Most of the program and policy ideas featured in Chapters 5 and 6 are modifications and combinations of decades-old social programs that have been studied extensively by academic researchers and policy analysts. Their evidence makes it clear who uses these programs, how a given program interacts with other programs to affect child poverty, and how the work effort of parents changes in response to changes in the programs themselves. That knowledge has been incorporated into the Transfer Income Model, Version 3 (TRIM3), which was used to simulate the poverty-reduction effects of changes to the programs and packages of programs presented in Chapters 5 and 6.
This chapter is devoted to evidence-based program and policy ideas that were considered by the committee but, for a variety of reasons, were not chosen for inclusion in Chapters 5 and 6. For most of them, research evidence was not sufficiently strong to support predictions of the magnitude and, in some cases, even the direction of impacts on child poverty rates. In other cases, although the research suggested that a reform was likely to decrease the number of poor children, it was not feasible to simulate the magnitude of the effect.
Some of the programs the committee chose not to simulate relate to families, in particular family planning and structure, including marriage, as well as to paid family and medical leave. For other reforms, such as block grants, mandatory employment programs, and expansion of the Temporary Assistance for Needy Families (TANF) program, the evidence on poverty-reducing impacts is ambiguous or incomplete. For health insurance programs such as Medicaid, we were thwarted by serious poverty measurement
issues, which were raised in Chapter 2, are expanded on here, and are the subject of a paper commissioned by the committee (Korenman, Remler, and Hyson, 2017). Finally, we remind readers that many evidence-based program areas such as home visiting and early education may generate benefits that fall outside of the 10-year window dictated by our statement of task. These kinds of programs are not included in this or any other report chapters.
Although it was possible to estimate poverty reductions associated with the various program and policy options and combinations discussed in Chapters 5 and 6 for many demographic subgroups of interest, small sample sizes precluded reliable estimates for certain racial/ethnic groups, such as Asians and Pacific Islanders, American Indians, and Alaska Natives. This is a serious concern, particularly in the case of American Indian and Alaska Native (AIAN) children, whose poverty rates are very high. In the final section of this chapter, we use other sources of data, as well as findings from a paper the committee commissioned (Akee and Simeonova, 2017), to discuss policy issues involving AIAN children.
As we will note below, research has shown that unintended births are very common and that they have a high probability of leading to family incomes below the poverty line. Reducing unintended births is therefore an option often raised in discussions of how to reduce poverty. However, before reviewing the research on the issue and discussing the policy implications of that research, the committee considered the question of whether birth control should be used as a policy to reduce child poverty. Given the history in the United States of limiting the reproductive freedom of women, particularly low-income women and women of color (Gordon, 1976), any policy that aims to reduce unintended pregnancies may be construed as a policy designed to prevent poor women from having children. The committee strongly condemns any such coercive efforts and considers informed, voluntary access to effective contraception a basic health care right for women and men.
However, research shows large racial/ethnic differences in the implementation of expanded access to effective contraception among women of low socioeconomic status. One study found that low-socioeconomic status African American and Latina women have three times the odds of being offered long-acting reversible contraceptives as do their their low-socioeconomic status White counterparts (Dehlendorf et al., 2010), indicating that reproductive inequities may still exist. Thus, expanding
unbiased, voluntary, and informed access to the contraception options that women feel are best for them may be a sound policy objective in and of itself, as long as it is pursued with child poverty reduction as a secondary consequence and not the primary goal.
As background, in the United States, mothers report that nearly one-half of all their pregnancies and over one-third of births are unintended (Guttmacher Institute, 2016; Mosher, Jones, and Abma, 2012). The rate of unintentional births varies considerably by poverty status. Between 2006 and 2010, 46 percent of births to women with household incomes below the federal poverty line were reported as unintended, as compared with 18 percent of births to women with incomes more than four times higher than the poverty line (Mosher, Jones, and Abma, 2012). Furthermore, women who experience an unintended birth are likely to do so again in the future (Rajan et al., 2017).
Recent studies have found that unintended births often limit women’s economic mobility and increase the likelihood of poverty-level family incomes. Unintended pregnancies may prevent adolescents and young adults from earning a college degree and make it more difficult for them to obtain and keep stable, well-paying jobs (Sonfield et al., 2013; Waldfogel, 1998). Research also suggests that limited access to and awareness of effective birth control options makes unintended births more frequent, particularly among low-income women.
Might access to effective birth control methods reduce the child poverty rate? Using the FamilyScape 2.0 simulation model, Karpilow and his colleagues (2013) found that if 25 percent of women under age 30 who are not currently using any contraception were to begin using more effective hormonal contraception methods (such as intrauterine devices or implants), the poverty rate among newborns would be reduced by one-half of a percentage point in a single year. They estimate that a sustained 25 percent uptake for each subsequent cohort of younger women would reduce child poverty by at least 2 percentage points over the 10-year period. The reduction in child poverty might be even greater over this timeframe if the indirect effects of delaying pregnancy are considered. For example, if women delay pregnancy until they intend to give birth, they may seek more schooling or have better employment opportunities, which in turn may decrease the likelihood that their child will be born into poverty (Sawhill and Venator, 2015).
Implications for Policy
The research literature on unintended births has established three facts relevant to national policy on birth control methods that would reduce child poverty by allowing women who want to delay births to do so effectively. First, since a disproportionate share of unplanned pregnancies are
experienced by women living in poverty, any reduction in the incidence of unplanned pregnancies will lower the child poverty rate.
Second, highly effective means of birth control have been developed over the past two decades. Although the contraceptive pill afforded women and couples greater control over fertility, its impact on pregnancy prevention has been inconsistent, largely because many women have difficulty remembering to take the pill on a regular basis (Bailey, 2013). Intrauterine devices and subcutaneous forms of birth control, collectively referred to as long-acting reversible contraception (LARC), have been found to be 20 times as effective in preventing pregnancy as older methods of birth control, such as contraceptive pills and condoms (Winner et al., 2012).
Third, evidence suggests that increasing access to effective contraception can help reduce the number of unintended births. In 2009, Colorado launched its Colorado Family Planning Initiative with the goal of providing women with no-cost access to and information about the most effective forms of contraception, especially LARC (Colorado Department of Public Health and Environment, 2017). Over a 6-year period, the rate of LARC use quadrupled in Colorado Title X clinics,1 and the rate of unintended pregnancies declined by 40 percent among teens and by 20 percent among young women ages 20 to 24 (the two groups with the highest rates of unintended pregnancy). The average mother’s age at first birth also increased by 1.2 years in the state. In addition, the Colorado Family Planning Initiative saved a total of around $68 million in entitlement program costs (combining federal and state costs) for women ages 15 to 24 and their infants (Colorado Department of Public Health and Environment, 2017).
Training health center staff in proper contraceptive counseling techniques appears to be a promising way of helping women who wish to avoid pregnancy to use voluntary birth control more effectively. A recent national study of family planning clinics in the United States randomly assigned staff in 20 clinics to receive training in providing counseling and inserting IUDs or progestin implants on the same day when women came for advice and counseling about birth control and opted to try these methods; staff in 20 control-group clinics provided standard care. Researchers found that women receiving services from the experimental clinics were less than one-half as likely to become pregnant within the next 12 months (Harper et al., 2015).
In cooperation with local and state governments, Upstream USA2 trains clinic staff in effective methods for counseling women about available birth
1 Title X clinics are family planning clinics that provide family planning and related preventive health care services to low-income and uninsured individuals. See https://www.hhs.gov/opa/title-x-family-planning/about-title-x-grants/index.html for more information about Title X grants.
control options and provides information about how federal programs such as Title X and Medicaid can help clinics finance their operations. Working with Delaware’s state government, in 2014 Upstream USA carried out a statewide initiative aimed at increasing access to contraceptives. An evaluation of its efforts showed that among women ages 20 to 39 who were Delaware Title X family planning clients, use of LARC roughly doubled, from 14 to 27 percent, while use of less effective birth control measures, including the pill, the patch, and the ring, decreased substantially. These changes were projected to decrease the rate of unintended pregnancy among this population by 15 percentage points between 2014 and 2016 (Welti and Manlove, 2018).
These studies show that it is possible to increase access to and requests for LARC during a single regular visit to a health clinic, thereby reducing the rate of unintended pregnancy. Although the studies did not provide separate estimates for poor and nonpoor women, the fact that they identified very strong results among women using public clinics suggests that reducing unintended pregnancies might well be effective in reducing the child poverty rate. Research suggests, however, that it is possible for racial bias to influence clinician recommendations in contraceptive counseling sessions (Dehlendorf et al., 2010; Higgins, Kramer, and Ryder, 2016). Thus, the use of patient-centered care practices in health centers could be beneficial in protecting the reproductive autonomy of the women receiving counseling (Higgins, 2014).
In contrast to the positive outcomes that result from increased communication and training, policies that restrict women’s access to family planning services have led to reductions in the use of effective contraception and increases in the number of births (Fischer, Royer, and White, 2017; Lu and Slusky, 2016; Stevenson et al., 2016; Woo, Alamgir, and Potter, 2016). Texas provides a valuable case study. Between 2011 and 2014, the Texas state legislature substantially cut funding for women’s health programs, eliminated Planned Parenthood from fee-for-service programs, and significantly restricted access to abortion. Because of these policy changes, more than one-half of the abortion-providing women’s health clinics and a quarter of publicly funded family planning clinics in the state closed. Stevenson et al. (2016) found that the elimination of Planned Parenthood from the state’s family planning program was associated with a one-third reduction in Medicaid claims for LARC and a 1.9 percentage-point increase in Medicaid-related births in Texas (Stevenson et al., 2016).
CONCLUSION 7-1: Increasing both awareness of and access to effective, safe, and affordable long-acting reversible contraception (LARC) devices reduces the incidence of unplanned births, which could in turn reduce child poverty. In contrast, policies that reduce access to LARC
by cutting Medicaid, Title X funding of family planning services, or mandated contraceptive coverage appear to increase the number of unintended births and thus also child poverty.
The poverty rate for children in single-parent families is roughly five times the rate for children in married-couple families (Semega, Fontenot, and Kollar, 2017). Moreover, as detailed in Chapter 4, the rise of single-parent family structures and the increase in the number of births outside marriage played important roles in child poverty trends during the last quarter of the 20th century, although as discussed in earlier chapters they have become less important since 2000. Thus, policies that increase the share of children living in married-couple or other two-parent family structures are likely to reduce child poverty rates (Gibson-Davis, 2016). By the same token, existing policies with provisions that reduce marriage rates, even if unintentionally, are likely to increase child poverty.
Implications for Policy
Social scientists have conducted numerous studies to determine how various social policies might influence the decisions that teens and adults make about family composition (Lopoo and Raissian, 2014). Some of these studies have focused on the impacts on marriage of past and current safety-net policies, while others have evaluated attempts by the George W. Bush administration to increase the share of children living in two-parent households (whether the parents are married or not) (Haskins, 2015).
Much of the rigorous research that has been conducted on the effects of existing programs focuses on the Earned Income Tax Credit (EITC), Medicaid, and the TANF program (Moffitt, 2016). In the case of the EITC, a recent review (Nichols and Rothstein, 2016) describes how low-income couples with one wage earner are incentivized by the EITC to marry, while two-earner couples are effectively penalized for marrying if their joint income brings them above the EITC eligibility level. These kinds of effects are unavoidable in a tax system that taxes income at the family rather than the individual level.
Examining the expansion of the EITC in the 1990s, Eissa and Hoynes (2003) found changes in marriage rates that are consistent with these incentives, increasing marriage rates by 1 to 5 percentage points for families with incomes below $25,000 but reducing marriage rates by 1 percent for families with incomes between $25,000 and $75,000. Other studies have
found more uniformly negative impacts on marriage (e.g., Rosenbaum, 2000), while some have found null or very small effects (Dickert-Conlin and Houser, 2002; Ellwood, 2000; Herbst, 2011; Michelmore, 2018). Summarizing this literature, Nichols and Rothstein (2016) conclude only that links between the EITC and marriage are poorly understood.
The limited literature on Medicaid’s marriage effects has focused on changes in marriage in response to expansions of Medicaid coverage. Until the mid-1980s, the strong link between Medicaid and the Aid to Families with Dependent Children (AFDC) Program meant that most married couples were ineligible for Medicaid coverage (Buchmueller, Ham, and Shore-Sheppard, 2016). Yelowitz (1998) found that after the Medicaid expansions of the 1980s and 1990s, women whose children were all eligible for Medicaid were slightly (1.5%) more likely to be married than women with at least one ineligible child. However, at least some of that effect may have been due to choices about childbearing, and it is possible that some of the effect is actually accounted for by the EITC expansions (Meyer and Rosenbaum, 2001).
Most studies of the effect of the TANF program on marriage compare it with its predecessor, the AFDC program, which it replaced as part of the welfare reforms of the 1990s. Because TANF is a more restrictive program than AFDC, and because it greatly reduced the program caseload, the effect of the reform can be broadly interpreted as showing the effects of reducing the availability of welfare programs on marriage. Reviews of the literature in this area (Grogger and Karoly, 2005; Ziliak, 2016) find mixed evidence for any effect: A few studies find effects for some subgroups but not others, while other studies find no effects for any group. One of the higher-quality studies, by Dunifon, Hynes, and Peters (2009), highlights the murky nature of program results, finding few consistent effects of welfare policy measures on the likelihood that a child is living with married, cohabiting, or single parents.
Overall, the existing literature on marriage incentives and disincentives provides little reason to believe that current social policies have had a substantial impact.3 This may be because marriage, cohabitation, and divorce are affected by many economic and noneconomic factors other than transfer programs—including men’s employment and earnings levels, women’s employment potential, nonmarital birth rates (see above), and levels of community and family support, to name just a few.
In response to evidence suggesting that many low-income couples have a strong desire to marry but often do not because of financial and social
obstacles (Gibson-Davis, Edin, and McLanahan, 2005), the George W. Bush administration launched an ambitious effort to promote two-parent relationships and provided funding for the Administration for Children and Families to support rigorous evaluations of three different programs.
The Building Strong Families project developed and tested a number of voluntary programs that offered relationship-skills education and other support services to unmarried couples who were expecting or had just had a baby. Over the course of 3 years, more than 5,000 couples living in eight states participated in the evaluation of the Building Strong Families program, at an average program cost of about $11,000 per couple. A random-assignment evaluation found that the project had no overall effects on the quality of couples’ relationships, the chances that they would stay together or get married, their coparenting relationships, or their family incomes. Of the two statistically significant effects generated by the programs, one was negative (a reduction in some aspects of father involvement) and one was beneficial (a modest reduction in children’s behavioral problems). Couples in one of the eight program sites—Oklahoma City—were more likely to still be living together 3 years after the program began, but that effect did not appear to translate into improved child well-being (Wood et al., 2012).
The Supporting Healthy Marriage Program tested the effectiveness of a skills-based relationship education program designed to help low- and modest-income married couples strengthen their relationships and to support more stable and nurturing home environments. An evaluation showed that the program did not lead more couples to stay together and had little effect on indicators of coparenting, parenting, or child well-being. However, it did find a consistent pattern of modest but sustained positive impacts of the program on the quality of the couples’ relationships (Lundquist et al., 2014).
The Community Healthy Marriage Initiative was a community-level effort to improve relationship skills and promote healthy marriages. It brought together multiple stakeholders from a community to develop media campaigns, offer relationship courses, make service referrals, and in other ways attempt to generate a critical mass of community awareness and positive behaviors. An evaluation of the project showed no significant effects on community-level outcomes for parenting measures, awareness of the program, or marriage options and attitudes (Bir et al., 2012).
As compared with the discouraging results from these large-scale studies, a few smaller-scale studies have produced results that some analysts believe to be more hopeful (e.g., Frimmel, Halla, and Winter-Ebmer, 2012). Perhaps the most frequently mentioned is the evaluation of the Parents and
Children Together (PACT) Program (Avellar et al., 2018), which showed beneficial impacts on the participating couples’ relationship quality, conflict behavior, coparenting relationship, and marriage rates 1 year after the program ended. Although well conducted, this study has a few limitations. One is that all participating couples were already in long-term (5 years or longer) marital or co-habitation relationships at the beginning of the study, so the marriage impact in the PACT study was one of reducing breakups rather than increasing marriage rates. Also, in contrast to the longer-run follow-ups for the three Bush administration programs, results of the PACT evaluation were obtained after only 1 year of program participation, and it is commonplace for intervention impacts to fade out over time. The committee judged that findings like those from the PACT study, although interesting and potentially important, should not override our conclusions based on the results of well-conducted, longer-term studies like those in the Bush marriage initiative.
At the state level, a related policy initiative in the early 1990s involved the passage of laws streamlining the process of paternity establishment in hospitals at the time of the birth. Rossin-Slater (2017) finds that these laws substantially increased paternity establishment and also increased the amount of time that absent fathers spend with their children and the amount of money they spend with them as well. However, the laws had the unintended effect of reducing marriage rates. As a result of the decline in marriage among these mothers, the mothers were more likely to marry or cohabit with men who were older and had higher employment rates than the males with whom they had conceived their baby. Moreover, the fathers who would have married the mothers in the absence of these laws were less involved with the child than they would have been otherwise. Averaged across the entire sample of both married and unmarried parents, the effects of these laws on observable measures of fathers’ involvement with their children are either zero or negative.
CONCLUSION 7-2: Although increasing the proportion of children living with married or cohabiting parents, as opposed to single parents, would almost certainly reduce child poverty, the impacts of existing social programs designed to promote such a change are uncertain. Evidence from these programs is inconclusive and points to neither strong positive nor negative effects. In the early 2000s, an ambitious attempt to develop programs that would improve couple-relationship skills, promote marriage, and improve child well-being failed to boost marriage rates and achieve most of their other longer-run goals.
The unmet health needs of parents and children can compromise a family’s ability to sustain full-time employment and generate earnings sufficient to keep family income above the poverty line. As documented in Chapters 3 and 8, low-income children and adults are more likely than their higher-income counterparts to experience health problems (Case, Lubotsky, and Paxson, 2002; Centers for Disease Control and Prevention, 2013). Further, taking time off from work to care for a sick family member is a challenge for some low-income parents, as some may not be eligible for family and medical leave or have access to paid leave (Joshi et al., 2014; Mathur et al., 2017). When workers lack access to paid leave, families must choose between addressing health needs and continuing to work to earn income (Boushey, 2016). When these individuals do take leave, they forgo wage income, which can put them at risk of falling—or falling deeper—into poverty because of inadequate savings to accommodate financial disruptions (see Chapter 8).
The United States is the only nation among the 34 members of the Organisation for Economic Co-operation and Development (OECD) that does not guarantee paid leave to mothers of infants (Raub et al., 2018b), and it is one of only two OECD nations that does not guarantee leave for personal illness (Raub et al., 2018a). In most OECD countries, benefit levels (as determined by wage replacement rates) provide median wage earners with sufficient income to remain above the poverty line during paid leave, although fewer countries ensure benefits that allow minimum wage earners to remain above the poverty line (Bose et al., 2018).
Current U.S. family and medical leave policy comprises a variety of laws enacted at the federal, state, and local levels to provide for unpaid or paid leave; additionally, in some cases employers have adopted their own policies. The national policy governing family or medical leave is embodied in the Family and Medical Leave Act (FMLA), which entitles eligible employees (roughly one-half of all workers) to take unpaid, job-protected leave for family and medical reasons with continuing group health insurance coverage (Joshi et al., 2014; Klerman, Daley, and Pozniak, 2012). Hispanic workers are less likely to be eligible for unpaid FMLA than other workers, and both Black and Hispanic workers are less likely than other workers to be both eligible for and able to afford unpaid FMLA (Joshi et al., 2014).
Seven states and Washington, D.C., as well as more than 70 municipalities, have established paid family and medical leave for targeted populations (National Partnership for Women and Families, 2018a, 2018b).
Yet in 2016, only 6 percent of low-wage workers had access to employer-provided paid family leave, compared with 25 percent of higher-wage workers (Bureau of Labor Statistics, 2017).
Implications for Policy
Access to paid family and medical leave has the potential to reduce child poverty by increasing employment and improving maternal and child health, although the potential effects of paid family and medical leave on employment and wages are ambiguous (Klerman and Leibowitz, 1994; Olivetti and Petrongolo, 2017). Paid leave might reduce human capital by discouraging employers from hiring, leading to a decline in wages and employment. On the other hand, paid leave might increase job continuity for workers, which could result in higher wages and employment levels.
Likely impacts of paid family and medical leave on child poverty depend on their policy designs. Providing paid leave through a social insurance program could minimize employer costs and prevent wage and employment discrimination against individuals who are perceived as likely to take leave (Mathur et al., 2017). On the other hand, paid family and medical leave provided through an employer mandate might have no net effect on or even increase child poverty because employers might seek to reduce costs by avoiding hiring covered workers or workers they believe are likely to take leave (Mathur et al., 2017).
Some of the best U.S.-based evidence on the impacts of paid leave comes from California, which enacted a paid leave program that began in 2004. Under this program, workers are entitled to a maximum of 6 weeks’ leave to care for a newborn, an adopted child, or an ailing family member and are paid about 60 to 70 percent of their normal wages, up to a maximum benefit based on the state’s average weekly wage. A tax on all employees finances this program.
Evaluations of California’s Paid Family Leave policy have shown that it has generated positive impacts on continued parental employment, when compared with the counterfactual of no provision being made for parental leave.4 For example, the program made it more likely that mothers would return to work after childbirth (Baum and Ruhm, 2016) and increased labor force attachment around the time of childbirth (Byker, 2016). It increased leave-taking among mothers and fathers (Bartel et al., 2017; Rossin-Slater,
4 In 2016, California increased the weekly wage replacement percentage from approximately 55 percent to approximately 60-70 percent (from $50 to $1,216). The evaluations of California’s Paid Family Leave policy included in this chapter represent data collected prior to 2016. For more information on California’s Paid Family Leave policy, please see https://www.edd.ca.gov/disability/FAQ_PFL_Benefits.htm.
Ruhm, and Waldfogel, 2013) but also increased work hours for mothers 1 to 3 years after childbirth (Baum and Ruhm, 2016; Rossin-Slater et al., 2013). On the downside, one study of the program found that it was associated with an increase in unemployment among young women, both relative to men and older women in California and relative to young women, men, and older women in states without paid leave (Das and Polachek, 2015). This finding is consistent with Gruber (1994) who found that federal mandates that maternity benefits be included in health insurance plans reduced female employment.
Turning to employers, one study of the California Paid Family Leave policy suggests that it had no burdensome effects on employers’ wage costs. After matching paid leave and state disability insurance program data to employee and employer data from the California Employment Development Department, researchers found no evidence that an increase in the share of employees who take leave is associated with an increase in wage costs or a significant rise in employee turnover rates (Bedard and Rossin-Slater, 2016).
The California Paid Family Leave policy also produced changes associated with improved health. In particular, it doubled the average length of time women took for maternity leave, from 3 weeks to between 6 and 7 weeks, which can have a positive impact on infant health (Rossin-Slater et al., 2013). Two California studies found that paid family and medical leave has increased the incidence of breastfeeding relative to other states without such policies (Huang and Yang, 2015) and that children in early elementary school had positive health outcomes, such as a lower probability of being overweight, compared with the period before the introduction of paid leave (Lichtman-Sadot and Bell, 2017).
There are few methodologically strong studies of the direct impact of paid leave policies on child poverty, however. Studies that have examined California’s Paid Family Leave policy show positive effects on employment and wages (Baum and Ruhm, 2016; Rossin-Slater, Ruhm, and Waldfogel, 2013) but they have not isolated the effects of the policies on lower-income families.
CONCLUSION 7-3: Evidence suggests that paid family and medical leave increases parents’ ability to continue in employment and has positive impacts on children’s health, although it might also reduce employment among women potentially eligible for such leave. It is important to continue evaluating the labor market, health, and child-poverty impacts of states’ paid-leave laws.
Both common sense and a wealth of research, as documented in earlier chapters, point to increases in steady employment, wage rates, and earnings as among the strongest correlates of escaping poverty (Sawhill, Rodrigue, and Joo, 2016). Policies for increasing employment and earnings among the poor in order to help them escape poverty include efforts to build basic skills through education, government-sponsored training programs to help those pursuing specific skills (like the WorkAdvance Program featured in Chapter 5), work-related assistance such as child care subsidies, and purely financial incentives designed to work through the tax system, especially tax credits like the EITC. All of these have the potential to make a difference, and a large body of research evidence shows that many of them generate modest to substantial increases in employment and subsequent reductions in family poverty.5
This section focuses on another employment policy approach: mandatory employment programs for recipients of government transfers. Mandatory work programs have been attached to the TANF program, apply to some recipients of the Supplemental Nutrition Assistance Program (SNAP), have been tested in public housing in a few areas around the country, and most recently have been adopted in some states for recipients of Medicaid benefits. Mandatory job search requirements have also been a longstanding component of state unemployment-insurance programs in the United States.
Mandatory employment programs have the potential to be more effective than purely voluntary incentive programs at increasing work and earnings among transfer program recipients and, therefore, at reducing poverty. Moreover, they garner considerable public support because they are perceived to reinforce widely accepted social norms about the value of work.
However, while appealingly simple in theory, mandatory employment programs are complex in detail and application. Almost all of them provide for exemptions, and it is difficult to draw the line separating individuals who are from those who are not expected to work, a line that has major implications for the success of such mandates in reducing child poverty.
5 The importance of financial work incentives in increasing employment and reducing poverty is reinforced by several randomized controlled trials conducted in the 1990s that tested major increases in earnings disregards of cash welfare programs. These programs included the Minnesota Family Investment Program, the New Hope program, and the Canadian Self-Sufficiency program. These programs often decreased poverty as well as increasing employment (see Blank, 2002, for a comprehensive review). While these programs reinforce the view that financial incentives can result in poverty reduction, their design is quite different than any program being considered today. The committee’s Chapter 5 policy for expansion of the EITC represents its preferred program of this type.
Coupling mandated employment with work supports like child care, job search assistance, and transportation assistance is often the key to success, because, as we discuss in Chapter 8, low-income families face many barriers to work related to these factors. But these supports can be expensive and cumbersome to administer.
Another challenge in implementing mandatory employment programs is determining the amount of time recipients should be given to search for jobs that match their skills and pay at least the minimum wage. Finding the right balance, while also taking into account each recipient’s barriers to work, requires skill and experience on the part of job counselors and a supportive administrative structure.
Implications for Policy
The committee sought to develop mandatory employment policy options that could be included in our Chapter 5 simulations. Given the overriding importance of research evidence in the committee’s deliberations, we conducted an extensive review of the research on the impacts of mandatory employment programs on poverty. Some of the strongest evidence in support of these programs comes from randomized controlled trials that were published in the 1990s, when a large number of experiments were conducted on a diverse set of mandatory employment programs in several states and localities.6 Most of these employment-related programs were directed at recipients of benefits from the former AFDC program, most of whom were single mothers, so the bulk of the available evidence relates to that demographic group.
A particularly useful and comprehensive summary of the many randomized clinical trials conducted over that period is provided in Greenberg, Deitch, and Hamilton (2009). The authors divided mandatory employment programs for single mothers into four types, three of which required either (1) work “per se” experience, often with unpaid jobs at nonprofits or government agencies (frequently after a period of job search), (2) an immediate job search, or (3) immediate enrollment in education or training prior to either job search or work. A fourth group included a mixture of mandates, such as (1) through (3), plus work supports such as child care, with recipients’ specific mandates based on an assessment of their individual needs. Programs of each type were tested across a number of cities.
6 A randomized controlled trial evaluation of the impact of work requirements in the SNAP program is currently under way. It is being conducted by Mathematica Policy Research, in cooperation with other organizations, with funding from USDA (see https://www.mathematicampr.com/our-publications-and-findings/projects/snap-employment-and-training-pilots). Initial findings are expected in 2019, with a final report to be published in 2021.
The results of the clinical trials showed that over a 3- to 5-year period following random assignment, the family incomes of participants in the “work per se” programs rose only minimally, while incomes of participants in the “immediate job search” and “immediate enrollment in education/job training” programs fell because benefit losses exceeded increases in earnings. In contrast, mixed programs tailored to recipients’ needs generally produced clear increases in family income (Greenberg, Deitch, and Hamilton, 2009, Table ES.1).
The mixed and tailored program models were therefore the only types that could be expected to increase family income and reduce poverty. In the case of the mixed model, comprehensive programs at five different sites were tested, and the analysis showed net income effects (discounted over a 5-year period) ranging from −$745 to $2,651 (Greenberg, Deitch, and Hamilton, 2009, Table B-11). These 5-year summed effects correspond to an average annual income gain of $340 per year, an amount unlikely to reduce child poverty to any appreciable degree.
A smaller number of randomized clinical trials have assessed impacts on employment and family income for two-parent families. The best-known and most skillfully implemented study evaluated the California Greater Avenues for Independence (GAIN) Program (Riccio, Friedlander, and Freedman, 1994). The GAIN program was a statewide initiative targeted toward increasing employment and self-sufficiency for individuals who received AFDC cash welfare program (Riccio, Friedlander, and Freedman, 1994). The impacts of mandatory work programs on participants in this program (who, unlike the Greenberg et al.  study participants, were not grouped into categories of program types) were generally unfavorable. By the 5th year after random assignment, net family income had fallen by an average of $260 per year, and some sites reported annual income losses exceeding $2,000. While programs implemented at some of the sites did produce substantial gains in household income, the evaluations were unable to identify the program features that made this difference.
Evidence on the impacts of mandatory work programs also comes from the implementation of the Personal Responsibility and Work Opportunity Reconciliation Act of 1996, which required that all states mandate work for most recipients of benefits under the new TANF program. A number of studies have sought to estimate the effects of this legislation on employment, poverty, and other outcomes (Blank, 2002; Grogger and Karoly, 2005; Hamilton, 2002). The most consistent evidence indicates that the legislation reduced welfare receipt and increased employment. But while these work mandates may have generated short-run reductions in poverty, they may have simultaneously increased the number of families with incomes far below the poverty line (Bitler, Gelbach, and Hoynes, 2006). However, it is problematic to draw conclusions about work mandates from this evidence,
because impacts on families were generated by multiple features of the legislation, including mandatory work requirements as well as time limits, block grants, and in some cases earnings disregards. Researchers have been unable to identify the relative contributions of mandatory employment and other features to the outcomes that have been observed.7
Given that the evidence on the effects of mandatory employment under TANF is inconclusive, the best available evidence on child poverty reduction comes from the experimental evaluations just described, which were conducted in the 1990s. The question remains: Do the increases found in the family incomes of single mothers participating in the mixed programs that were the focus of those evaluations warrant conducting simulations of the impacts of such program for today’s transfer recipients? We conclude that they do not.
The AFDC caseload in the early 1990s was very different from the caseloads of major programs today, both in its demographic composition and in the nature of participants’ experience and employment-related education. The SNAP program, for example, includes far more nondisabled, nonelderly able-bodied workers than AFDC did, in addition to including large numbers of elderly and disabled individuals. The Medicaid program, with its high income-eligibility levels, covers more workers than AFDC did in the past. The labor market and the availability of other work supports, such as child care and the EITC, are also very different today.
CONCLUSION 7-4: There is insufficient evidence to identify mandatory work policies that would reliably reduce child poverty, and it appears that work requirements are at least as likely to increase as to decrease poverty. The dearth of evidence also reflects underinvestment over the past two decades in methodologically strong evaluations of the impacts of alternative work programs.
Block grants provide federal assistance, typically to state governments, for broadly defined functions such as social services. Unlike categorical grants, federal block grants give states considerable flexibility in allocating and spending the allotted funds. In the case of safety-net programs, block
7 See the extensive discussion of this issue in Blank (2002). One study which attempted to separate the work components concluded that “work requirements alone have relatively weak effects on family income and poverty” (Grogger and Karoly, 2005, p. 171).
grants have the potential to affect child poverty rates, and in principle they can be a tool for reducing poverty.
For two key reasons, however, the committee chose not to simulate block grant proposals and reforms in Chapter 5. First, very little evidence concerning the impact of block grants on poverty rates meets the standard of rigor we imposed on the other reforms we simulated. Second, block grants come in a variety of forms, and knowing how they are constructed is crucial in assessing any poverty impacts they might have. Accordingly, there is no simple answer to the question of whether block grants are likely to increase or reduce poverty.
Implications for Policy
Key features of block grants can be gleaned from states’ experience with several existing block grants—in particular, the TANF block grant, the Title XX Social Services block grant, and the Child Care and Development block grant.8 A fundamental feature is the block grant’s initial funding level. Ideally, the grant level is geared to a state’s level of need, but determining how that compares with the level of funding already received by the state is usually a contentious issue. Generally, block grants require “maintenance-of-effort” provisions to keep total spending at a reasonable level and encourage the recipient state’s commitment to program effectiveness and quality. Maintenance-of-effort provisions typically require states to continue to contribute a certain amount of their own funds, and penalties are in place for violating that requirement.
A potentially even more important feature in a block grant’s design is how its funding will change over time. Inflation-adjusted expenditures from block grants will fall as time goes by if funding amounts are fixed in nominal dollars and not allowed to change with inflation, unless states make up the shortfall with their own additional funds. Drops in funding for programs directed at children are likely to increase child poverty unless the level of need in the state is also dropping.9 Additionally, to avoid inequities in federal support over time, block grants also need to adjust to changes in a state’s level of need. Recessions are a special case of increased need;
9 In the TANF program, the caseload has fallen significantly since the 1990s, so that real spending per recipient has not dropped as much as the drop in real total TANF spending. However, a large share of the block grant is now funding activities other than cash assistance and work supports, and the participation rate of financial eligibles has fallen, demonstrating that the TANF program is now serving a smaller share of the needy population (Bitler and Hoynes, 2016).
without rules stipulating that adjustments are to be made in response to recessions, a block grant is not likely to be effective in reducing poverty during a downturn.
A common argument in favor of block grants is that they enable states to be flexible in addressing the needs of their populations and responding to the will of their voters. However, in some cases that flexibility can allow states to use block-grant funds to finance other, unrelated state activities, contrary to the intent of the grant. As a result, a key challenge in designing block grants is to formulate legislation in a way that constrains states, as intended by Congress, and prevents them from spending funds for unintended purposes. This raises a philosophical question: To what extent should the federal government restrict the states’ flexibility? The answer to that, in turn, depends on how much weight should be given to voters’ interest in supporting the poor in states other than their own and how important it is to have a uniform floor below which poor families are not allowed to fall.
The TANF block grant is a prime example worth examining, since it allows states considerable flexibility in spending block-grant funding. States vary widely in the amount of money they spend from this grant on cash assistance or a variety of other programs, and they also vary widely in the amounts they allocate per family at different income levels.10 Unfortunately, we know very little about how states’ choices relate to changes in state child-poverty rates.11 States’ reporting requirements under TANF are quite minimal, so federal policy makers and researchers are unable to determine whether the funds are being spent in keeping with the letter or spirit of the block grant.12 All of these issues illustrate the challenges that are inherent in the design and operation of block grants, which will in turn affect the degree to which these grants are able to reduce the poverty rate.
CONCLUSION 7-5: Block grants that are adequately funded and sustained over time, and that provide for countercyclical relief, may serve local populations well by providing more fiscal flexibility for state
10 See Falk (2016) for a detailed discussion of the TANF block grant. In FY2016, for example, overall, states spent 24% of their block grants on cash assistance, 11% on work-related activities, 20% on early care and education (child care and preschool), and the other 45% on a variety of activities including program management, state EITCs, and child welfare (https://www.acf.hhs.gov/ofa/resource/tanf-financial-data-fy-2016).
11 Some have suggested that states should be required to put aside some fraction of funds to conduct evaluations of the poverty impacts of their programs. This would provide important information to help states as well as Congress assess the grants’ impacts.
12 Beginning in federal fiscal year 2015, the Administration for Children and Families has required more detailed financial reporting from the states, leading to considerably more detail on spending categories than had been the case in prior years.
and local governments. However, block grants that are inadequately funded, fail to be sustained, or lack provisions for countercyclical adjustment have resulted in reduced support for low-income families and in increased poverty. In addition, most block grants require only limited reporting and almost no evaluation, which decreases the likelihood that their funds will be used for their intended purposes.
On a bipartisan basis, Congress created the TANF program, which was signed into law by President Clinton in 1996. The legislation converted what was previously known as AFDC from a matching grant to a block grant program, introduced work requirements and time limits, and imposed a large number of conditions on the states. Subsequent to the reform, the caseload in the program fell dramatically, and by 2000 it was only a little more than one-half of what it had been in 1995, prior to passage of the TANF legislation (Office of the Assistant Secretary for Planning and Evaluation, 2008). Similarly, expenditures on cash assistance for the affected families dropped by nearly one-half relative to expenditures on cash assistance in 1995 (Falk, 2015).13
One of the chief goals of the 1996 law was to increase employment and reduce poverty. Poverty could be expected to decline if the reform led to an increase in earnings and market income that exceeded the decrease in family income triggered by caseload reductions and a consequent drop in benefit receipt. As Figures 4-1 and 4-6 in this report show, market-based poverty fell sharply in the years after 1996, and most of the reduction in the overall poverty rate (including taxes and transfers) in the first 3 or 4 years after 1996 was a result of an increase in market income rather than expansions of transfers (although by 2015 most of the decline in overall poverty could be attributed to increases in transfers rather than increases in market income). However, the years after 1996 were also marked by improvements in the economy and the expansion of the EITC, both of which probably made independent contributions to poverty reduction.
A substantial research literature has attempted to distinguish the various contributions of these forces to poverty reduction. A review examining the short-run poverty impacts of well-evaluated pre-1996 programs
13 Because expenditures in the TANF program have fallen so dramatically, the cash component of the program currently contributes very little to poverty reduction. Eliminating TANF would increase the child poverty rate by about one-half of one percentage point (Wheaton and Haldar, 2018).
resembling TANF, as well as studies of TANF itself, concluded that while evaluations of most of the pre-1996 programs showed no effect on poverty, some of the studies of TANF itself suggested that it did indeed reduce poverty (Grogger and Karoly, 2005, Chapter 7). The review cautioned that after time limits became effective and block grants declined in real value, the program might show different effects. A later review by Ziliak (2016) found less evidence for the poverty-reducing impact of the 1996 legislation, which suggests that the longer-run impacts of TANF on poverty reduction may have been smaller than its short-run impacts.
Implications for Policy
The committee chose not to simulate an expansion of the TANF program or the elimination or removal of any of the provisions of the 1996 law, for several reasons. First, the evidence suggests that the TANF law did in fact reduce poverty in the short run, if not necessarily in the long run, so it is unlikely that the poverty rate would decline if the pre-1996 system were to be reinstated. Furthermore, it would be impossible to simulate changes in work requirements or block grants, for reasons explained in the preceding two sections. All other features of the law held constant, it is impossible to identify the relative contributions of those two components. Based on the available evidence, it would be an impossible task to simulate changes in the many features of state TANF programs and the impacts of these changes on the U.S. child poverty rate.
Few would disagree with the premise that all children deserve to be healthy and that public policy should enable them to benefit from the dramatic advances in U.S. medical care. Moreover, as documented in Chapter 3, investments in child health provide long-run benefits to society as a whole. Healthier children are more likely to grow up into healthier adults who will, as a consequence, work and earn more (Brown, Kowalski, and Lurie, 2015), experience greater happiness and life satisfaction (Council on Community Pediatrics, 2016), and be more likely to marry (Smith, 2009). Thus, policies aimed at improving child health could significantly reduce future poverty as today’s children grow up and start families of their own.
Poverty reduction in the next generation falls outside of the committee’s 10-year window. However, we considered how providing health insurance and taking other steps to improve children’s health might reduce child poverty in the short run through such mechanisms as reducing families’
out-of-pocket medical expenses and allowing parents to work (see Chapter 8). In addition, affordable health insurance may enable parents to seek needed health care for themselves and their children without falling behind on rent or other necessary expenses. Indeed, evidence suggests that good insurance coverage improves parents’ mental health, presumably by reducing stress and worry about health-care costs (Baicker et al., 2013; Finkelstein et al., 2016).
Implications for Policy
The United States has always relied on a patchwork health insurance system, one that does not cover everyone and can strain families’ ability to afford premiums, copayments, deductibles, and the costs of needed but uncovered care. At the same time, the federal government and the states have made substantial efforts to improve the health of poor children by providing access to medical care through Medicaid and the Children’s Health Insurance Program (CHIP).
Abundant evidence suggests that Medicaid and CHIP, which have both grown in size over the years, have had a major positive impact on child health and well-being (see Chapter 3). As documented in Chapter 4, in terms of expenditures Medicaid is by far the largest benefit program for low-income families with children, accounting for expenditures of $180 billion annually. The CHIP program spends an additional $15 billion per year (Centers for Medicare & Medicaid Services, 2017). Yet despite their proven benefits, health insurance programs such as Medicaid and CHIP are not directly reflected in official poverty measures. Consequently, the committee was unable to estimate the full effects on child poverty (as measured by the Supplemental Poverty Measure or SPM) of Medicaid expansion or other improvements in health insurance coverage for low-income families using the TRIM3 simulations (see Chapter 2).
There are two main obstacles to including health care needs and health-insurance benefits in poverty measures. First, families’ health care needs vary much more, both within and across years, than other needs such as food and housing. Incorporating these changing needs in poverty thresholds would require constructing a large number of poverty thresholds using, at a minimum, information on people’s health conditions and family size. Second, there is no publicly available information on the costs of coverage for many of the different health insurance packages families have.
As detailed in a paper commissioned by the committee (Korenman, Remler, and Hyson, 2017), the SPM takes an indirect approach to these problems. SPM thresholds are based on needs for food, clothing, shelter, utilities, and a few other things, but do not include health care. The SPM resource definition includes nonmedical in-kind benefits but excludes
health insurance benefits. Instead, the SPM deducts medical out-of-pocket (MOOP) expenses—for health insurance premiums, copayments, deductibles, and uncovered care—from family resources. When these expenses are deducted, some families that are above the poverty line defined by the Official Poverty Measure (OPM) drop below the SPM poverty line. Conversely, reductions in MOOP as a result of Medicaid expansion, for example, will add to family resources and reduce measured SPM poverty, all else being equal.
Yet the National Research Council (1995, p. 236) has acknowledged that its indirect approach for taking into account medical care benefits and costs (the basis for the SPM) was not fully satisfactory, because “. . . it does not explicitly acknowledge a basic necessity, namely, medical care, that is just as important as food or housing. Similarly, the approach devalues the benefits of having health insurance, except indirectly.” In the case of people who defer medically necessary care because they lack affordable insurance or access to free care, the MOOP deduction is too small—consequently, they appear to be better off than they actually are.
In the same paper commissioned by the committee from Korenman, Remler, and Hyson (2017), the authors critique various ways of accounting for health care needs and health insurance benefits in poverty measurement. Their critique covers, among other methods, the SPM indirect approach and the fungible or recipient-value approach of adding a portion of the market value of health insurance to family resources (see, e.g., Winship, 2016, Figure 2). They identify problems in each approach, and conclude by suggesting that health insurance costs, rather than health care needs, should be added to the SPM poverty thresholds and that the benefits from health insurance coverage (net of MOOP) should be included in resources. They name this proposed approach the Health-Inclusive Poverty Measure (HIPM).
Designating health insurance as a fundamental health care need would eliminate the problems of estimating care needs for inclusion in the thresholds, provided that certain conditions were met: Health insurance prices must not vary substantially with health conditions (otherwise, sicker people with higher-cost insurance may seem to be better off than they are), and it must be possible to designate a “Basic Plan”—namely, a plan that covers all health care that is deemed by society to be essential and for which cost-sharing requirements are capped. The Affordable Care Act (ACA) exchange plans make it possible to satisfy these conditions. The ACA-guaranteed issue and community rating regulations allow anyone to purchase health insurance at a price that does not depend on health status and that caps nonpremium MOOP.
As detailed in Korenman, Remler, and Hyson (2017), the HIPM starts with the SPM and then (1) adds health insurance needs to the SPM thresholds, using as the Basic Plan the unsubsidized premium of the
second-cheapest Silver Plan available in a household’s rating area; (2) adds the health insurance benefits received to resources; and (3) deducts nonpremium MOOP for medical care received. Korenman, Remler, and Hyson (2017, Table 1) display SPM thresholds and HIPM thresholds for 2014 by family size and composition. The average threshold for all families with children is $39,745. Of this amount, the average material need (SPM threshold) is $27,662, and the average health insurance need is $12,083, or 30 percent of the HIPM threshold, which makes explicit the importance and high cost to families of obtaining health insurance (in the absence of subsidies). For a family with one adult and two children, the average HIPM threshold is $27,727, of which $6,949 is the health insurance need, constituting 25 percent of the threshold.
Using the HIPM approach, Korenman, Remler, and Hyson (2017, Table 2) estimate that Medicaid reduces child poverty by 5.3 percentage points, compared with a 4.4 percentage point reduction from other means-tested benefits such as SNAP and a 6.5 percentage point reduction from tax credits such as the EITC. To the extent that more states expand Medicaid, child poverty will be further reduced; to the extent that states introduce premiums, copayments, and deductibles for Medicaid, as some are doing under waivers from the federal government, child poverty will increase.
CONCLUSION 7-6: Despite the importance of medical care needs and benefits for both poverty reduction and child health and well-being, these needs and benefits are captured only indirectly by current poverty measures. Thus, by definition, health spending can have little direct short-run impact on child poverty measures. Nevertheless, the significant child-poverty-reducing effects of Medicaid are illustrated by the 2014 results of a Health-Inclusive Poverty Measure, which augments the Supplemental Poverty Measure by considering health insurance needs when setting the thresholds and appropriately treating net medical expenses in measuring family resources.
AIAN are eligible for the standard programs and services available to all U.S. citizens, and they may also be eligible for additional programs and services offered by their tribes or the U.S. federal government. As mentioned in Appendix D, 2-7, the AIAN population is not only a racial/ethnic group but also recognized by the U.S. government as a political group, which allows individual tribal communities to participate in programs and
services designed specifically for them (see Chapter 2 for a discussion of the demographic characteristics of the AIAN population). In addition to federal programs such as TANF and EITC, other programs and policies that have shown promise for reducing poverty in the AIAN population include training and education programs that focus on cultural connections and internal tribal programs and services. The committee’s analysis of these policies benefited greatly from a paper we commissioned on the subject (Akee and Simeonova, 2017).14
Implications for Policy
Improvements in education and training programs hold promise for reducing poverty in the AIAN adult population, which has lower levels of educational attainment than the U.S. population as a whole (Akee and Taylor, 2014). In particular, programs that incorporate a tribe’s values and culture tend to be more effective (Goodluck and Willeto, 2009; HeavyRunner, 2003). The Family Education Model, for example, takes a family-centered approach to education and advocates for a more inclusionary process that takes into account the AIAN students’ cultural worldview. This enables them to enroll in, and successfully complete, higher education (HeavyRunner, 2003).
Tribal governments also play an important role in reducing child poverty. In addition to providing direct services and programs to support residents, they are a significant source of employment. Thriving and successful tribal governments are therefore a key component in reducing child poverty among the AIAN population (Jorgensen, 2007). Local political and legal authorities may also play a role in improving incomes on American Indian reservations. For example, Dimitrova-Grajzl, Peter, and Joseph (2014) found that when civil and criminal jurisdiction is removed from tribal control and given to states (U.S.), tribal incomes decrease. Changes in tribal political institutions may come from effective lobbying at the U.S. congressional level as well as the more local level in enacting reforms in tribal constitutions, which many AIAN tribes have been engaged in over the past 25 years (Lemont, 2006).
The Indian Gaming Regulatory Act of 1988, for example, grants federally recognized AIAN tribes the authority to operate casinos on tribal lands, providing a large economic opportunity for tribal communities.15 Over the past 10 years, the Indian gaming industry has reported annual revenues
15 Not all tribal nations operate casinos, and those that do are not all equally successful; revenue generation is dependent primarily on location and proximity to large population centers.
of approximately $28 billion, which may serve as an important means of alleviating child poverty (Akee, Spilde, and Taylor, 2015). Wolfe and colleagues (2012) reported increases in household incomes of about $1,700 for American Indians residing in counties with tribal casinos. Anderson (2013) found that the presence of a casino reduced child poverty rates by 4.6 percent between 1990 and 2000; however, some of that reduction may have been caused by the influx of new residents with more favorable economic characteristics.
One mechanism that might play a direct role in reducing household poverty levels is the use of casino revenues to fund cash transfers. Not all tribes provide this type of transfer, some electing instead to use casino revenues for tribal program operations. Nevertheless, as detailed in Chapter 3, Akee and colleagues (2010) found that these cash transfers result in improved child educational attainment for households that were originally in poverty, and there is no evidence that this additional unearned income reduces the probability that parents will find full- or part-time employment.
Federal programs like EITC and TANF are also important to AIAN households living in poverty. Wagner and Hertel (2008) surveyed individuals in 14 Volunteer Income Tax Assistance areas located on American Indian reservations. When asked how they would spend their tax refunds, respondents overwhelmingly answered that they would spend refunds on basic needs such as groceries, utilities, clothing, and rent or mortgage payments. Only 10 percent of respondents indicated that they would use the refund for savings.
Approximately 70 AIAN tribal governments, serving almost 300 different AIAN tribes and villages, are approved to operate TANF programs.16 Tribally operated TANF programs are unique in that their participants are exempt from the 5-year lifetime limit on benefits, provided that participants reside on reservations with unemployment rates above 50 percent. As a result, the binding TANF constraint does not apply to a number of AIAN communities and program recipients. Limited evaluation of these programs suggests that tribes that operate their own TANF programs experienced a drop of about 5 percentage points in poverty rates between 1990 and 2010 (Mather, 2017). Yet while TANF recipients on reservations received training and other preparation for jobs, employment opportunities on reservations are scarce, and the few studies that have evaluated TANF programs show that the availability of employment opportunities are the primary determinant of whether an individual is able to leave the TANF program.
16 The U.S. Department of Health and Human Services currently allows federally recognized tribal governments to operate their own TANF programs.
CONCLUSION 7-7: Small sample sizes in population surveys have made it particularly difficult to reliably measure poverty rates among American Indian and Alaska Native children. Moreover, we know little about the effectiveness of a number of important programs and policies—whether provided by the tribes, by the states, or by the federal government—that affect this population. Available evidence does suggest that some federal and tribal programs designed to improve opportunities for educational attainment, boost employment, and increase income have the potential to reduce child poverty.
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