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Federal Policy Changes Can Help More Families with Housing Vouchers Live in Higher-Opportunity Areas

September 4, 2018

The Housing Choice Voucher (HCV) program, which is federally funded and run by more than 2,100 state and local housing agencies, helps about 2.2 million low-income households — nearly half of which have minor children in the home — pay for modestly priced housing they find in the private market. Housing Choice Vouchers enable families to afford decent, stable housing, avoid homelessness, and make ends meet. They also can enable children to grow up in better neighborhoods, enhancing their chances of long-term health and success. When black families use housing vouchers, for example, their children are twice as likely as other poor black children to grow up in low-poverty neighborhoods and are less likely to grow up in extremely poor areas. Still, 315,000 children in families using vouchers lived in extremely poor neighborhoods in 2017.[1] Many families with vouchers would like to move to safer, higher-opportunity areas with good schools, and vouchers could do much more to help them do so. Many families with vouchers would like to move to safer, higher-opportunity areas with good schools.

Public housing agencies have flexibility under current HCV program rules to implement strategies to help more low-income families live in better neighborhoods. But without changes in federal policy to encourage agencies to take such steps and to modify counter-productive policies — and without reliable funding to maintain the number of families receiving HCV assistance and to administer the program effectively — there’s little reason to expect significantly better results.

This paper briefly reviews research on why the type of neighborhood in which children grow up matters to their future and current data on where children in families that have vouchers live. It then describes four sets of interrelated federal policy changes that would help more families in the HCV program live in higher-opportunity neighborhoods:

  1. Help interested families use vouchers to live in high-opportunity areas. Congress should establish and fund the Housing Choice Voucher Mobility Demonstration. Authorized by a nearly unanimous, bipartisan vote of the House, the demonstration would allow public housing agencies to provide robust housing mobility services, including pre- and post-move support (such as financial coaching) for voucher holders who want to move to a higher-opportunity area, outreach to landlords to recruit more of them to participate, and housing search assistance. The Department of Housing and Urban Development (HUD) should support inclusion of funding for the demonstration in the final 2019 HUD funding bill and implement it quickly and effectively.
  2. Create strong incentives for housing agencies to improve location outcomes. Federal policy should provide incentives for agencies to reduce the share of families using vouchers in extreme-poverty areas and to increase the share residing in low-poverty, high-opportunity areas. HUD could do this by rewarding agencies that help families move to high-opportunity areas (by paying these agencies additional administrative fees), by giving added weight to location outcomes in measuring agency performance, and by reinforcing these “carrots” through implementation and enforcement of the 2015 fair housing rule.
  3. Modify policies that discourage families from living in lower-poverty communities. Some HCV program policies impede families from moving to low-poverty areas and thereby unintentionally encourage families to use their vouchers in poor neighborhoods, which may undermine their children’s future success. For example, families’ rental subsidies are generally based on rental costs of modest housing over an entire metropolitan area, so they’re often too low for neighborhoods with low poverty, low crime, and strong schools. HUD can address this problem by effectively implementing the Small Area Fair Market Rent (SAFMR) regulation; SAFMRs better reflect actual market rents and thus make more units available to voucher holders. HUD should also require agencies to identify available units in higher-opportunity, low-poverty communities and give families seeking to make such moves added time to search for housing.
  4. Minimize jurisdictional barriers to families’ ability to choose to live in high-opportunity communities. In most metropolitan areas, one agency administers the HCV program in the central city and different agencies serve suburban cities and towns, which often impedes families’ efforts to use vouchers in higher-opportunity areas. HUD can substantially reduce these jurisdictional barriers by encouraging agencies in the same metropolitan area to unify their program operations and by reducing financial disincentives for agencies to encourage moves across jurisdictional lines (known as “portability” moves).

Some families will choose to remain in their current neighborhood — in order to remain close to their current job, their family, or child care, for example — even if the barriers to moving to areas with more opportunities are removed. But the policy changes listed above could enable many more families and their children to significantly improve their lives and would make a modest but important step forward in reducing intergenerational poverty.

These changes alone, of course, will by no means solve the problems associated with concentrated poverty.[2] Other initiatives are also critical, including efforts to preserve affordable housing in communities where gentrification and other forces would otherwise push poor families away from improving opportunities. Better strategies are also needed to increase incomes, enhance safety, create healthier environments, and improve educational performance in very poor areas.[3] In the meantime, improving the HCV program’s performance in helping families live in better neighborhoods is an attainable near-term goal that policymakers should pursue aggressively.

Neighborhoods Influence Children’s Well-Being and Long-Term Success

Where families live largely determines the quality of their children’s schools, the safety of the streets and playgrounds, and the characteristics of their neighbors. It also can affect adults’ access to jobs,[4] transportation costs to work, access to fresh and reasonably priced food and other basic goods and services, and the distance between child care and jobs.[5]\

A compelling body of research shows that growing up in low-poverty neighborhoods with good schools improves children’s academic achievement and long-term chances of success, on average, and reduces intergenerational poverty. Studies have also consistently found that, on average, living in high-poverty neighborhoods with low-performing schools and high rates of violent crime harms families’ well-being and children’s long-term outcomes.[6] In light of these findings, federal housing policy should, wherever possible, enable low-income families — particularly those with young children — to live in high-opportunity neighborhoods, if they choose to do so.

Groundbreaking Studies Strengthen Evidence of Neighborhoods’ Influence

A groundbreaking 2015 study by Harvard economists Raj Chetty, Nathaniel Hendren, and Lawrence Katz found that young children in low-income families that used housing vouchers to move to better neighborhoods fared much better on average as young adults than similar children who remained in extremely poor neighborhoods.[7] The study provided the first look at adult outcomes for children who were younger than 13 when their families entered the Moving to Opportunity (MTO) demonstration, a rigorous, multi-decade comparison of low-income families who used vouchers to relocate to low-poverty neighborhoods with similar families that remained in public housing developments in extremely poor neighborhoods.

The Chetty-Hendren-Katz study found that young boys and girls in families that used a voucher to move to lower-poverty neighborhoods were 32 percent more likely to attend college and earned 31 percent — nearly $3,500 a year — more as young adults than their counterparts in families that didn’t receive an MTO voucher. Girls in families that moved to lower-poverty neighborhoods were also 30 percent less likely to be single parents as adults. (See Figure 1.) Neighborhoods’ effects were cumulative, the study found: the longer children lived in better neighborhoods (that is, the younger they were when their families moved), the larger their gains as young adults. These important findings reinforced similar results obtained in a separate Chetty-led study of a much larger sample of children in families that moved across county lines.[8]

Earlier MTO studies further revealed that living in low-poverty neighborhoods has strong positive effects on adults’ mental and physical health. Adults in families that used an MTO voucher to move to lower-poverty neighborhoods reported 33 percent fewer instances of major depression, compared to those without MTO vouchers, and higher scores on measures of subjective well-being, such as happiness. Adults who moved with MTO vouchers also had much lower rates of extreme obesity and diabetes.[9] Parental depression can negatively affect children’s well-being as well as be debilitating for the adults themselves: studies show that parental depression (and other stress-related problems, as explained below) is associated with poor social development and poor physical, psychological, behavioral, and mental health for children, particularly young children.[10]

Figure 1
Moving with Voucher to Lower-Poverty Neighborhoods While Young Children Improves Key Adult Outcomes

 

The MTO studies reinforce the conclusions of earlier research. In a study of low-income children living in public housing and attending elementary schools in Montgomery County (a Maryland suburb bordering the District of Columbia), RAND researcher Heather Schwartz found that low-income students who lived in low-poverty neighborhoods and attended low-poverty schools made large gains in reading and math scores over a seven-year period, compared with similar students living in public housing and attending moderate-poverty or moderately high-poverty schools.[11] At the end of seven years, the test scores of the public housing children in low-poverty schools had closed half of the achievement gap between those students and non-poor students in the district in math and one-third of the gap in reading — large gains by educational standards.[12]

Studies Connect Exposure to Violence and Extreme Poverty to Worse Outcomes for Children

The rigorous studies led by Chetty, Schwartz, and others have strengthened the consensus among researchers that neighborhoods significantly influence children’s chances of academic and economic success.[13] Thanks to studies in several areas, researchers are also piecing together a nascent understanding of how extreme-poverty neighborhoods worsen children’s outcomes, although much work remains to be done.[14]

A seminal study by Robert Sampson, Patrick Sharkey, and Stephen Raudenbusch tracked 6- to 12-year-old black children in Chicago as they moved into and out of neighborhoods of concentrated disadvantage. (These neighborhoods were similar in many ways to those from which families with MTO housing vouchers moved.) Isolating the effects of neighborhoods from other factors such as parents’ income and marital status, the researchers found that children living in neighborhoods of concentrated disadvantage performed less well on two standard tests of vocabulary and reading — a major predictor of educational, employment, and other important life outcomes, studies show — by a magnitude equal to one to two years of schooling. Equally striking, the harmful effects became stronger the longer that children were exposed to such environments. And they lingered even after children had left the neighborhoods.[15]

In another series of studies, Sharkey and his colleagues examined the impact of neighborhood violence on children’s cognitive and academic performance. One study found that when preschool children were assessed within a week of a homicide occurring near their home, they were less able to control their impulses and pay attention, and they scored lower on pre-academic vocabulary and math tests.[16] Another study comparing the standardized test performance of New York City students in the week before a violent crime occurred on their block with that of students in the week after such crimes found that such exposure significantly reduced students’ performance on English language assessments, particularly for black students. Among black students, the effect on scores was equivalent to 13 percent of the black-white gap in test scores and reduced students’ passing rates by three percentage points.

While these studies directly examined the short-term effects of neighborhood violence, they have implications for the long-term success of students who are exposed to repeated incidents of violence.[17] Supporting this conclusion is a more recent study by Sharkey and Gerard Torrats-Espinosa, which found that children who grew up in communities with high rates of violent crime had significantly lower incomes as young adults. Chetty and his colleagues found a similar relationship between violent crime and children’s later economic success in their study of families that moved across communities.[18]

Toxic Stress Research Explains Some Links Between Neighborhoods and Child Well-Being

These findings dovetail with the growing research about the harmful effects of “toxic stress,” or the activation of the body’s stress response system when a child experiences frequent, persistent, or excessive fear or anxiety due to exposure to abuse, neglect, violence, or severe hardship — particularly when the child doesn’t receive adequate adult support in coping with the stress. While much of the research has focused on the effects of child abuse and family dysfunction, researchers believe that exposure to neighborhoods of concentrated disadvantage — particularly those where violent crime is more common — may also be a contributing factor.

Toxic stress affects children’s brain development, early learning, and their body’s stress response system in ways that alter their cognitive development and physical health over the longer term.[19] Toxic stress affects brain development in the areas that regulate emotion and executive function, for example, the latter of which includes the ability to create and follow plans, focus attention, inhibit impulses, and incorporate new information –– abilities essential to children’s success in school. Toxic stress has also been linked to physical changes that increase the risk of long-term health problems such as heart disease.[20]

So compelling is the research on toxic stress that the American Academy of Pediatrics adopted a formal policy statement urging policymakers to reshape policy and the provision of services to reduce the causes and effects of toxic stress for young children.[21] The statement explicitly cites “community-level” (or neighborhood) factors such as violence as a risk factor for toxic stress.

Further research is essential to better understand the specific mechanisms by which neighborhoods influence children’s well-being. But the extant body of work provides powerful evidence that neighborhoods have a substantial impact on their chances of long-term success.

Data Show Vouchers Have Limited Effect on Where Children Live

The Housing Choice Voucher program helps about 2.2 million low-income households pay for modestly priced, decent-quality homes in the private market.[22] It assists more families with children than public housing and Project-Based Rental Assistance, the other two major rental assistance programs, combined.[23] While the program helps families afford decent housing and make ends meet ― which has a significant impact on these families, as research shows[24] ― its impact on the neighborhoods in which they live has been limited, and is well short of the program’s potential.[25] Even so, it has performed substantially better than HUD’s project-based rental assistance programs in enabling more low-income families with children to live in lower-poverty neighborhoods and avoid extreme-poverty areas.[26]

Roughly 1 in 8 families with children participating in the HCV program in 2017 (13.6 percent) used their vouchers to live in a low-poverty area — that is, one where fewer than 10 percent of residents are poor. Poor black, Hispanic, Native American, and Pacific Islander families with vouchers were more likely to live in low-poverty neighborhoods than such poor families overall. Among families using vouchers, poor black children were twice as likely, and poor Hispanic children were 36 percent more likely, to live in low-poverty neighborhoods in 2017 than poor black and Hispanic children overall. In contrast, poor white and Asian children in families with vouchers were less likely to live in low-poverty neighborhoods than poor white or Asian children overall.[27] (See Figure 2.)

Figure 2
Vouchers Enable Minority Children to Live in Better Neighborhoods

Also, having a housing voucher may reduce the likelihood that poor children of color live in an extreme-poverty neighborhood, where 40 percent or more of the residents are poor. Poor black, Asian, Native American, and Pacific Islander children using vouchers are less likely to live in an extreme-poverty neighborhood than all poor black, Asian, Native American and Pacific Islander children. For example, in 2017, 16.7 percent of poor black children using vouchers lived in extreme-poverty neighborhoods, almost a third less than the figure for poor black children overall. Conversely, poor white, non-Hispanic children using vouchers were more likely to live in an extreme-poverty neighborhood than poor white children overall.[28]

As noted, 315,000 children in the HCV program live in extreme-poverty neighborhoods.[29] This shows that the program isn’t delivering adequately on its potential to expand children’s access to good schools in safe neighborhoods that encourage upward mobility, or to help families live outside of extremely poor neighborhoods that are more prone to violence and other conditions that undermine children’s health and future success. The program can and should do much more to help families avoid living in neighborhoods that likely diminish children’s outcomes and to help families remain in lower-poverty or improving neighborhoods.

Policy Recommendations

Some families don’t use their vouchers to reside in lower-poverty, safer, diverse neighborhoods because they want the stability of remaining in their current neighborhoods or close to support networks and current jobs. But many families want to move to higher-opportunity areas, or are largely unaware of opportunities in unfamiliar neighborhoods and would seek to live in them if they had more information.[30] Many also need assistance from program administrators to identify landlords willing to accept vouchers in communities where vouchers are infrequently used and rental vacancies are low. In addition, local voucher subsidy caps are often too low to enable families to afford units in high-opportunity areas, and other program policies can limit voucher holders’ available choices.[31]

The policy framework of the HCV program largely assumes that having a voucher opens up the choice of units to rent just like added income would, and that poor families are aware of the housing options that a voucher makes available. But as researchers Stefanie DeLuca, Philip Garboden, and Peter Rosenblatt concluded, “the ‘free market choice’ assumptions behind the HCV program do not hold in reality.”[32] Federal policy allows agencies to decide whether and how to address families’ needs for assistance in the search process.[33] Agencies that ignore the need for housing search assistance or have ineffective or counter-productive policies face virtually no risk of HUD sanction.[34]

While lack of moderately priced rental units in low-poverty neighborhoods is a constraint in some areas,[35] in most large metro areas there isn’t a supply barrier preventing a much larger share of families from using their vouchers to rent units in areas that would likely be better for their children.[36]

Public housing agencies have flexibility under current federal requirements to implement strategies in their HCV programs to improve location outcomes, and state and local governments could facilitate these efforts. But too few use the flexibility they have. Without changes in federal policy to encourage state and local agencies to take such steps and modify counter-productive policies — and without reliable funding to maintain the number of families receiving HCV assistance and administer the program effectively — there is little reason to expect better results.

Even in the current political and fiscal environment, we can make substantial progress toward providing greater opportunities for families to choose affordable housing outside of extreme-poverty neighborhoods and particularly in low-poverty, safe communities with access to jobs and better-performing schools. Federal policymakers should make four sets of interrelated policy changes.

 

Enabling Families With Children to Use Housing Choice Vouchers to Live in Higher-Opportunity Neighborhoods

Help Interested Families Use Vouchers to Live in High-Opportunity Areas

  • Congress should enact and fund the Housing Choice Voucher Mobility Demonstration
  • The Department of Housing and Urban Development (HUD) and public housing agencies (PHAs) should bring housing mobility programs to scale

Create Strong Incentives for Agencies to Improve Location Outcomes

  • HUD should pay PHAs added administrative fees when families use vouchers in high-opportunity areas
  • HUD should give increased weight to location outcomes in measuring PHA performance
  • HUD should enforce fair housing requirements
  • HUD should encourage agencies to collaborate regionally, including by forming consortia or consolidating
  • HUD should reduce financial disincentives for agencies to promote “portability” moves

Balance Families’ Location Incentives

  • PHAs should set subsidy caps for smaller geographic areas, and HUD should encourage them to do so
  • PHAs should give voucher holders information on available units in higher-opportunity neighborhoods, and HUD should monitor this requirement
  • PHAs should expand search periods when families need more time to find units in high-opportunity neighborhoods

1. Help Interested Families Use Vouchers to Live in High-Opportunity Areas

Some 20 agencies, out of 2,100, offer a mobility program to help low-income families use their vouchers to move to high-opportunity areas.[37] These programs, largely supported by special grants or private funding, have shown some promising results.[38] Other than these rare exceptions, however, agencies do little to expand families’ access to better neighborhoods,[39] though interest is growing.[40] With additional funding and incentives, they could do much more.

Inspired by the recent research by Raj Chetty and his colleagues described above, the House has approved legislation to establish a new Housing Choice Voucher Mobility Demonstration. If funded, the demonstration would allow agencies to provide robust housing mobility services and determine which are most effective. HUD should support inclusion of funding for the demonstration as the House Appropriations Committee bill proposes in the final 2019 HUD funding bill and implement it effectively.

Enact and Fund Promising Congressional Initiative

To create more housing mobility programs and determine which interventions are most cost effective, Reps. Sean Duffy (R-WI) and Emanuel Cleaver (D-MO), the chair and ranking member of the Housing and Insurance Subcommittee of the House Financial Services Committee, proposed the Housing Choice Voucher Mobility Demonstration Act of 2018. The proposal, which the House approved in a nearly unanimous, bipartisan vote, recognizes the growing body of evidence that families with children who move to low-poverty areas do better in the long term.[41] The House Appropriations Committee has proposed funding the demonstration with $50 million, which would be critical to providing robust services to voucher holders.

The House proposal includes:

  • $30 million for housing mobility support services and operating regional mobility programs. Using these funds, agencies would help families access communities of opportunity by offering services such as landlord outreach, housing search assistance, post-move support, and financial coaching. The demonstration would also let participating agencies use HCV program funding for security deposits in designated opportunity areas; lack of funds for security deposits is a significant barrier for poor families to move to higher-opportunity areas where landlords require these payments.
  • $20 million for new vouchers for families with children participating in the demonstration. These approximately 2,000 additional vouchers would serve as an incentive for agencies to participate. They also would make some progress toward addressing the decline in the number of families with children receiving vouchers.[42]
  • Research to determine which program components are most cost effective. If funds permit, the bill directs HUD to evaluate what interventions are most cost effective.

To ensure the demonstration has the greatest impact, the bill would require HUD to award funds on a competitive basis and prioritize regional collaborations among agencies with high concentrations of voucher holders in low-opportunity neighborhoods, a high-performing Family Self-Sufficiency program, or a strong regional collaboration including one or more small agencies, among other factors. HUD would have flexibility to decide how many grants to award.[43]

HUD should indicate its support for the demonstration, and Congress should enact and fund it at the level proposed by the House.[44] HUD should then move forward quickly to effectively implement the demonstration. HUD should engage private foundations to allow for a more robust evaluation and include a broad research advisory group for the evaluation.

Take Subsequent Steps to Bring Voucher Mobility to Scale

The House proposal gives HUD up to five years to submit a final report on the demonstration after it starts, but additional efforts to initiate or expand housing mobility programs need not wait until then.

HUD could widely share preliminary research findings from the demonstration to encourage other agencies to implement promising practices. In addition, Congress could adopt the recent proposal by the U.S. Partnership on Mobility from Poverty to fund 500,000 new vouchers for low-income families with young children combined with mobility services to facilitate moves to opportunity-rich neighborhoods.[45] And HUD implementation of the policy recommendations described below would encourage more agencies to expand housing choices for families with vouchers.[46]

2. Create Strong Incentives for Agencies to Improve Location Outcomes

By creating strong incentives for agencies to reduce the share of families using vouchers in extreme-poverty areas and increase the share living in high-opportunity areas, HUD can encourage agencies to develop policies and strategies best suited to varying local conditions. Three such steps are described below.

Pay agencies additional administrative fees when families use their vouchers in high-opportunity areas. Agencies that provide services to help families use their vouchers in high-opportunity areas incur additional costs and risk lower fee payments from HUD if it takes these families longer to find a willing landlord.[47] Higher costs but lower fees are more likely when such moves are particularly difficult, such as for families who may need more assistance to move to unfamiliar areas. In 2016, HUD issued a proposed rule for determining how to allocate administrative fees to agencies, based on a major analysis it had conducted of the costs of running a well-administered voucher program.[48] However, HUD has taken no action to finalize a new administrative fee structure.[49] HUD should move to implement a new fee structure that includes location-based payments, either as part of the new payment formula or as a bonus or supplemental payment.

Even without a change in regulation, HUD could make supplemental disbursements to help agencies offset these costs. HUD has used its discretion to make such payments to promote use of vouchers for homeownership and other purposes.[50] Indeed, since 2013 HUD has provided additional funding to agencies that administer a relatively large share of vouchers on behalf of families that have moved from a community served by a different agency; this has been an effective way to reduce financial disincentives to accepting such movers. While HUD develops a new administrative fee formula, it should use its discretion to provide supplemental administrative fees to agencies that significantly increase the share of vouchers used in high-opportunity areas and outside of areas of concentrated poverty.

Give increased weight to location outcomes in measuring agency performance. Over the long term, HUD’s most powerful tool to induce agencies to change their administrative practices is how it measures agencies’ management of the HCV program. HUD should revise its measurement tool, called the Section 8 Management Assessment Program (SEMAP), which was first issued in 1998 and is largely unchanged, to give more weight to the types of neighborhoods in which voucher holders live. SEMAP scores are important to agencies: they can affect whether agencies qualify for additional HUD funds or administrative flexibility, and some agencies take these scores into account in managers’ performance reviews and pay determinations. Agencies that perform particularly poorly are subject to corrective action procedures and can lose their HCV contract with HUD if they don’t remedy the problems.

Currently, fewer than 4 percent of the total points available under SEMAP are based on agencies’ use of administrative practices that “expand housing opportunities.” A similar number of bonus points are available to agencies in metropolitan areas that increase the share of HCV families with children living in “low-poverty” areas, but only a small share of agencies claim those bonus points.[51] In revising the performance measure, HUD should give more weight to location outcomes and also refine its location measure; research shows that a multi-factor measure can better identify high-opportunity areas than the poverty rate alone.[52]

To persuade more landlords in higher-opportunity areas to do business with them, agencies will also have to administer their voucher programs competently, such as by paying owners promptly and conducting inspections efficiently.[53] Thus, measuring agencies’ performance in significant part on their success in enabling more families to live in these areas also should improve overall program management.

Reinforce performance measures by effectively implementing the new fair housing rule. All agencies administering the HCV program (as well as HUD) have a statutory obligation to further the purposes of the Fair Housing Act, known as the “AFFH” duty. In 2015, some 47 years after Congress established this obligation, HUD finally issued a rule to indicate what agencies must do to meet it.[54] The rule requires HCV agencies (as well as agencies managing public housing and states and localities receiving HUD funds) to identify the factors that primarily contribute to segregation and restriction of housing choice in their regions and programs, and to establish priorities and goals that will guide their planning and policy and investment decisions to ameliorate these problems. The rule highlights “enhancing mobility strategies” in the HCV program as a key type of action that agencies should include in their assessment of fair housing.[55] HUD effectively suspended the rule in two separate actions in the first half of 2018 and is soliciting public comment on whether to revise the rule substantially.[56] Significantly changing the rule, which had been subject to many years of public comment, could strip its key elements, making it less effective at achieving long-overdue changes to achieve the goal of equal housing opportunities.

Regardless of the status of HUD’s rule, the statutory obligation to affirmatively further fair housing remains, as HUD has acknowledged, and agencies must certify annually that they have complied with civil rights and fair housing requirements in their administration of the HCV program.[57] Effective implementation of AFFH requirements, including specification of the consequences of inadequate HCV-related actions by agencies, would complement a revised performance measurement system that emphasizes increasing access to higher-opportunity areas. Black and Hispanic families make up most of the assisted families in extreme-poverty areas and are less likely than white assisted families to live in low-poverty areas,[58] in large part due to public policies that enforced or encouraged segregation.[59] HUD should take steps to help remedy the legacy of segregation and ensure that housing agencies, states, and localities meet their fair housing obligations.

3. Modify Policies That Discourage Families from Living in Lower-Poverty Communities

Many HCV program policies at both the federal and local levels — such as metropolitan-wide limits on rental subsidy levels and limits on the time that families have to find a rental unit — unintentionally encourage families to use their vouchers in poor communities with few resources to support children and their families. Combined with the recommendations listed above, the three federal policy changes outlined below could encourage agencies to adopt payment standards and search-related practices that would help families move to higher-opportunity areas.

Increase use of new subsidy caps for smaller geographic areas. HCV rental subsidies are capped by a payment standard set by the local housing agency; the standard generally can vary by only 10 percent from the Fair Market Rent (FMR) figure, which is specified by HUD. Until recently, HUD based FMRs throughout the country on the cost of modest housing over an entire metropolitan area. Payment standards based on metro-wide FMRs are inefficient and often too low to cover rent for units in neighborhoods with low poverty, low crime, and strong schools.[60]

In 2016, HUD issued a regulation requiring certain agencies to base their voucher subsidy caps on Small Area Fair Market Rents (SAFMRs), which are based on market rents in individual zip codes rather than an entire metro area. This requirement applies to 24 metropolitan areas where vouchers are heavily concentrated in low-income neighborhoods and the rental market is not too tight.[61] After a court invalidated the Trump Administration’s suspension of the requirement, it took effect April 1, 2018.[62] Congress provided additional funds in 2018 to help agencies comply with the rule.[63] HUD should effectively monitor the implementation of SAFMRs where they are required and encourage other agencies in metropolitan areas to base their voucher subsidy caps on SAFMRs.

Give voucher holders information on units in high-opportunity neighborhoods. Many agencies influence families’ neighborhood choices through their lists of landlords willing to rent to voucher holders. (HUD requires agencies to provide a list of willing landlords or other resources, such as online search tools, in the information packet they provide to families as they are issued vouchers.) But unless agencies take the potentially time-consuming effort to solicit listings from landlords in lower-poverty areas, many of the landlords who reach out to the agency will likely list units that are difficult for them to rent, particularly units in very poor neighborhoods where families often have trouble paying rent on time each month unless they have a rental subsidy.[64]

In 2015, HUD modified its rules to require agencies to ensure that such lists or other resources include units in areas “outside of poverty or minority concentration.”[65] This is a positive step, but it’s unclear if HUD is monitoring compliance with the new requirement. HUD should monitor and enforce this requirement.[66] Since many agencies refer voucher holders searching for new housing to online search tools, HUD could facilitate agencies’ compliance by persuading the major companies that list appropriately priced apartment rentals to meet the new standard or by compelling them to do so through its power to enforce the Fair Housing Act.[67]

Extend search periods when families need more time to find units in high-opportunity neighborhoods. Inflexible limits on the time that families with vouchers have to find a unit meeting program requirements can also discourage them from searching for housing in neighborhoods that are harder for them to get to and/or where fewer landlords accept vouchers.[68] Federal rules require agencies to give households a minimum of 60 days to lease a unit with their voucher and permit agencies to allow additional time.[69] HUD should make clear that agencies may set a longer initial search period or extend the search time for any sound reason, and should do so to enable a family to find a unit in a low-poverty area or in an area where their race does not predominate. In the latter case, this would “affirmatively further” fair housing.

4. Minimize Jurisdictional Barriers to Families’ Ability to Live in High-Opportunity Communities

HUD should modify the administrative geography of the HCV program to substantially reduce the extent to which agencies’ service areas (or “jurisdictions”) impede families’ access to higher-opportunity neighborhoods. In most metropolitan areas, one agency administers the HCV program in the central city and one or more different agencies serve suburban cities and towns. That’s the case in 97 of the 100 largest metro areas, where 71 percent of households in the HCV program lived in 2015. In 35 of the 100 largest metro areas, voucher administration is divided among ten or more agencies. They include mid-size areas such as Providence, Rhode Island, and Albany, New York, each of which has at least 35 agencies administering the HCV program.[70]

Rental units in safe neighborhoods with good schools may be more plentiful in suburban areas than in the central cities, which are more likely to have higher-poverty neighborhoods with failing schools, but the balkanization of metro-area HCV programs among numerous agencies often impedes greater use of vouchers in the higher-opportunity areas.[71] Agency staff may be unfamiliar with housing opportunities outside of their jurisdiction and are unlikely to assist families to make such moves. Some landlords may be reluctant to do business with an unfamiliar housing agency.

Overcoming these administrative divisions is challenging, and cumbersome federal “portability” policies can exacerbate the problem by making it harder for families coming from the central city or poor suburban areas to use their vouchers to lease housing in low-poverty suburban areas with better schools. Agencies also have financial disincentives to encourage such moves. HUD could substantially lessen these barriers by adopting the steps outlined below.

Encourage agencies to form consortia or consolidate. If agencies in a metro area could at least form a consortium in which each retains its local board but together they have a single voucher funding contract with HUD, families could use their vouchers to move seamlessly within the cities and towns in the consortium.[72] Families that want to move to another jurisdiction wouldn’t have to jump through additional administrative hoops, and agencies wouldn’t have to transfer voucher documents and funds to another agency under portability procedures. Nor would families risk losing savings they accumulated through participation in HUD’s Family Self-Sufficiency program.[73] Under HUD’s current rules, however, agencies have little incentive to form consortia, and even if they do, they still don’t have a single funding contract with HUD.[74]

In May 2018, the President signed legislation requiring HUD to allow for full consolidated reporting by agencies that elect to operate consortia, in order to reduce agencies’ administrative burdens.[75] This could be an important incentive for more agencies to form consortia. HUD should implement this requirement no later than the November 2018 deadline, as the law requires. Reporting requirements would be further reduced if agencies in a consortium had a single funding contract with HUD, which would enable them to report voucher utilization and spending data as a single entity. In 2014, HUD proposed to revise its consortia rule to allow all HCV agencies in a consortium to have a single funding contract with HUD, but to date has not finalized the rule.

The 2018 law also requires HUD to make software available to agencies and privately owned assisted properties to implement regional shared waiting lists.[76] The availability of such software likely would encourage more housing providers to operate joint waiting lists in regions or states, making it easier for families to apply for voucher assistance. Also, operating joint waiting lists would encourage regional agency cooperation and information sharing, which could be a stepping stone to forming consortia or consolidating. HUD should act expeditiously to implement this directive.

Reduce financial disincentives for agencies to promote “portability” moves. When a family uses a voucher in a different jurisdiction than the one that issued the voucher, both agencies involved usually receive lower fees (due to the requirement to split the administrative payments) and typically incur higher costs (due to the transfer of paperwork and funds between the agencies).[77] HUD recently made modest changes in its “portability” procedures that likely will reduce some of the added costs for agencies, but agencies likely will still incur financial losses when families move to other jurisdictions. Those losses deter agencies from encouraging such moves.[78]

HUD should revise its administrative fee policy to provide higher funding to agencies that send or receive substantial numbers of families across jurisdictional lines.[79] HUD’s efforts since 2013 to provide additional funding to agencies that have more than 20 percent of their participants from another jurisdiction have reduced the most extreme financial penalties agencies face. But this policy isn’t sufficiently broad, and isn’t reliable since HUD can decide each year whether to continue such supplemental funding. HUD should change its administrative fee policy to permanently recognize increased costs that occur when families “port” their vouchers.[80]

In some areas, agencies have established regional portability agreements that reduce agencies’ costs and families’ administrative barriers. HUD could encourage adoption of such agreements in more areas by collecting and disseminating information on leading practices through notices, trainings, and online materials.

Consider consolidation and expanding housing choice in selecting remedies in response to poor agency performance. HUD has the authority to require consolidation when an agency is not administering the HCV program effectively, even if a state or local law limits the geographic area of agency operation.[81] HUD rarely uses this authority, and when consolidation occurs, HUD typically transfers vouchers from the failing agency to the nearest local housing agency. HUD should instead consider whether a county, regional, or statewide housing voucher program exists that could serve the original community while also expanding families’ housing choices due to its broader geographic service area.

Technical Appendix

TABLE A-1
Where Assisted Households With Children Live, by Neighborhood Poverty Rate
    Distribution by Neighborhood Poverty Rate  
Program Total Households Less than 10% 10%-19.9% 20%-29.9% 30%-39.9% 40% or higher Median Poverty Rate
Housing Choice Vouchers 958,200 13.6% 27.7% 26.1% 18.8% 13.8% 23.2%
Public Housing 344,900 3.9% 15.5% 20.9% 23.1% 36.6% 34.4%
Project-Based Section 8 325,000 6.4% 22.7% 25.0% 20.7% 25.3% 28.6%
Total 1,638,700 10.1% 24.1% 24.7% 20.1% 21.0% 26.3%

Note: Table excludes roughly 18,000 assisted households with missing neighborhood data and assisted households in U.S. territories. Total includes additional households in several small HUD programs.

Source: CBPP analysis of 2017 HUD administrative data and 2012-2016 American Community Survey.

TABLE A-2
Where Assisted Children Live, by Neighborhood Poverty Rate
    Distribution by Neighborhood Poverty Rate  
Program Total Children Less than 10% 10%-19.9% 20%-29.9% 30%-39.9% 40% or higher Median Poverty Rate
Housing Choice Vouchers 2,141,400 13.5% 27.0% 25.7% 19.1% 14.7% 23.5%
Public Housing 725,000 4.0% 15.3% 20.6% 23.0% 37.1% 34.6%
Project-Based Section 8 637,500 6.1% 21.8% 24.7% 21.0% 26.4% 28.8%
Total 3,522,400 10.2% 23.7% 24.4% 20.2% 21.5% 26.5%

Note: Table excludes roughly 41,000 assisted children with missing neighborhood data and assisted children in U.S. territories. Total includes additional children in several small HUD programs.

Source: CBPP analysis of 2017 HUD administrative data and 2012-2016 American Community Survey.

TABLE A-3
Race and Ethnicity of Assisted Households With Children, by Program and Neighborhood Poverty Rate
      Distribution by Neighborhood Poverty Rate    
Program Race or Ethnicity Total Households Less than 10% 10%-19.9% 20%-29.9% 30%-39.9% 40% or higher % households with children % all households in program
Housing Choice Vouchers Asian 13,100 20.8% 33.8% 27.1% 12.8% 5.5% 1.4% 2.5%
Black 560,000 11.8% 24.8% 26.4% 21.2% 15.8% 58.5% 48.2%
Hispanic/Latino* 163,800 12.0% 26.2% 27.3% 19.9% 14.6% 17.1% 16.3%
Multiracial 9,300 16.1% 29.8% 25.3% 16.1% 12.7% 1.0% 0.8%
Native American 6,800 15.8% 33.8% 26.1% 15.3% 9.1% 0.7% 0.7%
Pacific Islander 4,500 22.0% 40.5% 21.4% 9.9% 6.1% 0.5% 0.3%
White 200,300 19.2% 36.0% 24.3% 12.1% 8.5% 20.9% 31.2%
Public Housing Asian 5,300 6.4% 18.1% 18.2% 21.9% 35.4% 1.5% 2.3%
Black 185,600 2.9% 11.0% 18.2% 23.8% 44.1% 53.8% 45.3%
Hispanic/Latino* 64,800 3.4% 13.7% 20.1% 25.2% 37.6% 18.8% 16.4%
Multiracial 2,400 7.4% 20.2% 22.7% 21.6% 28.1% 0.7% 0.4%
Native American 2,900 8.1% 25.5% 19.6% 21.5% 25.3% 0.8% 0.6%
Pacific Islander 2,300 7.0% 35.7% 12.8% 20.7% 23.8% 0.7% 0.4%
White 81,400 6.3% 25.9% 27.9% 20.1% 19.7% 23.6% 34.4%
Project-Based Section 8 Asian 4,100 9.4% 28.9% 28.2% 18.6% 14.9% 1.3% 4.9%
Black 167,800 4.0% 16.3% 22.5% 23.6% 33.6% 53.5% 34.8%
Hispanic/Latino* 56,700 5.5% 20.4% 25.9% 22.6% 25.6% 18.1% 14.7%
Multiracial 5,000 9.3% 29.3% 25.7% 18.8% 16.9% 1.6% 1.0%
Native American 3,100 6.7% 28.8% 24.8% 22.8% 16.8% 1.0% 0.7%
Pacific Islander 700 11.0% 26.9% 28.9% 16.1% 17.1% 0.2% 0.2%
White 76,100 11.2% 37.0% 29.9% 13.3% 8.7% 24.3% 43.7%
Total Asian 22,600 15.4% 29.2% 25.1% 15.9% 14.4% 1.4% 3.2%
Black 918,200 8.5% 20.4% 24.0% 22.2% 24.9% 56.5% 43.3%
Hispanic/Latino* 288,200 8.7% 22.2% 25.3% 21.6% 22.1% 17.7% 15.9%
Multiracial 16,700 12.8% 28.4% 25.0% 17.6% 16.1% 1.0% 0.8%
Native American 12,900 11.8% 30.8% 24.3% 18.5% 14.7% 0.8% 0.7%
Pacific Islander 7,500 16.4% 37.9% 19.5% 13.8% 12.5% 0.5% 0.3%
White 360,000 14.5% 33.9% 26.3% 14.1% 11.1% 22.1% 35.8%

*A household of any race may identify as Hispanic or Latino ethnicity. All racial categories (Asian, black, multiracial, Native American, Pacific Islander, and white) exclude households whose head identifies as Hispanic or Latino, making the categories mutually exclusive. Race and ethnicity categories are determined using the race or ethnicity of the household head.

Note: Table excludes 26,000 households with children with missing race, ethnicity, or neighborhood data and assisted households in U.S. territories. Total includes additional households in several small HUD programs.

Source: CBPP analysis of 2017 HUD administrative data and 2012-2016 American Community Survey.

TABLE A-3
Race and Ethnicity of Assisted Households With Children, by Program and Neighborhood Poverty Rate
      Distribution by Neighborhood Poverty Rate    
Program Race or Ethnicity Total Households Less than 10% 10%-19.9% 20%-29.9% 30%-39.9% 40% or higher % households with children % all households in program
Housing Choice Vouchers Asian 13,100 20.8% 33.8% 27.1% 12.8% 5.5% 1.4% 2.5%
Black 560,000 11.8% 24.8% 26.4% 21.2% 15.8% 58.5% 48.2%
Hispanic/Latino* 163,800 12.0% 26.2% 27.3% 19.9% 14.6% 17.1% 16.3%
Multiracial 9,300 16.1% 29.8% 25.3% 16.1% 12.7% 1.0% 0.8%
Native American 6,800 15.8% 33.8% 26.1% 15.3% 9.1% 0.7% 0.7%
Pacific Islander 4,500 22.0% 40.5% 21.4% 9.9% 6.1% 0.5% 0.3%
White 200,300 19.2% 36.0% 24.3% 12.1% 8.5% 20.9% 31.2%
Public Housing Asian 5,300 6.4% 18.1% 18.2% 21.9% 35.4% 1.5% 2.3%
Black 185,600 2.9% 11.0% 18.2% 23.8% 44.1% 53.8% 45.3%
Hispanic/Latino* 64,800 3.4% 13.7% 20.1% 25.2% 37.6% 18.8% 16.4%
Multiracial 2,400 7.4% 20.2% 22.7% 21.6% 28.1% 0.7% 0.4%
Native American 2,900 8.1% 25.5% 19.6% 21.5% 25.3% 0.8% 0.6%
Pacific Islander 2,300 7.0% 35.7% 12.8% 20.7% 23.8% 0.7% 0.4%
White 81,400 6.3% 25.9% 27.9% 20.1% 19.7% 23.6% 34.4%
Project-Based Section 8 Asian 4,100 9.4% 28.9% 28.2% 18.6% 14.9% 1.3% 4.9%
Black 167,800 4.0% 16.3% 22.5% 23.6% 33.6% 53.5% 34.8%
Hispanic/Latino* 56,700 5.5% 20.4% 25.9% 22.6% 25.6% 18.1% 14.7%
Multiracial 5,000 9.3% 29.3% 25.7% 18.8% 16.9% 1.6% 1.0%
Native American 3,100 6.7% 28.8% 24.8% 22.8% 16.8% 1.0% 0.7%
Pacific Islander 700 11.0% 26.9% 28.9% 16.1% 17.1% 0.2% 0.2%
White 76,100 11.2% 37.0% 29.9% 13.3% 8.7% 24.3% 43.7%
Total Asian 22,600 15.4% 29.2% 25.1% 15.9% 14.4% 1.4% 3.2%
Black 918,200 8.5% 20.4% 24.0% 22.2% 24.9% 56.5% 43.3%
Hispanic/Latino* 288,200 8.7% 22.2% 25.3% 21.6% 22.1% 17.7% 15.9%
Multiracial 16,700 12.8% 28.4% 25.0% 17.6% 16.1% 1.0% 0.8%
Native American 12,900 11.8% 30.8% 24.3% 18.5% 14.7% 0.8% 0.7%
Pacific Islander 7,500 16.4% 37.9% 19.5% 13.8% 12.5% 0.5% 0.3%
White 360,000 14.5% 33.9% 26.3% 14.1% 11.1% 22.1% 35.8%

*A household of any race may identify as Hispanic or Latino ethnicity. All racial categories (Asian, black, multiracial, Native American, Pacific Islander, and white) exclude households whose head identifies as Hispanic or Latino, making the categories mutually exclusive. Race and ethnicity categories are determined using the race or ethnicity of the household head.

Note: Table excludes 26,000 households with children with missing race, ethnicity, or neighborhood data and assisted households in U.S. territories. Total includes additional households in several small HUD programs.

Source: CBPP analysis of 2017 HUD administrative data and 2012-2016 American Community Survey.

TABLE A-4
Race and Ethnicity of Poor Children Using Vouchers, by Neighborhood Poverty Rate
    Distribution by Neighborhood Poverty Rate    
Race or Ethnicity Total Children Less than 10% 10%-19.9% 20%-29.9% 30%-39.9% 40% or higher Median Poverty Rate % all poor children using vouchers
Asian 17,400 18.4% 31.3% 27.5% 14.8% 7.9% 20.0% 1.0%
Black 985,900 11.2% 24.0% 26.4% 21.7% 16.7% 25.5% 59.3%
Hispanic/Latino* 283,400 11.1% 25.7% 27.0% 20.5% 15.6% 24.7% 17.1%
Multiracial 27,000 15.8% 32.1% 24.5% 16.3% 11.3% 20.6% 1.6%
Native American 11,300 15.8% 33.9% 25.0% 16.0% 9.3% 20.1% 0.7%
Pacific Islander 7,800 20.8% 42.2% 21.1% 10.4% 5.6% 17.6% 0.5%
White 328,400 16.4% 32.1% 23.6% 13.6% 14.3% 20.4% 19.8%
Total 1,661,600 12.4% 26.3% 25.9% 19.7% 15.8% 24.2% 100.0%

*A child of any race may identify as Hispanic or Latino ethnicity. All racial categories (Asian, black, multiracial, Native American, Pacific Islander, and white) exclude children who identify as Hispanic or Latino, making the categories mutually exclusive.

Note: Poverty status is determined using Census Bureau’s official poverty measure. Poverty status cannot be determined for unrelated individuals under age 15 (such as foster children). See Methodology for details. Table excludes 51,000 children with missing race, ethnicity, or neighborhood data and assisted children in U.S. territories. Total includes additional households in several small HUD programs.

Source: CBPP analysis of 2017 HUD administrative data and the 2012-2016 American Community Survey.

TABLE A-5
Race and Ethnicity of All Poor Children, by Neighborhood Poverty Rate
    Distribution by Neighborhood Poverty Rate  
Race or Ethnicity Total Children Less than 10% 10%-19.9% 20%-29.9% 30%-39.9% 40% or higher Median Poverty Rate  
Asian 370,100 23.3% 31.0% 22.5% 13.8% 9.5% 17.4%  
Black 3,238,000 5.6% 19.6% 26.1% 24.0% 24.7% 29.2%  
Hispanic/Latino* 4,667,900 7.1% 25.2% 29.7% 22.0% 15.9% 25.6%  
Multiracial 788,100 14.4% 33.4% 25.5% 15.5% 11.3% 20.1%  
Native American 209,400 6.2% 23.5% 25.5% 23.6% 21.1% 24.1%  
Pacific Islander 33,600 10.8% 34.6% 28.2% 16.9% 9.6% 15.5%  
White 4,050,100 21.1% 41.1% 23.3% 9.3% 5.2% 16.6%  
Total 12,986,800 11.9% 29.4% 26.4% 18.0% 14.4% 22.9%  

*A child of any race may identify as Hispanic or Latino ethnicity. Categories are not mutually exclusive and do not sum to the total. Black and white racial categories exclude children who identify as Hispanic or Latino. However, 370,000 children who identify as Asian, multiracial, Native American, or Pacific Islander also appear in the Hispanic/Latino category and cannot be separated out due to data limitations.

Note: Poverty status is determined using Census Bureau’s official poverty measure. Poverty status cannot be determined for unrelated individuals under age 15 (such as foster children). See Methodology for details. Table excludes children for whom poverty status could not be determined, children who identified as some other race, and children in U.S. territories.

Source: CBPP tabulations the 2012-2016 American Community Survey.

Data Sources and Methodologies

Assisted Households

Data on HUD-assisted households are from a 2017 dataset from the HUD Office of Policy Development and Research, available through a research agreement. This dataset contains demographic and location information collected through HUD Form 50058 and the Tenant Rental Assistance Certification System. This dataset includes households with children in the following HUD-administered rental-assistance programs:

  • Public Housing
  • Section 8 Housing Choice Vouchers
  • Section 8 Project-Based Rental Assistance
  • Moderate Rehabilitation
  • Supportive Housing for the Elderly (Section 202)
  • Supportive Housing for People with Disabilities (Section 811)
  • Rent Supplement
  • Rental Assistance Program

Our analysis excludes HUD-assisted households located in U.S. territories.

Assisted Households With Children

The HUD administrative data report the presence and number of minor children in each household using rental assistance. We considered a household to have children if at least one household member was under age 18, regardless of their relationship to the household head.

Race and Ethnicity of Assisted Households

The HUD administrative data report the race and ethnicity of each person in each household using rental assistance. Data on assisted households by race and ethnicity are based on the self-reported race and ethnicity of the household head. Data on assisted children by race and ethnicity are based on the self-reported race and ethnicity of each child. We create mutually exclusive categories based on race and ethnicity in order to isolate differences in location for Hispanic or Latino households and children. Asian, black, multiracial, Native American, Pacific Islander, and white race categories exclude households or children who identify as Hispanic or Latino ethnicity, making the categories mutually exclusive. A household or child who identifies as Hispanic or Latino ethnicity may be of any race. Race and ethnicity data were missing for roughly 8,000 assisted household heads and 10,000 assisted children.

Race and Ethnicity of Poor Children

Data on poor children by race and ethnicity are from the 2012-2016 American Community Survey (ACS). The ACS does not consistently differentiate between children by race who identify as Hispanic or Latino ethnicity. Black and white racial categories exclude children who identify as Hispanic or Latino ethnicity. However, roughly 370,000 children who identify as Asian, multiracial, Native American, or Pacific Islander also appear in the Hispanic/Latino category because they also identify as Hispanic/Latino ethnicity. Consequently, race and ethnicity categories for poor children add to more than 100 percent. These data may include some children receiving HUD rental assistance. The ACS does not include information on receipt of rental assistance, making it impossible to exclude such children.

Poverty

Poverty status is determined using the Census Bureau’s official poverty measure. The Census Bureau uses a set of money income thresholds that vary by family size and composition to determine who is in poverty. If a family’s total income is below the threshold, the family and every individual in it are considered in poverty. The official poverty thresholds do not vary geographically, but they are updated for inflation using the Consumer Price Index (CPI-U). The official poverty definition uses money income before taxes and omits capital gains and non-cash benefits (such as housing assistance, Medicaid, and SNAP benefits). The Census cannot determine poverty status for people in:

  • Institutional group quarters (such as prisons or nursing homes)
  • College dormitories
  • Military barracks
  • Living situations without conventional housing (e.g., homeless people who are not in shelters)

Additionally, the Census cannot determine poverty status for unrelated individuals under age 15 (such as foster children) because the Census does not collect relevant income data on people age 15 or younger. We rely on Census’s poverty thresholds to determine the poverty status of households using vouchers in the HUD administrative data. To ensure comparability between the two sources, we exclude unrelated children under age 15 (i.e., foster children) in our poverty calculations. We compare poor assisted children to all children in poverty to control for income and because it is not possible to identify all children who are eligible for but do not receive HUD rental assistance in the ACS data. (A household is eligible for federal rental assistance if its income is below 80 percent of the local median income.)

Neighborhood Poverty

Data on neighborhood poverty rates are from the 2012-2016 ACS. We use Census tract boundaries as a proxy for neighborhood boundaries. Census tracts are small, relatively permanent geographic subdivisions of a county or equivalent entity; they generally have a population between 1,200 and 8,000 people, with an optimum size of 4,000. We consider a neighborhood “low poverty” if fewer than 10 percent of the people living in that Census tract have incomes below the poverty line. We consider a neighborhood “extreme poverty” if 40 percent or more of the people living in that Census tract have incomes below the poverty line. To determine the neighborhood poverty rate for assisted households and children, we matched each household’s tract number to their Census tract’s poverty rate reported in the ACS data. Our analysis excludes roughly 18,000 assisted households and 41,000 children with missing neighborhood data.

End Notes

[1] CBPP analysis of HUD 2017 administrative data.

[2] Caroline Ratcliffe and Emma Kalish, “Escaping Poverty: Predictors of Persistently Poor Children’s Economic Success,” U.S. Partnership on Mobility from Poverty, May 2017, https://www.urban.org/sites/default/files/publication/90321/escaping-poverty.pdf.

[3] Broad-scale economic development and revitalization strategies for disadvantaged neighborhoods (including those, such as HOPE VI, that emphasize revitalizing affordable housing developments have proven costly, often take years to implement, and have yielded mixed results for low-income residents. See Susan J. Popkin and Mary Cunningham, “Has HOPE VI transformed residents’ lives?,” in H.G. Cisneros & L. Engdahl, eds., From Despair to Hope: HOPE VI and the New Promise of Public Housing in America’s Cities, Brookings Institution Press, 2009, pp. 191-204. While we have much to learn about which interventions are effective in transforming poor areas at a substantial scale, researchers have identified several successful examples of such changes (e.g., Tennessee Valley Authority and casino gaming on some American Indian reservations), as well as promising efforts to improve outcomes for families in poor communities by targeting them with intensive services and supports for families (e.g., Harlem Children’s Zone). See Margery Austin Turner et al., “Opportunity Neighborhoods: Building the Foundation for Economic Mobility in America’s Metros,” US Partnership on Mobility from Poverty, February 2018, https://www.mobilitypartnership.org/opportunity-neighborhoods; Laura Tach and Christopher Wimer, “Evaluating Policies to Transform Distressed Urban Neighborhoods,” US Partnership on Mobility from Poverty, October 2017, https://www.mobilitypartnership.org/file/1218161/download?token=KviEEtEo; and Patrick Sharkey, “Neighborhoods, Cities, and Economic Mobility,” Russell Sage Foundation Journal of the Social Sciences, Vol. 2, 2016, pp. 159-177, https://www.rsfjournal.org/doi/full/10.7758/RSF.2016.2.2.07.

[4] Rebecca Casciano and Douglas S. Massey, “Neighborhood Disorder and Individual Economic Self-Sufficiency: New Evidence from a Quasi-experimental Study,” Social Science Research, February 2012, pp 1-18.

[5] Xavier de Souza Briggs, The Geography of Opportunity: Race and Housing Choice in Metropolitan America, Brookings Institution Press, 2005.

[6] For a synthesis of some of this research, see Barbara Sard and Douglas Rice, “Creating Opportunity for Children: How Housing Location Can Make a Difference,” Center on Budget and Policy Priorities, October 15, 2014, http://www.cbpp.org/research/creating-opportunity-for-children; Patrick Sharkey, Stuck in Place: Urban Neighborhoods and the End of Progress toward Racial Equality, University of Chicago Press, 2013; Sharkey, 2016, op. cit.

[7] Raj Chetty, Nathaniel Hendren, and Lawrence Katz, “The Effects of Exposure to Better Neighborhoods on Children: New Evidence from the Moving to Opportunity Experiment,” American Economic Review, April 2016, pp. 855-902. (This study was first released in 2015, see http://www.equality-of-opportunity.org/images/mto_paper.pdf). The results of this study are broadly consistent with the impressive outcomes found in the quasi-experimental Gautreaux studies, which tracked the outcomes of low-income families who used housing vouchers to move from segregated public housing developments in Chicago to middle-class, mostly-white suburbs. See also James E. Rosenbaum, “Changing the Geography of Opportunity by Expanding Residential Choice: Lessons from the Gautreaux Program,” Housing Policy Debate, 1995, pp. 231-269; Stefanie DeLuca and Elizabeth Dayton, “Switching Social Contexts: The Effects of Housing Mobility and School Choice Programs on Youth Outcomes,” Annual Review of Sociology, August 2009, pp. 457–491.

[8] Raj Chetty and Nathaniel Hendren, “The Effects of Neighborhoods on Intergenerational Mobility I: Childhood Exposure Effects and II: County-Level Estimates,” Quarterly Journal of Economics (August 2018, a version of which was released in 2015) tracked more than 7 million lower-income families who moved across county lines or “commuting zones,” comparing outcomes of children who moved to better neighborhoods (as measured by the outcomes of the children already living there) to those who did not. Consistent with the findings of their MTO analysis, the researchers found greater college attendance, less teenage pregnancy, and higher incomes as young adults for the children in families that moved to better areas. The longer the children lived in better areas, the stronger were these positive effects. The five location characteristics most strongly correlated with low-income children’s long-term outcomes were segregation by race and income (including concentration of poverty), income inequality, school quality, preponderance of two-parent families, and rate of violent crime.

[9] Jens Ludwig et al, “Long-Term Neighborhood Effects on Low-Income Families: Evidence from Moving to Opportunity,” American Economic Review, May 2013, pp. 226-231.

[10] Several MTO studies have found differences in mental health outcomes for boys and girls in families that used vouchers to relocate to lower-poverty areas. These studies generally find reduced risks of depression and other mental health improvements among girls, but several found worse mental health outcomes among boys. The latter findings are not well understood. One potential factor identified by researchers is that neighborhood changes may weaken boys’ relationships with fathers who remain behind. Racial bias among white residents of low-poverty neighborhoods may also have a greater impact on black boys than girls. For discussion of these findings, see Sard and Rice (2014), and Raj Chetty, et al., “Race and Economic Opportunity in the United States: An Intergenerational Perspective,” March 2018, http://www.equality-of-opportunity.org/assets/documents/race_paper.pdf. From a policy perspective, it is important to keep in mind that the share of boys experiencing worse mental health was small (fewer than 1 in 20), and despite these negative impacts, boys overall experienced positive long-term gains (e.g., in college attendance and earnings) identified by Chetty and his colleagues. Still, the mental health outcomes for boys are cause for concern and suggest that counseling and other forms of support for parents and children aimed at easing their transition to new neighborhoods are important. These outcomes also reinforce the importance of family choice of housing and location as a key principle of housing policy: family needs may be complex, and parents are ultimately the best judge of what type of housing and neighborhood best suits their family’s needs.

[11] Schwartz’s study took advantage of a natural experiment made possible by the county’s housing policies. Applicants for public housing assistance were randomly assigned to public housing developments across the county. Because of the county’s zoning policies, most of these developments are in low-poverty neighborhoods (with poverty rates of less than 10 percent), while the others are in neighborhoods with moderate or high poverty rates (up to 32 percent). This enabled Schwartz to compare educational outcomes for students living in neighborhoods and attending schools that differed significantly with respect to poverty and related characteristics.

[12] Heather Schwartz, “Housing policy is school policy: Economically integrative housing promotes academic success in Montgomery County, Maryland,” in R.D. Kahlenberg, ed., The Future of School Integration, Century Foundation, 2012. A study of families participating in the Baltimore Housing Mobility Program also found promising gains in reading and math test scores after five years for children in families that used vouchers to move to low-poverty areas, although the study did not have a control group. See Stefanie DeLuca et al., The Power of Place: How Housing Policy Can Boost Educational Opportunity, Abell Foundation, 2016, https://abell.org/sites/default/files/files/ed-power-place31516.pdf.

[13] For references, see Sard and Rice, 2014.

[14] Racism and discriminatory public policies have played a central role in the creation and persistence of neighborhoods of extreme poverty, which are home primarily to people of color, particularly African Americans. (These factors also contributed to the creation and persistence of high-opportunity neighborhoods, which are predominantly white.) See, for instance, Richard Rothstein, The Color of Law: A Forgotten History of How Our Government Segregated America, Liveright, 2017, and Sharkey, 2013, op. cit. For this reason, it is important to recognize that many of the characteristics of extreme-poverty neighborhoods that harm children’s health and chances of success are entangled with the forces of racism.

[15] Robert J. Sampson, Patrick Sharkey, and Stephen W. Raudenbusch, “Durable Effects of Concentrated Disadvantage on Verbal Ability Among African-American Children,” Proceedings of the National Academy of Sciences, January 2008, pp. 845-852. Building on the work of Sampson and others, Wodtke, Harding, and Elwert also found that sustained exposure to neighborhoods of concentrated disadvantage had a long-term impact on children’s educational achievement. Analyzing data, including neighborhood changes, for more than 4,000 students from across the country over a 17-year period, they found that high-school graduation rates were 20 percentage points lower for black children with the greatest exposure to neighborhood disadvantage than for comparable black children with the least exposure. See Geoffrey T. Wodtke, David J. Harding, and Felix Elwert, “Neighborhood effects in temporal perspective: The Impact of Long-Term Exposure to Concentrated Disadvantage on High School Graduation,” American Sociological Review, September 2011, pp. 713–736.

[16] Patrick T. Sharkey et al., “The Effect of Local Violence on Children’s Attention and Impulse Control,” American Journal of Public Health, December 2012, pp. 2287-2293. Researchers also found elevated levels of stress among the parents, which suggests that parental stress may be a causal pathway by which violence influences children’s performance. (This hypothesis is consistent with the research on toxic stress discussed below.)

[17] Patrick Sharkey et al., “High Stakes in the Classroom, High Stakes on the Street: The Effects of Community Violence on Students’ Standardized Test Performance,” Sociological Science, May 2014, pp. 199-220.

[18] Patrick Sharkey and Gerard Torrats-Espinosa, “The effect of violent crime on economic mobility,” Journal of Urban Economics, 2017, pp. 22-33. This study builds on the longitudinal data on children’s locations and incomes that Chetty and his colleagues released in 2015 (and published in 2018). Chetty and Hendren (2018) also found strong correlations between local violent crime rates and children’s later incomes as young adults.

[19] National Scientific Council on the Developing Child (NSCDC), “Excessive Stress Disrupts the Architecture of the Developing Brain: Working Paper No. 3,” Harvard University, 2014, https://developingchild.harvard.edu/resources/wp3; NSCDC, “Persistent Fear and Anxiety Can Affect Young Children’s Learning and Development: Working Paper No. 9, Harvard University, 2010, https://developingchild.harvard.edu/resources/persistent-fear-and-anxiety-can-affect-young-childrens-learning-and-development; Jack Shonkoff et al., “Neuroscience, molecular biology, and the childhood roots of health disparities: building a new framework for health promotion and disease prevention,” JAMA, June 2009, pp. 2252-2259, http://www.brooklyn.cuny.edu/pub/departments/childrensstudies/conference/pdf/Shonkoff-Boyce-McEwen_JAMA.pdf; Shonkoff et al., “The lifelong effects of early childhood adversity and toxic stress,” PediatricsMonth, 2012, pp. 232-246, http://pediatrics.aappublications.org/content/pediatrics/129/1/e232.full.pdf.

[20] Centers for Disease Control and Prevention, “Child maltreatment: risk and protective factors,” April 10, 2018, https://www.cdc.gov/violenceprevention/childabuseandneglect/riskprotectivefactors.html. Nurturing support from parents and other adults can mitigate the effects of stress on children. Yet poor parents living in high-poverty neighborhoods experience hardships, stresses, and stress-related problems — such as depression — to a degree that can hinder their ability to provide nurturing support for their children (and may engender or exacerbate negative outcomes among children). NSCDC, “Maternal Depression Can Undermine the Development of Young Children: Working Paper No. 8,” Harvard University, 2009, https://developingchild.harvard.edu/resources/maternal-depression-can-undermine-the-development-of-young-children/.

[21] American Academy of Pediatrics, “Early childhood adversity, toxic stress and the role of the pediatrician: Translating developmental science into lifelong health,” January 2012, http://pediatrics.aappublications.org/content/129/1/e224.

[22] Center on Budget and Policy Priorities, “Policy Basics: The Housing Choice Voucher Program,” updated May 3, 2017, http://www.cbpp.org/research/housing/policy-basics-the-housing-choice-voucher-program.

[23] CBPP analysis of Department of Housing and Urban Development (HUD) 2017 administrative data. See Appendix Table A-1.

[24] Will Fischer, “Research Shows Housing Vouchers Reduce Hardship and Provide Platform for Long-Term Gains Among Children,” Center on Budget and Policy Priorities, October 7, 2015, http://www.cbpp.org/files/3-10-14hous.pdf; Barbara Sard, Mary Cunningham, and Robert Greenstein, “Helping Young Children Move Out of Poverty by Creating a New Type of Rental Voucher,” US Partnership on Mobility from Poverty, February 8, 2018, https://www.mobilitypartnership.org/helping-young-children-move-out-poverty-creating-new-type-rental-voucher.

[25] In 2017, the median poverty rate of communities where poor children using vouchers lived was 24.2 percent, slightly higher than the comparable rate for all poor children of 22.9 percent, according to CBPP analysis of the 2012-2016 American Community Survey. (In contrast, the median neighborhood poverty rate for all children is 12.5 percent.) Among poor children using vouchers, 12.4 percent lived in low-poverty neighborhoods (poverty rate of less than 10 percent), compared with 11.9 percent of all poor children. See Appendix Tables A-4 and A-5. The racial and ethnic composition of these two groups, however, differ significantly. For example, poor non-Hispanic white, Asian, and Pacific Islander children — who typically live in lower-poverty neighborhoods than other poor children — make up 34.2 percent of all poor children but only 21.2 percent of poor children using vouchers.

[26] In 2017, 13.6 percent of families with children using vouchers lived in low-poverty neighborhoods, compared to 3.9 percent of those in public housing and 6.4 percent of those in privately owned units with project-based rental assistance. Also, families using vouchers were substantially less likely to live in extreme-poverty neighborhoods compared to families in public housing or project-based rental assistance: 13.8 percent of families using Housing Choice Vouchers lived in extreme-poverty neighborhoods, whereas 36.6 percent of family-occupied public housing units and 25.3 percent of family-occupied, privately owned units with project-based assistance were located in extreme-poverty neighborhoods. See Appendix Table A-1.

[27] See Appendix Tables A-3, A-4, and A-5.

[28] See Appendix Tables A-4 and A-5. There is little difference between the share of all poor Hispanic children who live in extremely poor neighborhoods and the share of poor Hispanic children with vouchers who live in these neighborhoods: 15.9 percent of the former live in neighborhoods with a poverty rate of 40 percent or more, compared with 15.6 percent of the latter.

[29] A third of children with vouchers (33.8 percent) live in high-poverty or extreme-poverty neighborhoods, with a poverty rate of 30 percent or more. See Appendix Table A-2.

[30] For example, in St. Louis, 64 percent of families with vouchers offered the option of receiving services from the housing mobility program expressed interest. A nonprofit, Ascend STL Inc., operates the mobility program in partnership with the St. Louis City and County Housing Authorities. Ascend STL Inc., “Mobility Connection Year End Report, 2017,” https://www.ascendstl.org/reports. Housing mobility program administrators in Chicago and Dallas also report strong interest in their voluntary programs, where recruitment generally occurs at the voucher briefing. Jennifer Darrah and Stefanie DeLuca, “Living Here has Changed My Whole Perspective”: How Escaping Inner‐City Poverty Shapes Neighborhood and Housing Choice,” Journal of Policy Analysis and Management, March 2014, pp. 350-384.

[31] Mary Cunningham, et al., “A Pilot Study of Landlord Acceptance of Housing Choice Vouchers: Executive Summary,” HUD, August 2018, https://www.huduser.gov/portal//portal/sites/default/files/pdf/ExecSumm-Landlord-Acceptance-of-Housing-Choice-Vouchers.pdf; Stefanie DeLuca, Philip M. Garboden, and Peter Rosenblatt, “Segregating Shelter: How Housing Policies Shape the Residential Locations of Low-Income Minority Families,” ANNALS of the American Academy of Political and Social Science, April 2013, pp. 268-299.

[32]Ibid.

[33] HUD rules require agencies to provide information to families when they first receive a voucher about their choices of where to live, and to explain the advantages of moving to an area that does not have a high concentration of poor families. See 24 C.F.R. §982.301. But agencies aren’t required to provide actual assistance to families to find a suitable unit, though HUD’s Housing Choice Voucher Program Guidebook includes some reasons why agencies may find it in their interest to do so. HUD Handbook 7420.10G, chapters 2-9.

[34] HUD measures the performance of agencies in administering the HCV program through the Section 8 Management Assistance Program, known as SEMAP. As discussed below, only a very small share of the points available under SEMAP relate to housing location, and the measures are weakly defined. See below regarding agencies’ duties to further fair housing.

[35] Kirk McClure, “Which Metropolitan Areas Work Best for Poverty Deconcentration with Housing Choice Vouchers,” Cityscape (2013), pp. 209-236.

[36] Alicia Mazzara and Brian Knudsen, “Where Families with Children Use Housing Vouchers: A Comparative Look at the 50 Largest Metropolitan Areas,” Center on Budget and Policy Priorities, forthcoming.

[37] Mobility Works and Poverty & Race Research Action Council, “Housing Mobility Programs in the United States,” forthcoming September 2018.

[38] Some of these programs are new. For example, the Seattle and King County Housing Authorities began implementing a rigorous randomized control trial in the fall of 2017 to determine what types of interventions are most cost effective in helping voucher holders access low-poverty areas. (See https://www.seattlehousing.org/creating-moves-to-opportunity-seattle-king-county-pilot-project-fact-sheet.) There are three large scale housing mobility programs, in Dallas, Chicago, and Baltimore. Each began as the result of fair housing litigation, and each has reported significant success in moving substantial number of families to much lower-poverty, predominantly non-minority communities. For example, the Baltimore program reports that for families that moved using a voucher for the first time in 2010 or later, the average pre-move poverty rate was 28.4 percent, while the average post-move poverty rate was 6.9 percent. The program has strong retention results as well: as of June 2018, 70 percent of all families in the program remain in opportunity areas and the average neighborhood poverty rate is 10.6 percent. (BRHP administrative data obtained August 2018.) For more information on these three programs, see Barbara Sard and Douglas Rice, “Realizing the Housing Voucher Program’s Potential to Enable Families to Move to Better Neighborhoods,” Center on Budget and Policy Priorities, January 12, 2016, https://www.cbpp.org/research/housing/realizing-the-housing-voucher-programs-potential-to-enable-families-to-move-to. Other agencies have self-funded mobility initiatives through administrative fees, funds earned from other activities such as developer fees, funds awarded through litigation, and funds made possible by the flexibility to reallocate resources for agencies participating in the Moving to Work demonstration. HUD has also made at least two small awards of discretionary administrative fees for regional mobility initiatives.

[39] A HUD-sponsored study found that in 2013–2014, only about half of the sampled housing agencies devoted any staff time to expanding housing opportunities for families, and none deployed significant staff resources. Jennifer Turnham et al., “Housing Choice Voucher Program: Administrative Fee Study,” Abt Associates, August 2015, https://www.huduser.gov/portal/publications/pdf/AdminFeeStudy_2015.pdf.

[40] The Mobility Works consortium — a group of mobility practitioners, researchers, and policy experts — has been in contact with about a dozen public housing agencies across the country that are interested in developing voucher mobility programs. Some of these emerging programs are underway, but some are not yet serving families. For more information see: www.housingmobility.org.

[41] Speaking on the House floor, Rep. Duffy said: “We know that low-income children whose families move to areas of lower poverty have higher earnings as adults. We must eliminate the cycle of poverty that keeps generations of families living within the same area with a limited amount of opportunity. Helping people move to better opportunities will increase the chances for them to achieve academic success and reduce intergenerational poverty.” Rep. Cleaver echoed those remarks and added: “This bill should pass. . . . All you have to do is read the Harvard research project from Raj Chetty, Nathaniel Hendren, and Lawrence Katz, which spoke about the improved opportunities for children based on their location. Higher opportunity neighborhoods offer just about everything that we would want a child to have growing up in this country.” See 164 Cong. Rec. H6010, daily ed., July 10, 2018, https://www.congress.gov/congressional-record/2018/07/10/house-section/article/H6010-1.

[42] Alicia Mazzara, Barbara Sard, and Douglas Rice, “Rental Assistance to Families with Children at Lowest Point in Decade,” Center on Budget and Policy Priorities, October 18, 2016, https://www.cbpp.org/research/housing/rental-assistance-to-families-with-children-at-lowest-point-in-decade.

[43] Center on Budget and Policy Priorities, “Proposed Housing Mobility Demonstration Would Improve Families’ Access to High-Opportunity Areas,” July 18, 2018, https://www.cbpp.org/sites/default/files/atoms/files/5-31-18hous_0.pdf.

[44] The 2019 funding bill for HUD that the Senate approved in August 2018 doesn’t include funds for a voucher mobility demonstration. Senators Todd Young (R-IN) and Chris Van Hollen (D-MD) have introduced a bill, S. 2945, to authorize the demonstration, as the House-passed bill (H.R. 5793) would do.

[45] Sard, Cunningham, Greenstein, 2018. The US Partnership on Mobility from Poverty recommends creating an additional 500,000 housing vouchers for families with children, phased in over five years. The vouchers would be targeted on low-income, high-need families with young children and would include funding for services to help families move out of poverty, including mobility counseling and home visiting.

[46] Although HUD convened a group of housing mobility practitioners, researchers, and agencies in early 2016 that many attendees found productive (see https://www.hud.gov/program_offices/public_indian_housing/programs/hcv/mobilityresources), much more could be done to share information and recommended policy changes to promote better locational outcomes for voucher holders.

[47] Agency fees are primarily based on the number of vouchers in use. Leasing units in high-opportunity areas typically takes longer than leasing in neighborhoods where vouchers are commonly accepted. Cunningham, et al., 2018. A fee incentive would help balance agencies’ current financial interest in having families locate units as quickly as possible.

[48] HUD, Housing Choice Voucher Program – New Administrative Fee Formula: Proposed Rule, 81 FR 44099, July 6, 2016; Turnham et al. As noted above, this study found that agencies spent no significant time on landlord outreach or other mobility services, and thus didn’t incorporate the costs of such services in its proposed new fee formula.

[49] The Trump Administration’s most recent regulatory agenda does not include action on this proposal. See Office of Management and Budget, Office of Information and Regulatory Affairs, Agency Rule List – Spring 2018, Department of Housing and Urban Development, www.reginfo.gov.

[50] HUD has authority under its current rule (24 C.F.R. §982.152(a)(iii)(C)) to provide supplemental fees for “extraordinary costs,” which HUD uses to provide a $200 bonus to a housing agency for each family that buys a home while participating in the HCV program.

[51] Under SEMAP, only five out of the 135 points that agencies in metropolitan areas are eligible to receive concern adoption and implementation of policies to “expand housing opportunities,” which HUD defines as encouraging participation of landlords located outside areas of poverty or minority concentration and providing information to voucher holders about such opportunities. 24 C.F.R. § 985.3(g). (Metropolitan agencies required to operate a Family Self-Sufficiency program may earn a total of 145 points.) Agencies can earn an additional five points if half or more of HCV families with children live in “low-poverty” census tracts or the share of families living in such areas increases by 2 percent or more. HUD defines “low poverty” for this purpose as a poverty rate of 10 percent or less, or at or below the overall poverty rate in the agency’s primary service area, whichever is higher (see 24 C.F.R. §985.3(h)). As of 2012, only 166 of the 1,403 agencies operating in metropolitan areas claimed these additional five points (CBPP calculation of HUD SEMAP data).

[52] Recent HUD-sponsored research uses a multi-factor measure of opportunity area, which results in an overall composite index. The composite index includes four unique indicators: percent nonpoor, public school quality, employment access, and environmental hazards. Meryl Finkel et al., “Small Area Fair Market Rent Demonstration Evaluation: Interim Report,” prepared for U.S. Department of Housing and Urban Development, August 2017, https://www.huduser.gov/portal/publications/SAFMR-Interim-Report.html. See also Mazzara and Knudsen, forthcoming.

[53] Philip Garboden et al., “Urban Landlords and the Housing Choice Voucher Program: A Research Report,” HUD, May 2018, https://www.huduser.gov/portal/sites/default/files/pdf/Urban-Landlords-HCV-Program.pdf.

[54] HUD, Affirmatively Furthering Fair Housing Final Rule, 80 Fed. Reg. 42272 (July 16, 2015).

[55]Ibid.

[56] HUD, Affirmatively Furthering Fair Housing: Streamlining and Enhancements, 83 FR 40713 (August 16, 2018).

[57] HUD, Affirmatively Furthering Fair Housing, 83 FR 23927, May 23, 2018; 24 CFR 903.7(o), Civil rights certification.

[58] See Appendix Table A-3.

[59] Rothstein, 2017, op. cit.

[60] Will Fischer, “Trump Administration Blocks Housing Voucher Policy That Would Expand Opportunity and Reduce Costs,” Center on Budget and Policy Priorities, September 7, 2017, https://www.cbpp.org/research/housing/trump-administration-blocks-housing-voucher-policy-that-would-expand-opportunity.

[61] Sensibly, the SAFMR rule allows agencies outside of the mandatory areas to use SAFMRs voluntarily. Agencies that are not required to implement SAFMRs should consider whether adopting them would expand voucher holders’ access to low-poverty neighborhoods. Agencies are permitted to set payment standards based on SAFMRs in some or all of the higher-rent zip codes they serve without seeking HUD approval; they may also request HUD approval to fully adopt SAFMRs in place of metro FMRs. Will Fischer, “A Guide to Small Area Fair Market Rents (SAFMR),” Center on Budget and Policy Priorities and Poverty and Race Research Action Council, May 4, 2018, https://www.cbpp.org/research/housing/a-guide-to-small-area-fair-market-rents-safmrs.

[62] HUD, “PIH Notice 2018-01: Guidance on Recent Changes in Fair Market Rent (FMR), Payment Standard, and Rent Reasonableness Requirements in the Housing Choice Voucher Program,” January 17, 2018, https://www.hud.gov/sites/dfiles/PIH/documents/PIH-2018-01.pdf.

[63] HUD, “Implementation of the Federal Fiscal Year (FFY) 2018 Funding Provisions for the Housing Choice Voucher Program,” May 21, 2018, https://www.hud.gov/sites/dfiles/PIH/documents/pih2018-09.pdf. The notice allows agencies to apply for one-time funding for costs associated with adopting SAFMRs.

[64] DeLuca, Garboden, and Rosenblatt (2013); Poverty & Race Research Action Council, “Constraining Choice: The Role of Online Apartment Listing Services in the Housing Choice Voucher Program,” 2015, https://prrac.org/pdf/ConstrainingChoice.pdf; Eva Rosen, “Selection, matching and the rules of the game: Landlords and the geographic sorting of low-income renters,” Joint Center for Housing Studies, 2014, http://www.jchs.harvard.edu/sites/default/files/w14-11_rosen_0.pdf.

[65] 24 C.F.R. § 982.301(b)(11), effective September 21, 2015. 80 Fed. Reg. 50564, 50573, August 20, 2015.

[66] HUD also should evaluate whether listing units in high opportunity areas more prominently will help more families move to low-poverty neighborhoods. In Moving to Opportunity: The Story of an American Experiment to Fight Ghetto Poverty, (Oxford University Press, 2010), p. 233, Xavier de Souza Briggs, Susan J. Popkin, and John Goering emphasize the importance of strategies that would “change the default” of families staying in familiar neighborhoods, citing Richard Thaler and Cass Sunstein, Nudge: Improving decisions about health, wealth and happiness, Yale University Press, 2008.

[67] Some of the listing services focus on the “Section 8 market” while others provide broader listings. HUD initiated a complaint against Facebook alleging that the social media platform allows landlords and home sellers advertising on the site to engage in housing discrimination through targeting tools made available by Facebook. HUD, Housing Discrimination Complaint, Assistant Secretary for Fair Housing & Equal Opportunity v Facebook, August 17, 2018, https://www.hud.gov/sites/dfiles/PIH/documents/HUD_01-18-0323_Complaint.pdf.

[68] DeLuca, Garboden, and Rosenblatt, 2013, pp. 275-280. In most areas of the country, landlords may legally refuse to accept HCVs unless such a refusal can be proven to be a proxy for discrimination based on race, national origin, disability, or family status that is prohibited by the Fair Housing Act. Poverty & Race Research Action Council (PRRAC), “Expanding Choice: Practical Strategies for Building a Successful Housing Mobility Program: Appendix B: State, Local, and Federal Laws Barring Source-of-Income Discrimination,” June 19, 2018, https://www.prrac.org/pdf/AppendixB.pdf. A new HUD-funded study suggests that state or local laws prohibiting discrimination against voucher holders would increase landlord acceptance of vouchers. Mary Cunningham, et al., 2018, https://www.huduser.gov/portal//portal/sites/default/files/pdf/ExecSumm-Landlord-Acceptance-of-Housing-Choice-Vouchers.pdf.

[69] See 24 C.F.R. §982.303. Extensions are required as a reasonable accommodation to people with disabilities, and when families move to the jurisdiction of another agency (see 24 C.F.R. §982.355(c)(13). HUD’s current voucher form, which says, “Insert date sixty days after date,” may mislead agencies about their discretion to provide a longer initial search period.

[70] Barbara Sard and Deborah Thrope, “Consolidating Rental Assistance Administration Would Increase Efficiency and Expand Opportunity,” Center on Budget and Policy Priorities, April 11, 2016, https://www.cbpp.org/research/housing/consolidating-rental-assistance-administration-would-increase-efficiency-and-expand.

[71] For a discussion of the interrelationship between low-income and racially segregated neighborhoods and lower-quality schools in central cities and some older suburbs, see Xavier de Souza Briggs, “More Pluribus, Less Unum? The Changing Geography of Race and Opportunity,” in The Geography of Opportunity: Race and Housing Choice in Metropolitan America, Brookings Institution Press, 2005, pp. 3-87; Philip Tegeler and Michael Hilton, “Disrupting the Reciprocal Relationship Between Housing and School Segregation,” 2017, https://www.prrac.org/pdf/Disrupting_the_Reciprocal_Relationship_JCHS_chapter.pdf.

[72] Consolidation of housing agencies to form a single metro-wide agency could have greater benefits but also faces greater political hurdles; for many agencies, retaining their independent identity is a paramount concern. This makes it more likely that agencies would join a consortium to achieve administrative economies of scale than to formally consolidate with other agencies. Urban policy experts Bruce Katz of the Brookings Institution and Margery Austin Turner of the Urban Institute have issued a paper recommending regional voucher administration; see “Invest but Reform: Streamline Administration of Housing Choice Voucher Program,” Brookings Institution, September 2013, https://www.brookings.edu/research/invest-but-reform-streamline-administration-of-the-housing-choice-voucher-program/.

[73] FSS is a voluntary program that provides case management services to improve participants’ job prospects and earning potential, such as information on available child care, credit and money counseling, and educational or training programs in the community. It also provides escrow accounts into which the agency deposits the increased rent that a family pays as its earnings rise. Families that complete FSS may withdraw funds from these accounts for any purpose; many FSS graduates use their savings to purchase a home. Most of the roughly 75,000 families currently participating in FSS have vouchers. When a voucher family participating in FSS moves to another jurisdiction, they can only continue participating if the receiving agency has an FSS program and an available slot, or if the initial agency is willing to allow the family to continue in its FSS program. If neither option is workable, families must choose between moving to a higher-opportunity neighborhood that may be better for their children but forfeit their escrowed savings or staying in place while continuing working on the FSS contract. HUD could revise its FSS rules to broaden families’ options to remain in FSS regardless of where they move. The Housing Choice Voucher Mobility Demonstration discussed above would create an incentive for agencies to collaborate to overcome the current barriers to continued FSS participation for families wishing to move to a higher-opportunity community.

[74] According to HUD, in 2014 there were only eight consortia involving 35 agencies that administer the HCV program. HUD, Streamlining Requirements Applicable to Formation of Consortia by Public Housing Agencies, Proposed Rule, 79 Federal Register 40019, July 11, 2014.

[75] Economic Growth, Regulatory Relief and Consumer Protection Act, P.L. 115-174, Sec. 209(c).

[76]Ibid, Sec. 209(e).

[77] The two agencies must split administrative payments and transfer paperwork and funds unless the “receiving” agency “absorbs” the family into its own HCV program by giving the family a voucher it has available instead of serving a family on its waiting list.

[78] Research in Southern California has identified the portability process as a barrier for families and a disincentive for agencies to inform families of their right to move to other jurisdictions. Victoria Basolo, “Local response to federal changes in the housing voucher program: A case study of intraregional cooperation,” Housing Policy Debate, March 2010, pp. 143-168.

[79] One reason “sending” agencies need additional compensation is to encourage them to continually make families aware of their right to use their vouchers in another agency’s jurisdiction and offset their cost of doing so. In the final portability rule, HUD declined to require agencies to remind families about portability after the briefing when they first receive a voucher, stating that “HUD finds this initial briefing to be sufficient.” 80 Fed. Reg. 50570, August 20, 2015. It is not clear on what basis HUD made such a finding. Few families will remember details from the initial briefing that are not of immediate importance to them.

[80] HUD’s proposed rule on administrative fees would provide 100 percent of the fee to the receiving agency, up from 80 percent under the current rule, and allow the initial agency to maintain 20 percent of the fee. HUD, Housing Choice Voucher Program – New Administrative Fee Formula, 81 FR 44099, July 6, 2016.

[81] U.S. Housing Act of 1937, 42 U.S.C. § 1437a(6)(B)(iii) (2006).