking to move to higher-opportunity neighborhoods, if affordable units can be found (cf. Rosen, 2014;Schwartz et al., 2017;McLaughlin and Young, 2018;Reina et al., 2019). Practitioners, for example, could take advantage of this by broadcasting eligible-unit information online or by helping voucher holders devise online search strategies that focus on unit characteristics in higher-opportunity neighborhoods rather than familiar geographic silos. ...
Preprint
Full-text available
As the rental housing market moves online, the Internet offers divergent possible futures: either the promise of more-equal access to information for previously marginalized homeseekers, or a reproduction of longstanding information inequalities. Biases in online listings' representativeness could impact different communities' access to housing search information, reinforcing traditional information segregation patterns through a digital divide. They could also circumscribe housing practitioners' and researchers' ability to draw broad market insights from listings to understand rental supply and affordability. This study examines millions of Craigslist rental listings across the US and finds that they spatially concentrate and over-represent whiter, wealthier, and better-educated communities. Other significant demographic differences exist in age, language, college enrollment, rent, poverty rate, and household size. Most cities' online housing markets are digitally segregated by race and class, and we discuss various implications for residential mobility, community legibility, gentrification, displacement, housing voucher utilization, and automated monitoring and analytics in the smart cities paradigm. While Craigslist contains valuable crowdsourced data to better understand affordability and available rental supply in real-time, it does not evenly represent all market segments. The Internet promises information democratization, and online listings can reduce housing search costs and increase choice sets. However, technology access/preferences and information channel segregation can concentrate such information-broadcasting benefits in already-advantaged communities, reproducing traditional inequalities and reinforcing residential sorting and segregation dynamics. Technology platforms like Craigslist construct new institutions with the power to shape spatial economies, human interactions, and planners' ability to monitor and respond to urban challenges.
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This article synthesizes findings from a wide range of empirical research into how neighborhoods affect families and children. It lays out a conceptual framework for understanding how neighborhoods may affect people at differ-ent life stages. It then identifies methodological challenges, summarizes past research findings, and suggests priorities for future work. Despite a growing body of evidence that neighborhood conditions play a role in shaping individual outcomes, serious methodological challenges remain that suggest some caution in interpreting this evidence. Moreover, no consensus emerges about which neighborhood characteristics affect which outcomes, or about what types of families may be most influenced by neighborhood condi-tions. Finally, existing studies provide little empirical evidence about the causal mechanisms through which neighborhood environment influences individual outcomes. To be useful to policy makers, future empirical research should tackle the critical question of how and for whom neighborhood matters.
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Fair Market Rents (FMRs) are used to define payment standards that govern the amount of assistance that Housing Choice Voucher Program (HCVP) participants receive. The U.S. Department of Housing and Urban Development (HUD) currently publishes a single FMR for each HUD metropolitan FMR area. To provide program participants with wider access to opportunity areas, the Department developed Small Area Fair Market Rents (SAFMRs). SAFMRs represent a fundamentally different way of operating the HCVP in metropolitan areas; therefore, HUD is testing SAFMRs through a demonstration program to better understand the programmatic effects.
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Individuals participating in the HUD Housing Choice Voucher program, formerly Section 8, can rent units in the private market and are not tied to public housing projects in a specific neighborhood. We would expect vouchers to help poor families leave the ghetto and move to more diverse communities with higher socioeconomic opportunity, but many voucher holders remain concentrated in poor, segregated communities. We use longitudinal qualitative data from one hundred low-income African American families in Mobile, Alabama, to explore this phenomenon, finding that tenants’ limited housing search resources, involuntary mobility, landlord practices, and several aspects of the voucher program itself limit families’ ability to escape disadvantaged areas. We also find that the voucher program’s regulations and funding structures do not incentivize housing authorities to promote neighborhood mobility and residential choice. This combination of forces often keeps voucher recipients in neighborhoods with high concentrations of poor and minority residents.
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The Section 8 voucher and certificate program potentially allows recipients to choose better neighborhoods than they might otherwise be able to afford. This article compares the location of households using Section 8 vouchers and certificates with the location of other renter households, both low‐income renters and all renters.In 1998, Section 8 users were 75 percent as likely as other poor tenants to live in distressed neighborhoods but 150 percent more likely than all renters to live in such tracts. These national averages obscure substantial variation among metropolitan areas. Section 8 users concentrate in distressed neighborhoods when rental housing concentrates there, but they avoid distressed neighborhoods with very low rents. Concentration also hinges on race; when assisted households are mostly black and other residents are mostly white, assisted households are much more likely to live in distressed neighborhoods.
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This chapter focuses on neighborhood effects in housing markets. Households in effect choose neighborhood effects, or more generally social interactions, via their location decisions, which renders them endogenous. Across several classes of models that it examines, it emphasizes how we may detect empirically the presence of neighborhood effects when they may be priced by housing markets and be capitalized into housing values and rents. The chapter focuses on models that are empirically relevant and help identify neighborhood effects, and discusses actual empirical findings.The first class of models examined involves models of choice over discrete sets of individual dwelling units that allow for a multidimensional bundle of characteristics. These models extend the Berry–Levisohn–Pakes characteristics-based approach and allow for endogenous contextual effects. The chapter develops in detail a specific application that also endogenizes contextual effects at a low level of dimensionality. The chapter examines neighborhood choice, with endogenous and contextual neighborhood effects, and housing demand (with housing being measured as a scalar) as joint decisions. This approach utilizes individual and neighborhood-level data at several levels of aggregation.The chapter next examines neighborhood effects within the canonical Alonso–Mills–Muth urban model with a well-defined spatial structure. Finally, the chapter reviews hierarchical models of neighborhood location in the presence of social interactions. These models describe communities in terms of a low-dimensional vector of attributes that are aggregated into a public good whose consumption is nonrival. Such approaches are designed to utilize community-level data, along with information on the community-specific distributions of various sociodemographicsociodemographic characteristics of individuals.JEL Codes: A10, C00, C31, C35, C81, D01, R14, R20, R21, H40, Z10, Z13
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Historically, federal housing policy has contributed to the concentration of poverty in urban America. Moving out of poverty is not the right answer for every low‐income family, but tenant‐based housing assistance (Section 8 certificates and vouchers) has tremendous potential to help families move to healthier neighborhoods. This article explores the role of tenant‐based housing assistance in addressing the problem of concentrated inner‐city poverty.The Section 8 program by itself does not ensure access to low‐poverty neighborhoods, particularly for minority families. Supplementing certificates and vouchers with housing counseling and search assistance can improve their performance; a growing number of assisted housing mobility initiatives are now in place across the country. The U.S. Department of Housing and Urban Development (HUD) should continue to fund these initiatives and increase their number over time. HUD should also strengthen incentives for all housing authorities to improve locational outcomes in their Section 8 programs.
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This article evaluates the relative performance of housing programs in terms of neighborhood quality. We profile neighborhood characteristics surrounding assisted housing units and assess the direction of assisted housing policy in light of this information. The analysis relies on a housing census database we developed that identifies the type and census tract location of assisted housing units—that is, public housing, developments assisted under the Department of Housing and Urban Development, the Section 515 Rural Rental Housing Direct Loan Program, the low‐income housing tax credit, certificates and vouchers, and state rental assistance programs.We conclude that project‐based assistance programs do little to improve the quality of recipients’ neighborhoods relative to those of welfare households and, in the case of public housing, appear to make things significantly worse. The certificate and voucher programs, however, appear to reduce the probability that families will live in the most economically and socially distressed areas.
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This paper examines the effect of receiving a housing voucher on the mobility and neighborhood attributes of low-income households. Housing policy has shifted towards vouchers in lieu of public housing projects to allow households to move away from high poverty areas. We use administrative records collected from an experiment to examine this issue. We find that households moved immediately after receiving the subsidy, but did not relocate to lower poverty neighborhoods until several quarters later. Our findings suggest that recipients initially lease in nearby units to secure the subsidy, while continuing to search for housing in lower poverty neighborhoods.
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This study estimates the effects of means-tested housing programs on labor supply using data from a randomized housing voucher wait-list lottery in Chicago. Evidence for the net effects of housing programs on labor supply is central to a wide range of policy decisions about how to provide housing assistance to the poor. Economic theory is ambiguous about the expected sign of any labor supply response. We find that among working-age, able-bodied adults, housing voucher use reduces quarterly labor force participation rates by 4 percentage points (6 percent of the control complier mean) and quarterly earnings by $285 (10 percent), and increases social program participation rates by 2 percentage points (16 percent of the control mean). These impacts are toward the lower end of the range of recent estimates from other studies of housing programs, but nonetheless do still imply that housing vouchers reduce labor supply.
Study on Section 8 voucher success rates. Volume I. Quantitative study of success rates in metropolitan areas. Cambridge, MA: Prepared by Abt Associates for the U.S. Department of Housing and Urban Development
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Housing choice voucher location patterns: Implications for participants and neighborhood welfare
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What do we know about housing choice voucher program location outcomes: A review of recent literature
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Department of Housing and Urban Development Office of Policy Development and Research
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Do vouchers help low-income households live in safer neighborhoods? Evidence on the housing choice voucher program
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