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A Roadmap to Reducing Child Poverty (2019)

Chapter: 8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs

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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Page 253
Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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Suggested Citation:"8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.
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8 Contextual Factors That Influence the Effects of Anti-Poverty Policies and Programs WHY CONTEXT MATTERS A fundamental lesson from the social and the behavioral sciences is that the context of people’s lives can affect their behavior in profound ways. Poverty itself is a powerful context because of its economic, physical, social, and psychological dimensions. In Chapter 3, we documented the adverse consequences for children of living in poverty, as well as the severe con- straints and stressors that inadequate financial resources place on families. Those constraints and stressors may in turn result in difficult choices and circumstances for both parents and children. In this chapter, we consider a more general set of contextual factors that can promote or impede the effectiveness of anti-poverty policies and pro- grams. For example, Supplemental Nutrition Assistance Program (SNAP) payments can best promote children’s nutrition and health when families have ready access to healthy and affordable food, and families can further benefit more from cash transfers when convenient and receptive banking institutions are available to help them manage their funds. Conversely, a job training program for parents may be less effective if there is racial dis- crimination in hiring, if there is an absence of employment opportunities, reliable transportation, or affordable child care options, or if parents are too disabled or sick to attend training. Given the potential for such contextual factors to influence the effec- tiveness of programs and policies, it is surprising to our committee how little rigorous empirical research has been conducted to test these factors’ moderating influence. Nevertheless, a strong empirical case can be made 227

228 A ROADMAP TO REDUCING CHILD POVERTY that these contextual factors influence decision-making in low-income fam- ilies as well as the impact of consequential programs and policies. Note that because the committee’s charge is confined to a 10-year period, we refrain from addressing several structural factors—including race and gen- der attitudes, perceptions of the poor, and the formerly incarcerated—that might generate longer-run impacts on the success and equity of program administration. SIX MAJOR CONTEXTUAL FACTORS Through internal discussions, public information-gathering sessions, and a review of the scholarly and policy literatures, the committee iden- tified six major, often co-occurring contextual factors that policy makers and program administrators are advised to consider when designing and implementing anti-poverty programs of the sort discussed in Chapters 5, 6, and 7: 1. Stability and predictability of income—Unstable and unpredict- able income makes it difficult for families to juggle everyday chal- lenges, diminishes the quality of everyday decisions, and renders the poor vulnerable to financial ruin. 2. Equitable and ready access to programs—Because of cumbersome, inconsistent, or demeaning enrollment procedures, or because of other barriers, not all families who qualify for benefits from gov- ernment programs receive them. 3. Racial/ethnic discrimination—Our nation’s long and painful his- tory of discrimination persists today in many forms and continues to influence differential access to opportunities and resources to overcome poverty, including employment, education, and housing opportunities. 4. Equitable treatment by the criminal justice system—Unequal treat- ment in legal penalties and law enforcement has disproportionately affected low-income families, especially Black and Hispanic fami- lies, in ways that disrupt family and social networks and reduce the economic and psychological resources that people who have been incarcerated could otherwise provide to their families. 5. Positive neighborhood conditions—Supportive, thriving social net- works and neighborhood conditions enrich family life, personal connections, and access to opportunities, yet too frequently people who live in poverty are concentrated in neglected urban areas or are widely dispersed in rural areas with limited transportation or access to employment, poverty-reduction programs, or community resources.

CONTEXTUAL FACTORS 229 6. Health and well-being—Among parents, physical and mental ail- ments, substance abuse, and domestic violence can harm their ability to make sound decisions, care for their children, become educated, obtain and keep work, and support their households. The chapter summarizes why each of these six contextual factors mat- ters, how each of them might affect the administration of anti-poverty policies, and what conclusions the committee has reached. Research rec- ommendations on these contextual factors are provided in the final chapter. INCOME STABILITY AND PREDICTABILITY Why It Matters An adequate and stable monthly family income enables parents to pay bills, meet basic needs, and engage in financial planning. When savings or access to affordable emergency resources are added to that, they can help buffer families against income shortfalls. But low-income families typically lack liquid assets and often pay high interest rates to obtain short-term credit (Barr, 2012). The resulting income instability can generate other kinds of instability—in housing and child care, for example—that in turn may limit families’ ability to work (Hahn et al., 2016; McKernan, Ratcliffe, and Vinopal, 2009) and compromise their children’s development (Hill et al., 2013). Because the savings and assets of Black and Hispanic families, at all income levels, are often considerably lower than those of White families, these populations are more vulnerable than White families to unpredictable changes in income (Kochhar and Cilluffo, 2017). Research has provided ample evidence of these differences in financial stability, and of their consequences. For example, the incomes of low earn- ers are more unstable than those of higher earners, and many lower-wage jobs offer little job security, fluctuating work hours, and no paid time off, which makes it difficult to budget and pay for dependable child care (Enchautegui, 2013; Gennetian and Shafir, 2015). Additionally, unexpected financial emergencies are ubiquitous among low-income households (Barr, 2009), and often require deferring bills or cutting spending on basic neces- sities, such as food. Approximately 9 percent of all children live in house- holds in which one or more child is food insecure. Food security is defined as “access by all people at all times to enough food for an active, healthy life” (Coleman-Jensen et al., 2017, pg. 2). Another important set of factors creating employment instability is the nature of the low-wage labor market and the difficulties many low-wage workers have in maintaining employment. Many low-wage jobs have high rates of turnover that create frequent periods of unemployment and require

230 A ROADMAP TO REDUCING CHILD POVERTY looking repeatedly for new jobs. Low-wage jobs are also more likely to have irregular hours and require shift work that low-income parents have difficulty sustaining (Enchautegui, 2013; Enchautegui, Johnson, and Gelatt, 2015). Transportation can pose challenges for low-income parents if they do not live close to work and have to take public transportation, which is unreliable and often includes extremely long commutes (Enchautegui, 2013; Holzer and Wissoker, 2001). Compounding these problems are difficulties in obtaining reliable and flexible child care that can respond to these irreg- ular shifts, long commutes, and high-turnover jobs (Enchautegui, 2013). Taken together, low-income families face a multitude of barriers to work that middle-income families do not face to the same degree (Enchautegui, 2013; Hill et al., 2013). More than one-half of all low-income families are asset-poor, defined as lacking the liquid resources necessary to finance essential consumption for 3 months (Lusardi, Schneider, and Tufano, 2011). Related to this, in recent years, due to their limited financial reserves one in four U.S. house- holds has used at least one alternative financial service, such as a payday, auto title, or refund anticipation loan, during the preceding year—services that are typically subject to very high interest rates (Burhouse et al., 2014; Caskey, 2006). Finally, more than one-half of all low-income families living in rental housing spend more than one-half of their income on housing costs (Desmond, 2016). Most of these problems are worse for racial/ethnic minority families, largely because of differences in wealth or assets minus debt (Kochhar and Cilluffo, 2017; Pew Charitable Trusts, 2015) and more limited options in terms of neighborhoods in which they can live. The combination of unstable incomes, high fixed expenses, and low savings translates into persistent material hardship for many low-income families, as adverse events challenge their ability to meet basic living needs. These families have little “slack,” defined by Mullainathan and Shafir (2013) as the ease with which one can cut down on other expenses to sat- isfy an unexpected need. When better-off families experience a rough patch of income instability, they typically have discretionary expenses they can cut back on and savings or access to credit to tide them over. In contrast, when low-income families face unanticipated shocks, they first cut back on somewhat less urgent needs, such as certain foods and the bills that are least likely to produce dire consequences if left unpaid. They then must cut back on essentials, which means skipping payments and incurring costly late fees, utility or phone reconnection fees, and eviction threats, and consequently they face a new round of disruptions to work, child care, education, and family life (Barr, 2009; Edin and Lein, 1997; Shipler, 2004).

CONTEXTUAL FACTORS 231 Relationship to Policy The unstable circumstances faced by the families of children living in poverty have significant implications for the design of benefit programs. Programs such as SNAP and Housing Choice Vouchers aim to fulfill basic needs by providing monthly benefits. In the case of SNAP, the long, 4-week intervals between benefits, coupled with income instability, lead recipi- ent families to overspend early in the benefit period and run short at the end (Hamrick and Andrews, 2016). Distributing SNAP benefits at weekly intervals might be more helpful to many families. For example, research- ers have found lower achievement test scores among children of families receiving SNAP benefits when those tests were taken near the end of the benefit month (Castellari et al., 2017; Gassman-Pines and Bellows, 2018). Experimentation with weekly versus monthly benefit payments would help guide policy in this case. Moreover, although the Earned Income Tax Credit (EITC) can help families pay down debt or purchase needed durables by providing credits annually as a lump sum (Halpern-Meekin et al., 2015; Mendenhall et al., 2012), some families may need the credit to meet basic expenses and may therefore benefit from more frequent payments.1 Other program design features to consider are the ease of determining eligibility and the frequency with which renewal is required. For example, when the subsidy authorization period for child care subsidies was expanded from 6 to 12 months, families made use of the subsidies for which they were eligible for 2.5 months longer, on average (Michalopoulos, Lundquist, and ­ Castells, 2010). Other studies have examined the administrative burden on families related to eligibility assessment, documentation, and scheduling and transportation issues. Research has shown that when these burdens are high, unpredictable (yet highly frequent) changes in family circumstances, such as job loss, moving, or a change in child care providers, can lead to a family abruptly losing its child care subsidy (Adams and Rohacek, 2010; Holcomb et al., 2006; Joshi et al., 2018). Abrupt subsidy losses of that kind can make finding or holding a job more difficult. Programs that provide emergency assistance can help prevent low-­ income families from falling deeper into poverty when unexpected financial problems occur (Pavetti, Schott, and Lower-Basch, 2011). For example, the Temporary Assistance to Needy Families (TANF) program provides emer- gency grants so that families at risk of losing the ability to work can repair a vehicle or pay rent without having to turn to public assistance over the longer term. However, in 2013, only 2 percent of TANF spending was on “nonrecurrent short-term benefits” or emergency spending (Schott, Pavetti, 1 For example, see the discussion in Chapter 7 of American Indian families and the discus- sion in Holt (2015) regarding periodic EITC benefit payments.

232 A ROADMAP TO REDUCING CHILD POVERTY and Floyd, 2015). Moreover, the asset limits set on many government assis- tance programs prohibit parents from saving money for emergencies or pur- chasing items, such as a reliable car, that can facilitate work and help move their family out of poverty, without the risk of losing the benefit (Campbell, 2014). States have the flexibility to set asset limits for most programs, and across states there is considerable variation in this regard. Public officials have a responsibility to ensure that families only receive benefits during the time period for which they are eligible, and short renewal periods for programs are a useful mechanism for carrying out that responsibility. However, low-income families’ eligibility may change rapidly with a loss or addition of a job or household member. Eligibility periods that are too short may leave families with such fluctuating circumstances more vulnerable than necessary and make it difficult for parents to move out of poverty. School meal programs have moved to an annual eligibility determina- tion, rather than requiring parents to report any time their income rises above the cutoff. This means that when children become eligible, they remain eligible for the whole school year. In addition, school districts have many options for directly certifying children who, for example, receive SNAP, so that they can also be eligible for the school lunch program with- out even applying. This sort of streamlining of eligibility requirements and using eligibility for one program as proof of eligibility for another could be a model for other programs (Currie, 2008).2 In the context of SNAP, longer periods between recertification have consistently been associated with higher rates of take-up and lower rates of drop-off, among eligible families (Hanratty, 2006; Ratcliffe, McKernan, and Finegold, 2007;  Wilde et al., 2000). Research has also shown that simplification of the certification process increases the participation rate (Kaushal and Gao, 2011). Furthermore, replacing paper vouchers with Electronic Benefit Transfer (EBT) cards, which look and operate like pre- paid debit cards and, in this way, feel quite mainstream and reduce potential stigma, increased participation (Kabbani and Wilde, 2003;  Kaushal and Gao, 2011; Kornfeld, 2002; Wilde et al., 2000).  Another policy consideration related to instability is that participation in public programs can be hindered by income instability. To take maximal advantage of work supports like the EITC and child care subsidies, par- ents need to be able to sustain steady employment. The barriers to such employment, discussed above, also generate barriers to receiving the public program benefits of work-encouraging programs. Participation in child care 2 For other examples of steps that have been taken to improve access to school meals, see https:// www.cbpp.org/research/key-steps-to-improve-access-to-free-and-reduced-price-school-meals.

CONTEXTUAL FACTORS 233 programs is particularly problematic if child care usage is sporadic and unstable, which typically reduces take-up of child care subsidies. CONCLUSION 8-1: Income instability, a paucity of savings, and little or no cushion for responding to unexpected financial difficulties are typical for many low-income families, and are more prevalent among Black and Hispanic families than among their White counterparts. Programs that provide regular income support, whether through tax credits, cash, or vouchers, may be more helpful to families if they pro- vide adequate benefits at well-timed intervals. Further, programs that are easily accessible and that facilitate savings or provide emergency cash assistance or credit at a modest cost can help families cope with unexpected emergencies and may prevent them from falling deeper into poverty. EQUITABLE AND READY ACCESS TO PROGRAMS Why It Matters Creating programs to reduce poverty through legislation does not, in itself, ensure equal program access to all families who qualify. If people are to participate in these programs, they need to understand them and then they need to be able to navigate the enrollment process. Often the bureau- cratic systems that underpin enrollment are cumbersome, and they vary considerably both by program and even within the same program across different states. The receipt of benefits may even be more a function of where a family lives than of the family’s need. For example, SNAP participation rates vary greatly across states, from an estimated low of 59 percent of eligible families to an estimated high of 100 percent (Gray and Cunnyngham, 2016). Some of this variation has been shown to be a function of enrollment requirements that are easier in some states than in others; 47 states allow families to apply for SNAP online, while the others require the recipient to fill out a paper application at a local office (Currie and Grogger, 2001).3 Such variation in adminis- trative procedures can lead to considerable variation in participation rates among eligible families for anti-poverty programs across states, and even within states participation rates can differ markedly by the applicant’s race, ethnicity, and other characteristics (Moore, Perez-Lopez, and Hisnanick, 2017). 3 Information about SNAP benefits and enrollment requirements is provided on the United States Department of Agriculture’s Food and Nutrition Service website, see https://www.fns. usda.gov/snap/facts-about-snap.

234 A ROADMAP TO REDUCING CHILD POVERTY The state in which a family lives may also determine the level of benefits families receive. For example, monthly TANF payments to a family vary from a low of $170 in Mississippi to a high of $1,021 in New Hampshire, and these differences are not fully accounted for by the variation in the cost of living across states (Floyd, 2017). Moreover, some states supplement fed- eral programs, whereas others do not; 26 states have their own version of the EITC, increasing the benefit families receive (Internal Revenue Service, 2018b). A study comparing the availability of assistance programs across states following the 1996 federal welfare reforms found that states fell into one of five package-support clusters, which ranged from minimal (with low inclusion rates and below-average support) to integrated (with generous and highly inclusive support packages) (Meyers, Gornick, and Peck, 2001). Naturally, such “contextual” variation can have a profound influence on the potential success of federal programs. Furthermore, there is real concern that the application of programs can be biased—whether intentionally or unintentionally. For example, it has been argued that long-acting, reversible birth control methods like intrauterine devices and implants, as tools for fighting poverty are more likely to be recommended to Black and Latina women of low socioeconomic status than to White women of the same status (Dehlendorf et al., 2010) In some cases, access for certain groups, such as immigrants or felons, is limited by a program’s design. An example can be found in the 1996 wel- fare reform legislation, the Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA), which was designed to create a separate eligibility regime for legal immigrants to limit their access to means-tested federal programs. Under this law, income-eligible documented immigrants who have been in the United States for less than 5 years are ineligible for the primary federal means-tested programs (SNAP, TANF, Supplemental Security Income [SSI], and Medicaid) unless they have 40 quarters of work history in the United States or have a military connection. PRWORA also gave states discretion over immigrant eligibility after the 5-year period of ineligibility. Moreover, while citizen children of undocu- mented immigrants who are income-eligible can receive government bene- fits, when fears of deportation are high undocumented parents are hesitant to apply for benefits for their American children (Alsan and Yang, 2018; Capps et al., 2004). Even legal immigrants who are income-eligible may be reluctant to apply for anti-poverty programs for themselves or their children due to the fear of being deemed a “public charge,” which may jeopardize their ability to become permanent residents or become U.S. ­ citizens (Batalova, Fix, and Greenberg, 2018; Perreira, Yoshikawa, and ­ berlander, 2018). Hispanic families bear the brunt of these kinds of O restrictions (Child Trends, 2014).

CONTEXTUAL FACTORS 235 Even if access were not problematic, program participation is often limited because funding is insufficient to provide benefits to all eligible fam- ilies. For example, the Housing Choice Voucher Program (often called the Section 8 program) is available to only about 15 percent of income-­ ligible e families with children (Joshi et al., 2014). Moreover, the federal Child Care and Development Fund supports only 17 percent of eligible children.4 Relationship to Policy As discussed above, state policies vary widely in the administrative burdens and requirements they impose on parents in anti-poverty programs, and states experience widely differing rates of participation in the programs (e.g., Holcomb et al., 2003). Data compiled by the Center on Budget and Policy Priorities indicate that many states are taking advantage of auto- mated technology so that people can more easily apply for assistance, update relevant information (e.g., changes in earnings), and renew their eligibility online (Wagner and Huguelet, 2016). Florida’s public assistance program, Automated Community Connection to Economic Self-Sufficiency (ACCESS), provides an example of a program that increases efficiency in the enrollment process (Cody et al., 2010).5 Key features of the Florida program include automating the public assistance application process and providing for online submission of applications for TANF, SNAP, and Medicaid (Cody et al., 2010). Other states have also turned to automation to streamline eligibility processes and increase program access, but wide variation in application processes across states and counties remains a sig- nificant factor limiting the participation of eligible families in many places (Isaacs, Katz, and Amin, 2016; Loprest, Gearing, and Kassabian, 2016). Work Support Strategies (WSS), a privately funded multistate initia- tive, is another example of how automation can improve the uptake of public assistance programs. The WSS initiative, which began in 2011, was developed to determine whether the implementation of technology improvements could better help qualifying families connect to work support programs (Isaacs, Katz, and Amin, 2016; Loprest, Gearing, and Kassabian, 2016). Evaluations suggest that using automated processes to streamline enrollment has resulted in time and money savings for both the applicants and the states. For example, in addition to reductions in lobby wait times in Colorado, Idaho, Illinois, and Rhode Island, individual participants gained an average of $195 annually in benefits, and one state, Idaho, reduced annual administrative costs by an estimated $53,500 (Isaacs, Katz, and Amin, 2016). 4 Congressional Research Service, as reported in the Committee on Ways and Means’ Green Book (Congressional Research Service, 2016), Chapter 9, Figure 9.5. 5 See http://www.myflorida.com/accessflorida for more information on ACCESS Florida.

236 A ROADMAP TO REDUCING CHILD POVERTY Training caseworkers to more effectively communicate and work with the families they serve may also improve the chances that parents will obtain steady employment. Caseworker training may also improve the chances that parents are informed about valuable services, such as child care subsidies (Strawn and Martinson, 2000). Federal rules have sought to establish minimum standards for access to information to help eligible families determine which benefits they qualify to receive. For example, SNAP regulations require applications and notices to be available in lan- guages other than English when specific population thresholds are met.6 How effective such rules are in facilitating access to benefits is not known, however. Other efforts to increase access to benefits and better coordinate and streamline services have been tried in many states (Annie E. Casey Foun- dation, 2010; Hoffman, 2006). Rigorous evaluations of the pilot programs would better inform states as to how to ensure that parents who are eligible for programs actually receive the benefits. One program that has worked to minimize the administrative burden on eligible participants is the EITC. Because it is administered through the tax code rather than through a social services office, it does not require repeated sign-ups throughout the year or a lengthy and complicated appli- cation process. Eligible persons must simply fill out their tax returns. Take-up rates have improved over time as commercial tax preparers have increasingly served this market, and more organizations have begun to help lower-income workers file their taxes (Kopczuk and Pop-Eleches, 2007), although commercial tax preparers charge large fees and remove their fees before their clients receive their refunds. The Internal Revenue Service has also provided specific information for tax preparers to help reduce errors (Internal Revenue Service, 2018c). CONCLUSION 8-2: Unnecessarily burdensome administrative proce- dures can discourage families from applying for, and thus prevent them from receiving, income assistance program benefits for which they are otherwise eligible. State-by-state variation in the implementation of fed- eral policies can lead to inconsistencies in access among eligible families and to variation in the efficacy of anti-poverty programs. CONCLUSION 8-3: Federal rules such as limits on the eligibility of documented immigrants and measures that discourage program use (e.g., “public charge” determination) reduce access to means-tested pro- grams for entire groups, even for individuals who meet income-­ ligibility e requirements. These rules may harm both citizen and immigrant children 6 Specifically, Code of Federal Regulations item 7CFR 272.4.

CONTEXTUAL FACTORS 237 in such families by reducing the benefits available to them, with a dis- proportionate impact on racial and ethnic minority families. RACIAL/ETHNIC DISCRIMINATION Why It Matters A substantial body of social science research shows that large racial/ ethnic disparities persist in U.S. society in access to education, employment, housing, and health care, as well as in equitable treatment in the civil and criminal justice systems (Pager and Shepherd, 2008). Discrimination and unequal access to resources can lead to social policies being less effective for parents who are racial/ethnic minorities. Employment and housing provide two examples. Discrimination in hiring makes it more difficult for parents from a racial/ethnic minority group to obtain employment and therefore to benefit from policies aimed at supporting low-wage workers or to maintain eligibility for programs that require beneficiaries to work (Bertrand and Mullainathan, 2004; Holzer, Raphael, and Stoll, 2006; Stoll, Raphael, and Holzer, 2004). Discrimination by landlords renders policies to expand housing less effective for parents who are members of racial/ethnic minorities and may expose these families to greater housing instability and the risk of homelessness (Desmond, 2016). Even for individuals with similar levels of education, racial/ethnic minorities have higher rates of unemployment and lower earnings than Whites (Pew Research Center, 2016), with Black unemployment rates typi- cally twice as high as White unemployment rates (U.S. Bureau of Labor Sta- tistics, 2018a). Black and Hispanic employment is also more vulnerable to downturns in the economic cycle and takes longer to recover (U.S. Bureau of Labor Statistics, 2018b). Moreover, Black and Hispanic families have on average one-sixth of the wealth of their White counterparts (McKernan et al., 2013). While not all of the racial/ethnic differences in employment, earnings, and asset accumulation can be attributed directly to discrimination, compel- ling evidence suggests that discrimination plays a continuing role, particu- larly for employment, and to a lesser degree for wages (Pager and Shepherd, 2008). For example, among job applicants, Whites receive 36 percent more requests to advance in the hiring process (callbacks), on average, than equally qualified Black applicants and 24 percent more callbacks than equally qualified Hispanic applicants (Quillian et al., 2017). Callback rates for Black and Hispanic males without a criminal record are lower than for Whites with a criminal record (Pager, Western, and Bonikowski, 2009). Discrimination against racial/ethnic minorities also persists in hous- ing. Rigorous studies sponsored by the U.S. Department of Housing and

238 A ROADMAP TO REDUCING CHILD POVERTY Urban Development (HUD) find that while racial/ethnic discrimination in both rental and sales markets has declined over the past 40 years, Blacks, Hispanics, and Asians seeking housing continue to be informed of and shown fewer housing units than their White counterparts (Turner et al., 2013). For example, one paired-testing study, which sampled 8,000 quali- fied apartment home-seekers across 28 states, found that for every 25 visits, Black home-seekers were shown one unit fewer than White home-seekers, while Hispanic home-seekers were shown one unit fewer for every 14 visits (Turner et al., 2013). As discussed above, provisions that limit legal immigrants’ eligibility for anti-poverty programs even when they would qualify based on income are discriminatory by program design. Relationship to Policy Discrimination against racial/ethnic minorities in the labor and hous- ing markets can limit the effectiveness of anti-poverty programs in several ways. For example, the Housing Choice Voucher program sets a time limit on voucher-subsidized housing searches—typically 60 days (U.S. Depart- ment of Housing and Urban Development, 2015). Families unable to locate qualifying housing within that amount of time must return the vouchers. Consequently, if minority families seeking to move are shown fewer units than majority families, as Turner et al. (2013) found, this may result in lower levels of program take-up. Further, if minority families are steered toward housing in neighborhoods with access to fewer job opportunities, then housing subsidy programs will be less successful in promoting eco- nomic mobility. Indeed, research has found that White families receiving Housing Choice vouchers are more likely to find rental units in low-poverty neigh- borhoods (those with poverty rates under 10%) with higher-performing schools than are Black and Hispanic families seeking the same (Horn, Ellen, and Schwartz, 2014; McClure, Schwartz, and Taghavi, 2015). Therefore, even when different families receive a housing subsidy that is comparable in monetary value, nonmonetary factors such as social ties, reliable infor- mation, and housing discrimination (associated with prevailing residential segregation patterns) may reduce the ability of Black and Hispanic families to translate their monetary benefit into better outcomes in employment and well-being. Discrimination in the operation of anti-poverty programs themselves may also reduce the benefit these programs offer to people who belong to racial/ethnic minorities. In an examination of six types of federal pro- grams (TANF, child care subsidies, Head Start, child support enforcement, programs for homeless and runaway youth, and adolescent pregnancy

CONTEXTUAL FACTORS 239 prevention programs), McDaniel et al. (2017) concluded that employment discrimination, as well as the organization and delivery of the programs themselves, results in racial/ethnic inequities in access to the programs and, consequently, in program outcomes. For example, evidence indicates that TANF case workers are more likely to offer work supports, such as child care, to White TANF recipients than to Black or Hispanic recipients, which may make it more difficult for the latter to find or sustain employment (McDaniel et al., 2017). CONCLUSION 8-5: Past and current racial/ethnic discrimination have contributed to substantial disparities in access to employment and housing. Discrimination in hiring and employment may undermine policies that aim to increase or subsidize wages and policies that require beneficiaries to work. Housing discrimination reduces racial/ethnic minority families’ access to and benefits from housing programs. CRIMINAL JUSTICE SYSTEM INVOLVEMENT Why It Matters As of 2015, some 2.8 percent of the U.S. adult population was either incarcerated (2.2 million adults) or on probation or parole (4.7 million adults) (Kaeble and Glaze, 2016; Kaeble and Bonczar, 2016). Although these figures have declined since their peak in 2007–2008, it remains the case that millions of Americans have close connections to people who are in prison or otherwise involved with the criminal justice system (Kaeble and Glaze, 2016; Kaeble and Bonczar, 2016; Lee et al. 2015). In 2015, 7 percent of non-Hispanic White children had a parent who was ever incarcerated, compared with 16 percent of Black children and 8 percent of Hispanic children.7 Such racial/ethnic differences persist even after controlling for parents’ educational attainment. For example, among children born in 1990 whose fathers were high school dropouts, the cumu- lative risk of paternal incarceration by the time the child reached age 14 was 50.5 percent for Black children, but only 7.2 percent for White children (Wildeman, 2009). Racial/ethnic differences in involvement with the criminal justice system can be attributed to several factors, including disproportionality in school discipline, differential involvement in delinquency, criminal case characteris- tics, and unequal treatment in the criminal justice system (Donnelly, 2018). 7 For more information, see https://datacenter.kidscount.org/data/tables/9734-children-who- had-a-parent-who-was-ever-incarcerated-by-race-and-ethnicity#detailed/1/any/false/1539/10, 11,9,12,1,13/18995,18996.

240 A ROADMAP TO REDUCING CHILD POVERTY In a recent quasi-experimental study, Arnold and colleagues (forthcoming) found that inexperienced and part-time judges in Miami and Philadelphia were more likely to make racially biased prediction errors when imposing bail amounts. Racial/ethnic disparities, however, can be seen through- out the various stages of the criminal justice process (National Research Council, 2014). An example from a recent consensus report issued by the National Research Council is that, for similar crimes, sentences issued for Blacks are more likely to be on the higher end of sentencing guidelines, whereas sentences for Whites tend to be toward the lower end. Further, the report committee found that both Blacks and Hispanics are more likely than Whites to be detained before trial, which has been shown to increase the chances that the defendant will receive a prison sentence (National Research Council, 2014). According to a recent report by the U.S. Commission on Civil Rights (2017), the fines and fees levied against individuals for even minor crimes can cause low-income families to sink into debt, which can be difficult to escape. The same report also found that these fees were often targeted at communities of color and low-income individuals (U.S. Commission on Civil Rights, 2017). The net effect of these disparities is that Black and Hispanic children are more vulnerable to the economic, social, and psychological adversities associated with having an incarcerated parent. Reviewing the most rigorous studies on the effect of parental incarceration on children’s behavioral prob- lems, academic achievement, and delinquency, Wildeman, Wakefield, and Turney (2013) found that paternal incarceration has consistently negative effects on child well-being and that the effects are greater than if the father were merely absent from the household (e.g., due to divorce). Research suggests that the effects of maternal incarceration are depen- dent on the behavior of the mother. For example, if a mother consistently placed her child in dangerous or stressful situations prior to being impris- oned, child outcomes may improve after incarceration. Children who were not exposed to dangerous or stressful situations may experience negative outcomes when the mother is incarcerated (Wildeman and Turney, 2014). Hagan and Foster (2015) have found higher rates of food insecurity and economic insecurity (inability to pay for rent or mortgage, telephone, and utilities) among families with adolescents who were experiencing or had experienced paternal or maternal imprisonment. Relationship to Policy Incarcerated parents face challenges in supporting their children eco- nomically and psychologically (Turney and Goodsell, 2018). Moreover, the incarceration of one parent puts added stress on the nonincarcerated parent

CONTEXTUAL FACTORS 241 (National Research Council, 2014). However, the release of an incarcerated parent does not end the adverse effects, because a record of incarceration substantially reduces the parent’s ability to work (Looney and Turner, 2018) and to find housing (Keene et al., 2018) and reduces eligibility for public services (Sugie, 2012). The lower levels of educational achievement of par- ents who enter prison may also reduce their chances of gaining employment after release (Looney and Turner, 2018). Accordingly, programs that aim to increase or supplement earnings or require beneficiaries to work, such as the EITC, may be less effective for families in which a parent has been incarcerated, unless efforts are made to reduce barriers to employment for these parents. Although the level of evidence in this area is slim, programs for which there is some evidence of effectiveness include training to recognize bias on the part of employers in the recruitment and hiring of staff (Carnes et al., 2015; Devine et al., 2012); readily accessible procedures to expunge records of criminal offenses committed as juveniles (Selbin, McCrary, and Epstein, 2018); and proactive assistance for newly released convicts in obtaining employment (Broadus et al., 2016). Reforms directed at these problems can sometimes backfire, however. Recently, several states and municipalities have passed laws to “ban the box,” meaning they prohibit employers from asking about applicants’ criminal history. There is some evidence that employers undercut the effec- tiveness of such laws by discriminating against all of the applicants in the larger groups that are statistically more likely to have a criminal history. For example, employers may automatically screen out names that appear to be Black or Hispanic (Agan and Starr, 2018; Doleac and Hansen, 2016). Social policies that exclude felons from receiving benefits may have developed with both punishment and deterrence in mind. A consequence of these policies, however, is that children in these families are (often unin- tentionally) denied benefits that are extended to other children in otherwise identical economic circumstances. The 1996 welfare reform imposed a lifetime ban on the receipt of TANF and SNAP for individuals with a drug felony conviction, except in states that opt out of the ban. The children of parents with a felony drug conviction are still eligible for SNAP benefits; however, by reducing the total amount of SNAP benefits a family receives as a result of these bans, families living in poverty may not be able to purchase the amount of food needed to maintain good health. To date, 37 states have implemented a full or modified ban on the receipt of TANF benefits for drug felons and 34 states have done so for SNAP benefits as well (Mauer and McCalmont, 2015). Individuals with a drug conviction also lose their eligibility for college financial aid (U.S. Department of Education, 2019), and Housing Choice Voucher housing assistance is not available to ex-convicts (who are not

242 A ROADMAP TO REDUCING CHILD POVERTY members of a protected class under anti-discrimination laws) unless local housing authorities choose to allow them to qualify (Curtis, Garlington, and Schottenfeld, 2013). Given the large racial disparity in criminal justice involvement (Lyons and Pettit, 2011), and specifically in drug-related con- victions (National Research Council, 2014, pp. 91-97), these reductions in public benefits particularly penalize Black families and limit the ability of incarcerated and previously incarcerated parents to support their children (either privately or through the child support system) or to enable their children to rise out of poverty (Sugie, 2012, pp. 3-4). CONCLUSION 8-6: Involvement of a parent or other relative with the criminal justice system harms significant numbers of low-income children, particularly minority children, both economically and in other ways. Prior incarceration may render some parents ineligible for ben- efits that could reduce child poverty and leave them unable to secure housing or work and thus provide for their children. NEIGHBORHOOD CONDITIONS Why It Matters Neighborhood conditions—particularly those associated with high con- centrations of families living in poverty—are a potentially important con- text both for families and children and for the anti-poverty programs that serve them. As the county-based information presented in Chapter 2 makes clear, high-poverty areas—defined as census tracts (neighborhoods of about 4,000 people) with an official poverty rate of 20 percent or more—exist all over the United States. Census data show that the adult residents of these neighborhoods are more likely than residents of low-poverty areas to lack a high school diploma, to be unemployed, to be separated or never-married, to be single parents, and to rent rather than own a home (Bishaw, 2014, Table 2a). Additionally, levels of child development, educational outcomes, psy- chological well-being, and health are all worse among children living in high-poverty neighborhoods than among other children (Leventhal, Dupere, and Shuey, 2015). At the same time, as noted concerning the associations between family-based poverty and child outcomes discussed in Chapter 3, it is difficult to disentangle correlation and causation in the associations between neighborhood-based poverty and child outcomes (Gennetian et al. 2012; Sanbonmatsu et al., 2006). Moreover, the effects of neighborhood poverty seem to depend on when children were exposed over the life course (Chetty, 2015).

CONTEXTUAL FACTORS 243 Neighborhood conditions are associated with a person’s ability to move out of poverty. Areas with lower levels of intergenerational mobility are characterized by greater residential segregation by race and income, higher income inequality, poorer quality K–12 schools, weaker measures of social networks and community involvement, and weaker family structures (as measured by the prevalence of single parents) (Chetty et al., 2014). Lack of intergenerational mobility is highest among Black families liv- ing in high-poverty neighborhoods. Chetty et al. (2018) found that White and Hispanic families are more likely than Black families to move up in the income distribution across generations. Moreover, the few geographic areas in which Black-White mobility gaps were found to be relatively small tended to be low-poverty neighborhoods where Whites had low levels of racial bias and Blacks grew up with their fathers present. However, fewer than 5 percent of Black children, as compared with 63 percent of White children, grow up in areas with poverty rates below 10 percent and where more than one-half of fathers are present. The role of past de jure discrimination should not be overlooked. High levels of current racial/ethnic residential segregation have been shaped by historical discrimination in housing policy and lending, such as redlining in the mortgage market and segregation in public housing, as well as by current zoning regulations (Rothstein, 2017). Segregation in turn has led to a disproportionate share of racial/ethnic minority families living in high-­ poverty neighborhoods intergenerationally (Sharkey 2008, 2013). Relationship to Policy Policies that aim to increase access to nutrition, housing, or employ- ment are likely to be less effective in places that lack the resources or social networks to support them. For example, families who live in high-poverty neighborhoods tend to eat substantially less nutritious food than their coun- terparts in low-poverty areas. Although socioeconomic status and limited access to nutritious food in high-poverty areas contribute to unhealthy eating, the vast part of this difference is explained by the concentration of lower levels of education and knowledge about the value of healthy eating in high-poverty neighborhoods as compared to lower-poverty neighborhoods (Allcott, Diamond, and Dube, 2018; Handbury, Rahkovsky, and Schnell, 2015). Thus, the SNAP program may be more effective at increasing nutri- tional outcomes for families who live in high-poverty neighborhoods if the program is coupled with counseling or education about how to choose and prepare healthy food. States have access to grant funding for such pro- grams through the Supplemental Nutrition Assistance Program—Education

244 A ROADMAP TO REDUCING CHILD POVERTY (SNAP-Ed) initiative.8 While not all states have chosen to implement nutri- tion education programs, a recent evaluation of the SNAP-Ed program by the Research Triangle Institute suggests that they have the potential to encourage low-income families to make healthier food choices (Hersey et al., 2014). Geographic location can also play a significant role in creating environ- ments that help break the cycle of intergenerational poverty. In particular, access to high-quality educational experiences, which integrate students from various socioeconomic backgrounds, can improve the likelihood of future success (Rothwell and Massey, 2014). Housing programs can also have a considerable effect on the level of neighborhood poverty that families experience. The Moving to Opportu- nity (MTO) experiment, discussed in Chapter 3, demonstrated that offer- ing housing vouchers to families to move to low-poverty neighborhoods (those with less than 10 percent of residents in poverty) led to a reduc- tion in neighborhood poverty by 20 percentage points for families that took up the offer (Gennetian et al., 2012). Although the decrease in their experience of neighborhood poverty led to virtually no improvements in MTO-­ articipating children’s well-being in the short term (Sanbonmatsu p et al., 2006; Gennetian et al., 2012), the subset of children who moved ­ to a lower-poverty neighborhood at a young age (before age 13) showed longer-term benefits in their college and labor market outcomes (Chetty, 2015). Thus housing programs may be made more effective by targeting families with younger children in high-poverty neighborhoods, as long as the program does not have enough funding to serve all families. The MTO experiment and corresponding Three-City Study (Cove et al. 2008; Orr et al., 2003) also provide insight into the employment effects on parents of moving from a high-poverty neighborhood to a lower-poverty neighborhood. The effects of this experiment on employment were gener- ally weak and showed that it was difficult for many families to integrate into lower-poverty neighborhoods and take advantage of new social net- works and employment opportunities. Thus, policies that require a parent to work to receive benefits may be less effective for families with limited social networks or access to resources. Rural areas have distinctly different needs where poverty is concerned. Low-income families in some of the nation’s rural areas face substantial burdens to employment because of extremely limited public transportation and child care options (Whitener, Duncan, and Weber, 2002). Families in these areas will not benefit from work-based policies in the same way that families with better access to employment will. These rural families may 8 For more information on the SNAP-Ed program, please see https://snaped.fns.usda.gov.

CONTEXTUAL FACTORS 245 benefit more from income supports that are not based on employment, such as child allowances or child support assurance. CONCLUSION 8-7: Living in areas of concentrated poverty makes it difficult for parents to lift their children out of poverty; poor Black and Hispanic families face a considerably higher risk of concentrated neighborhood poverty and other forms of neighborhood disadvantage than poor White families. HEALTH AND DISABILITY Why It Matters Across the United States, as in other countries, people living in poverty tend to have worse health than the rest of the population. In the case of U.S. children, this so-called health gradient grows steeper across childhood and adolescence (Case, Lubotsky, and Paxson, 2002), although the gradient has grown flatter in recent years with the expansion of Medicaid coverage for young children (Currie, Decker, and Lin, 2008). In adulthood, the gradient is steeper still: Adults (ages 18 and older) living in poverty in the United States were almost four times as likely in 2016 to report that they were in fair or poor health (28.2%)9 as adults with family incomes above twice the official poverty line (7.76%),10 and in 2014–2015 they were several times more likely to report serious psychological distress during the past 30 days (8% vs. less than 2%).11 According to the National Council on Disability, approximately 4.1 million parents in the United States live with disabilities, and their number is increasing (National Council on Disability, 2012). Of these 4.1 million parents, 52 percent receive SSI. The Social Security Administration main- tains an extensive list of impairments12 that it has judged to be severe enough to limit or prevent an individual’s ability to work. Some examples include cystic fibrosis, multiple sclerosis, cerebral palsy, traumatic brain injury, and schizophrenia (Social Security Administration, 2018). Parents with work-limiting impairments such as these are twice as likely to be  9 National Center for Health Statistics, Summary Statistics: National Health Interview Survey, Table A-11a, https://ftp.cdc.gov/pub/Health_Statistics/NCHS/NHIS/SHS/2016_SHS_ Table_A-11.pdf. 10 National Center for Health Statistics, Summary Statistics: National Health Interview Survey, Table A-11a, https://ftp.cdc.gov/pub/Health_Statistics/NCHS/NHIS/SHS/2016_SHS_ Table_A-11.pdf. 11 National Center for Health Statistics, Health, United States, 2016, Table 46 (page 1 of 2). 12 For a complete list of qualifying impairments, see https://www.ssa.gov/disability/­ professionals/bluebook/listing-impairments.htm.

246 A ROADMAP TO REDUCING CHILD POVERTY unemployed (48% compared to 22%) and three times as likely to live in poverty as those without disabilities (National Council on Disability, 2012). Regardless of their own health, parents living below the federal pov- erty level may have to care for children with physical or mental health conditions or disabilities, which can affect the parents’ employability and increase stress on the family (Carlson, Keith-Jennings, and Chaudhry, 2017). According to a secondary analysis of data collected for the National Health Interview Survey (NHIS) from 2001 to 2011, children living in pov- erty are more likely than other children to have a disability. Results from this analysis also show that the number of children with disabilities living below 100 percent of the federal poverty level increased by 10.7 percent between 2001 to 2011 (Houtrow et al., 2014). Some family members may have to reduce the number of hours they work or stop work altogether to care for relatives with disabilities, which can place an additional strain on family finances (Rupp and Ressler, 2009). This difficult balance between work and caregiving can be especially challenging for single parents (Rupp and Ressler, 2009). Furthermore, the costs related to caring for a family member with a disability may also create a significant financial burden (Carlson, Keith-­ Jennings, and Chaudhry, 2017; Stabile and Allin, 2012). An analysis of the period 1996 to 2004 found that people with disabilities had significantly higher health expenditures when compared to those without disabilities13 (Mitra, Findley, and Sambamoorthi, 2009). Moreover, a more recent exam- ination of administrative and survey data suggests that families with chil- dren with disabilities are less likely than other families with children to visit the doctor, more likely to delay paying bills and rent, and more likely to require food assistance14 (Carlson, Keith-Jennings, and Chaudhry, 2017). Impacts on the health, employability, and quality of life for persons living with a disability are often further exacerbated if they are Black or Hispanic, are older, have low educational attainment, or are living in pov- erty (Ross and Bateman, 2018). As an example, Blacks and Native Amer- icans with disabilities have the lowest employment rates (McGrew, Scott, and Madowitz, 2018). Mental health, developmental, and intellectual disabilities can also cre- ate significant barriers to employment (Luciano and Meara, 2014; National Council on Disability, 2012). An analysis of data from 2009 and 2010 found that individuals with a diagnosed mental illness were less likely to work, and 39 percent of those who identified as having a serious mental 13 This was a secondary analysis of the nationally representative Medical Expenditure Panel Survey (MEPS) collected from 1996 to 2004. 14 This was an analysis of SNAP administrative data and National Health Interview Survey data.

CONTEXTUAL FACTORS 247 illness had incomes below $10,00015 (Luciano and Meara, 2014). How- ever, this last analysis also found that when these individuals received employment services such as vocational counseling, their employment rates doubled (Luciano and Meara, 2014). Other studies suggest that families that care for ill or disabled members have an increased risk of emotional, mental, and physical health problems, including increased levels of depres- sion and anxiety.16 Substance abuse is also linked to lower levels of employment and wages, although the causal pathway may work in several directions. Adults who abuse drugs or alcohol may seek less work or be less qualified for well-paying jobs (Terza and Vechnak, 2007). Alternatively, the loss of employment or stress of low wages may lead to greater use of substances as a coping mechanism (Badel and Greaney, 2013). Also, injuries that initially limit a person’s ability to work may lead to a growing dependency on pain medication (i.e., opioids) that further reduces the person’s ability to work or care for himself or herself (National Institute on Drug Abuse, 2018). Relationship to Policy A key question for policy is the extent to which poor health is the primary cause of lower employment and earnings, as opposed to poverty causing poor health.17 However, the fact that health and income are so highly correlated suggests that programs that condition receipt of benefits on employment or that are intended to increase or supplement earnings will not help poor parents who are unable to sustain stable employment due to poor health or a disability. According to a recent National Council on Disability (2012) report, additional family and work supports such as assistance for child care, transportation, and job training may help parents living with disabilities comply with TANF work requirements. Low-income families in which the parents have disabilities that prevent them from main- taining full-time, stable employment are also less likely to be eligible for family and medical leave and less likely to be able to afford to take leave when eligible (Mathur et al., 2017). Further, while the Family and Medical Leave Act guarantees job protection for eligible workers who need to take leave for up to 12 weeks, it does not include wage replacement.18 Lack of leave time places people with disabilities at extreme risk, because they may 15 Based on data collected from the National Survey on Drug Use and Health between 2009 and 2010. 16 For more information, see https://www.caregiver.org/caregiver-health. 17 For reviews of the literature, see Cutler, Lleras-Muney, and Vogl (2008); Evans, Wolfe, and Adler (2012). 18 For more information about the Family and Medical Leave Act, see https://www.dol.gov/ whd/fmla.

248 A ROADMAP TO REDUCING CHILD POVERTY experience sporadic health flare-ups or need time off for medical appoint- ments (Vallas, Fremstad, and Ekman, 2015). Vocational rehabilitation programs have been shown to be effective in helping adults with mental or physical health challenges find and maintain employment (Cullen et al., 2017; Graham et al., 2016; Suijkerbuijk et al., 2017). Despite this, little has been done to connect low-income parents to most of these programs (Farrell et al., 2013; Farrell and Walter, 2013). A recent study conducted by the Office of Planning, Research, and Evaluation at the U.S. Department of Health and Human Services found that there is often only limited collaboration between TANF agencies and Social Security Administration agencies (Farrell et al., 2013). One of the most successful programs included in the study—Families Achieving Success Today, in Ramsey County, Minnesota—found that participants were more likely to receive vocational rehabilitation services and obtain employment than members of the control group and that on average they earned $1,235 more in the first year (Farrell et al., 2013), although this amount may not be enough to enable a family to rise out of poverty. CONCLUSION 8-8: Because parents who are in poor health or caring for a child in poor health may be less able to work and care for them- selves or their children, anti-poverty programs that require employment to maintain eligibility or that have cumbersome eligibility requirements may be less effective for these families. REFERENCES Adams, G., and Rohacek, M.H. (2010). Child Care Instability: Definitions, Context, and Policy Implications. Washington, DC: The Urban Institute. Agan, A., and Starr, S. (2018). Ban the box, criminal records, and racial discrimination: A field experiment. The Quarterly Journal of Economics, 133(1), 191–235. Allcott, H., Diamond, R., and Dube, J.P. (2018). The Geography of Poverty and Nutrition: Food Deserts and Food Choices Across the United States. Cambridge, MA: National Bureau of Economic Research. Alsan, M., and Yang, C. (2018). Fear and the Safety Net: Evidence from Secure Communities. Cambridge, MA: National Bureau of Economic Research. Annie E. Casey Foundation. (2010). Improving Access to Public Benefits: Helping Eligible Individuals and Families Get the Income Supports They Need. Baltimore, MD: Annie E. Casey Foundation. Arnold, D., Dobbie, W., and Yang, C.S. (Forthcoming). Racial bias in bail decisions. Quarterly Journal of Economics. Badel, A., and Greaney, B. (2013). Exploring the link between drug use and job status in the U.S. Regional Economist, January 7. Available: https://www.stlouisfed.org/publications/ regional-economist.

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CONTEXTUAL FACTORS 255 Rupp, K., and Ressler, S. (2009). Family caregiving and employment among parents of chil- dren with disabilities on SSI. Journal of Vocational Rehabilitation, 30, 153–175. Sanbonmatsu, L., Kling, J.R., Duncan, G.J., and Brooks-Gunn, J. (2006). Neighborhoods and Academic Achievement: Results From the Moving to Opportunity Experiment. NBER Working Paper No. 11909. Cambridge, MA: National Bureau of Economic Research. Schott, L., Pavetti, L., and Floyd, I. (2015). How States Use Federal and State Funds Under the TANF Block Grant. Washington, DC: Center on Budget and Policy Priorities. Available: https://www.cbpp.org/sites/default/files/atoms/files/4-8-15tanf_0.pdf. Selbin, J., McCrary, J., and Epstein, J. (2018). Unmarked: Criminal record clearing and employment outcomes criminal law/criminology. The Journal of Criminal Law and Criminology, 108(1). Sharkey, P. (2008). The intergenerational transmission of context. American Journal of ­Sociology, 113(4), 931–969. ________. (2013). Stuck in Place: Urban Neighborhoods and the End of Progress Toward Racial Equality. Chicago, IL: University of Chicago Press. Shipler, D.K. (2004). The Working Poor: Invisible in America. New York, NY: Vintage. Social Security Administration. (2018). Disability Evaluation under Social Security: Part III— Listing of Impairments. Available: https://www.ssa.gov/disability/professionals/bluebook/ listing-impairments.htm. Stabile, M., and Allin, S. (2012). The economic cost of childhood disability. Future of Chil- dren, 22(1), 65–96. Stoll, M.A., Raphael, S., and Holzer, H.J. (2004). Black job applicants and the hiring officers’ race. Industrial and Labor Relations Review, 57(2), 267–287. Strawn, J., and Martinson, K. (2000). Steady Work and Better Jobs: How to Help Low-Income Parents Sustain Employment and Advance in the Workforce. New York, NY: MDRC. Sugie, N.F. (2012). Punishment and welfare: Paternal incarceration and families’ receipt of public assistance. Social Forces: A Scientific Medium of Social Study and Interpretation, 90(4), 1403–1427. Suijkerbuijk, Y.B., Schaafsma, F.G., van Mechelen, J.C., Ojajarvi, A., Corbiere, M., and Anema, J.R. (2017). Interventions for obtaining and maintaining employment in adults with severe mental illness, a network meta-analysis. Cochrane Database System Review, 9, CD011867. Terza, J.V., and Vechnak, P.B. (2007). The Effect of Substance Abuse on Employment Status. University Park: The Pennsylvania State University. Turner, M.A., Santos, R., Levy, D.K., Wissoker, D., Aranda, C., and Pitingolo, R. (2013). Housing Discrimination Against Racial and Ethnic Minorities 2012. Washington, DC: U.S. Department of Housing and Urban Development. Turney, K., and Goodsell, R. (2018). Parental incarceration and children’s wellbeing. The Future of Children, 28(1). U.S. Bureau of Labor Statistics (2018a). Table A-2. Employment Status of the Civilian Popula- tion by Race, Sex, and Age. Washington, DC: U.S. Bureau of Labor Statistics. Available: https://www.bls.gov/news.release/empsit.t02.htm. ________. (2018b). Labor Force Statistics from the Current Population Survey. August 30. Washington, DC: U.S. Bureau of Labor Statistics. Available: https://www.bls.gov/cps/ demographics.htm#race. U.S. Commission on Civil Rights. (2017). Targeted Fines and Fees Against Low-Income Com- munities of Color: Civil Rights and Constitutional Implications. Washington, DC: U.S. Commission on Civil Rights. U.S. Department of Education. (2019). Federal Student Aid: Students with Criminal Con- victions. Washington, DC: U.S. Department of Education. Available: https://studentaid. ed.gov/sa/eligibility/criminal-convictions#incarcerated.

256 A ROADMAP TO REDUCING CHILD POVERTY U.S. Department of Housing and Urban Development. (2015). Housing search and leasing. Chapter 8 in Housing Choice Voucher Program Guidebook. Washington, DC: U.S. Depart­ ent of Housing and Urban Development. m Vallas, R., Fremstad, S., and Ekman, L. (2015). A Fair Shot for Workers with Disabilities. Washington, DC: Center for American Progress. Available: https://www.americanprogress. org/issues/poverty/reports/2015/01/28/105520/a-fair-shot-for-workers-with-disabilities. Wagner, J., and Huguelet, A. (2016). Opportunities for States to Coordinate Medicaid and SNAP Renewals. Washington, DC: Center on Budget and Policy Priorities. Whitener, L., Duncan, G., and Weber, B. (2002). Reforming Welfare: What Does It Mean for Rural Areas? Washington, DC: U.S. Department of Agriculture. Wilde, P., Cook, P., Gundersen, C., Nord, M., and Tiehen, L. (2000). The Decline in Food Stamp Program Participation in the 1990s. Washington, DC: U.S. Department of Agri- culture, Economic Research Service. Wildeman, C. (2009). Parental imprisonment, the prison boom, and the concentration of childhood disadvantage. Demography, 46(2), 265–280. Wildeman, C., and Turney, K. (2014). Positive, negative, or null? The effects of maternal incarceration on children’s behavioral problems. Demography, 51(3), 1041–1068. Wildeman, C., Wakefield, S., and Turney, K. (2013). Misidentifying the effects of parental incarceration? A comment on Johnson and Easterling (2012). Journal of Marriage and Family, 75(1), 252–258.

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The strengths and abilities children develop from infancy through adolescence are crucial for their physical, emotional, and cognitive growth, which in turn help them to achieve success in school and to become responsible, economically self-sufficient, and healthy adults. Capable, responsible, and healthy adults are clearly the foundation of a well-functioning and prosperous society, yet America's future is not as secure as it could be because millions of American children live in families with incomes below the poverty line. A wealth of evidence suggests that a lack of adequate economic resources for families with children compromises these children’s ability to grow and achieve adult success, hurting them and the broader society.

A Roadmap to Reducing Child Poverty reviews the research on linkages between child poverty and child well-being, and analyzes the poverty-reducing effects of major assistance programs directed at children and families. This report also provides policy and program recommendations for reducing the number of children living in poverty in the United States by half within 10 years.

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