Despite the success of government assistance programs in reducing child poverty in the United States over the past 50 years, an estimated 9.7 million children (13%) still live in families with incomes below 100 percent of the Supplemental Poverty Measure (SPM) poverty threshold. Of these, 2 million are in deep poverty, with family incomes below 50 percent of the SPM poverty line.1 With this as a backdrop, Congress has asked for expert guidance in ways to achieve greater progress. In 2016, Congress passed legislation directing the National Academies of Sciences, Engineering, and Medicine to establish an expert committee to conduct a comprehensive study of child poverty, with the goal of identifying programs that could achieve further significant reductions in child poverty within 10 years. This report is the fruit of that labor.
In the preceding chapters of this report, our Committee on Building an Agenda to Reduce the Number of Children in Poverty by Half in 10 Years has fulfilled the first four elements of its charge, namely, to: (1) review the literature on the health and social costs of child poverty; (2) evaluate the anti-poverty effectiveness of major assistance programs in the United States and other industrialized countries; (3) identify policies and programs with the potential to further reduce poverty and deep poverty for children by 50 percent within 10 years; and (4) perform analyses to identify combinations of programs that have a strong potential to reduce child poverty and
1 These estimates are for 2015 and use the SPM with income adjusted for underreporting for three large programs—the Supplemental Nutrition Assistance Program (SNAP), Supplemental Security Income (SSI), and Temporary Assistance to Needy Families (TANF) (see Chapter 2).
meet other policy objectives. All of our analyses, as specified in the charge made to us, used the SPM, adjusted for underreporting of major assistance programs, as the standard for assessing program benefits and costs. This chapter addresses the fifth element of our charge from Congress:
. . . to identify high-priority research gaps, the filling of which would significantly advance the knowledge base for developing policies to reduce child poverty in the United States and assessing their effects.
Substantial evidence undergirds our conclusions in the preceding chapters concerning the effectiveness of programs and combinations of programs at combating child poverty. Owing to gaps in the relevant policy literature and associated data, however, we were unable to assess certain program and policy options as fully as we would have liked. To provide just a few examples:
- In contrast to the wealth of evidence available during the welfare reform debates of the 1990s, today we have very few recent strong evaluations of programs and policies designed to boost the job skills and employment of parents in low-income families receiving public assistance.
- For some assistance programs, such as Supplemental Security Income (SSI) and various types of housing assistance, there is relatively little evidence of their effects on children.
- There is insufficient evidence to assess the potential poverty-reducing effects of programs that do not provide income support, such as family planning and marriage promotion programs.
- Available data sources lack sufficient sample sizes or variables, or both, to assess the poverty-reducing effects of programs for small or specialized population groups, such as American Indians and Alaska Natives, children with disabilities, and children with incarcerated parents.
- Crucial measures of family resources, such as benefits (cash or in-kind) from assistance programs (e.g., Supplemental Nutrition Assistance Program [SNAP] benefits), are underreported or misreported in household surveys. This problem is severe enough that it compromises these measures’ use for poverty analysis without substantial investment in data correction and adjustments using administrative data. Fortunately, there is a growing evidence base on ways to make these corrections.
Accordingly, this concluding chapter contains (1) a list of priority areas for research and (2) recommendations for data collection and measurement,
which if acted on will fill gaps in the literature and evidence base and make it possible to evaluate program and policy changes that may be made on the basis of our conclusions. In this chapter we also discuss (3) how having high-quality monitoring and evaluation efforts in place will enable a future expert study committee to evaluate progress and identify further steps that may be needed to further reduce child poverty and deep poverty. We could not address the entire field of poverty and well-being research; rather, we focused on areas for which the absence of solid research findings most compromised the committee’s ability to assess the effects of alternative programs and policies on child poverty reduction over a 10-year period.
Finally, this chapter concludes by underscoring the importance of a coordinated effort by relevant government agencies to set priorities for research and data collection so that scarce public resources can be used to their greatest effect. The U.S. social safety net is decentralized, with different agencies in charge of administering programs related to food, housing, energy, job training, medical care, and various kinds of income assistance. It is critical for these agencies to work together to provide for cost-effective data collection, monitoring of program administration and child outcomes, and research on the benefits and costs of the nation’s current and proposed efforts to reduce child poverty.
In this section, we identify four priority areas for research on finding ways to (1) assist parents in obtaining sustained employment; (2) reduce uncertainty and fluctuations in income that make it difficult for low-income families to handle the daily challenges of living; (3) facilitate access for all families to programs for which they are qualified; and (4) help offset the added barriers to poverty reduction encountered by low-income families that are living in urban areas of concentrated poverty or in rural areas lacking transportation and community resources, by low-income families that face pervasive discrimination in housing, employment, and other areas, and by children who have a parent involved in the criminal justice system.
In addition, there are two areas for which we do not make formal recommendations, but which nonetheless deserve attention. First, among the major assistance programs, SSI and various kinds of housing assistance have undergone little evaluation to determine their effectiveness in reducing child poverty and improving child well-being. The agencies with responsibility for these programs need to subject them to rigorous assessment of these impacts.
Second, as we documented in Chapter 7, several family-related issues deserve further research. Despite extensive experimentation, there has been little success in devising programs with positive effects on marriage rates,
despite the fact that child poverty would probably decline if more children were living in two-parent households. We are unable to identify specific programs that should be tested. However, we encourage the states, as they are testing work incentives (see next section), to seek out and test ideas for structuring benefits in a way that encourages marriage, or at least does not discourage it by penalizing families with married parents.
Two other family-related issues concern contraception and family leave. There is strong evidence that increasing awareness of and access to effective, safe, and affordable long-acting reversible contraception (LARC) reduces unplanned births, which in turn might reduce child poverty. States therefore have ample evidence that they could use to develop, test, and implement policies that promote the use of LARC. In addition, evidence from a small number of states suggests that paid family and medical leave may promote parental employment and improve child health, although it may reduce employment among women potentially eligible for such leave. It is therefore important to continue evaluating the labor-market, health, and poverty impacts on child poverty of state paid-leave laws.
We stress the importance of randomized controlled methodologies, where feasible, when evaluating the effectiveness of existing or proposed programs and policies for reducing child poverty and deep poverty. These methodologies can also provide evidence to help achieve other program goals that can improve child well-being, such as increasing marriage rates and parents’ labor force participation. Such experiments, while not without problems (e.g., missing data, attrition, small samples, high relative cost; see Deaton and Cartwright, 2018; National Research Council, 2010), make it possible to draw causal inferences—and not just correlational associations—concerning the effects of alternative policies.
Although we stress the importance of experiments, we recognize that it is often impossible to carry out controlled experimentation. For example, understanding the longer-term effects of alternative policies might require an experiment lasting far longer than resource constraints, family consent, and attrition from the experiment would allow. When random assignment of families to treatment groups is not an option, alternative methods can often provide compelling evidence on the effects of different regimes. Such methods include regression discontinuity, instrumental variables, propensity score matching, and case control studies, among others.
Analyses of natural experiments can also provide strong evidence of program effects. This approach might be useful, for example, in assessing the poverty-reducing effects of Medicaid expansion based on before-and-after comparisons of states that have and those have not implemented expansion. These before-and-after methods could also be applied to data gathered in health surveys to study policy effects on child and parental biomarkers and mental health. Quasi-experimental methods can be especially
helpful for determining the long-term effects of policies to alleviate child poverty on earnings, chronic diseases, and other important components of intergenerational mobility. In fact, much of what we know about long-term outcomes derives from studies with these research designs.
Data from randomized experiments and quasi-experiments often turn up evidence of differential effects of policies on different groups, although these findings should be subject to further testing in cases where analyzing such differences is not part of the original research design. In addition to experimentation and quasi-experimentation, other kinds of research can be used to (1) identify policy features that merit the use of scarce resources for rigorous but expensive research methods; (2) help understand the circumstances and family situations for which a given program might be more or less successful; and (3) help identify aspects of program administration that affect child outcomes. Research methods for these purposes include process analysis, which could look at the details of how programs operate; qualitative analysis, through which community sociologists could examine families’ circumstances and behaviors; and correlational analysis, which could suggest promising avenues for poverty reduction and other policy goals, based on ex-postanalysis of multivariate data, that warrant experimentation. (For an assessment of the strengths and weaknesses of various research methods, see National Research Council, 2001, Ch. 4, and National Academies of Sciences, Engineering, and Medicine, 2016, Ch. 6.)
In the recommendations that follow, for the sake of readability, rather than name every agency that could benefit from each proposed action, we call on “relevant agencies” to take appropriate action, on the assumption that agencies will be able to identify those recommendations that are relevant to their missions. The last section discusses the need for a coordination of efforts among the many relevant agencies, including a role for the U.S. Office of Management and Budget (OMB), as well as the need for making administrative data available to qualified researchers outside those agencies for the purposes of program evaluation.
Research on Effective Work-Oriented Child Poverty-Reduction Programs
Historically, an important goal of programs to reduce child poverty in the United States has been to move low-income families from reliance on government assistance to greater participation in the labor force. If government is to reach appropriate conclusions about which policies will have the largest effects on poverty reduction and labor force participation, it needs a solid and reliable body of research evidence. Much of what is known about the effects of work-oriented features of assistance programs on poverty, government budgets, and society at large (see Chapter 7) comes
from many well-run experiments that states conducted before the 1996 welfare reform (Grogger and Karoly, 2005; Haskins and Margolis, 2014; National Research Council, 2001). That research was largely a response to the requirement by the U.S. Department of Health and Human Services that states rigorously assess the effects of program modifications as a condition for obtaining waivers to implement them (Gueron and Rolston, 2013).
In recent years, however, states seeking to test new work-oriented programs, especially those including work requirements, have often chosen evaluations with methodologically weak designs, which have produced unreliable and misleading results (Mitchell, 2018). Low-quality evaluations are a waste of public funds and can harm the public discussion of the merits of new programs. When the government agencies that grant waivers do not prioritize high-quality evaluations, they fail to ensure that the public discussion of the programs’ strengths and weaknesses is based on strong evidence. Federal agencies therefore should require states to conduct rigorous and scientifically valid evaluations of any new programs implemented as a result of the waiver process.
RECOMMENDATION 9-1: Relevant federal departments and agencies, especially those granting waivers to state and local governments to test new work-related programs, should prioritize high-quality, methodologically rigorous research and experimentation to identify ways to boost the job skills and employment of parents of low-income families receiving public assistance. Congress should ensure that sufficient funding is made available to conduct these evaluations.
Research on Features of Assistance Program Administration That Will Enhance the Financial Stability of Low-Income Families
We have documented the financial instability that makes it difficult for many low-income families to juggle everyday challenges and find stable housing, for example when they lack the funds for a deposit and the first month’s rent. Low-income families are also vulnerable to financial catastrophe triggered by a loss of employment, a reduction in work hours, the loss of transportation, or other changes in parents’ circumstances—which can have dire consequences for children.
We recommend rigorous evaluation of those features of assistance programs that might make it easier for families to obtain and retain benefits. Examples include methods for integrating and streamlining enrollment across multiple program areas (e.g., housing, food, energy) and simplified procedures for updating information so that families retain eligibility. It would also be useful to experiment with different ways of offering
short-term financial assistance, such as to enable families to pay a deposit on a rental unit or a large car-repair bill, as well as ways to make existing benefit payments more frequent (e.g., for the Earned Income Tax Credit or EITC), in the interest of accommodating families’ needs.
RECOMMENDATION 9-2: Relevant federal departments and agencies should prioritize research and experimentation aimed at finding ways to reduce the financial instability of low-income families participating in assistance programs. Program features that may contribute to this goal and merit evaluation include streamlined program administration, more convenient access to the benefits that families are eligible to receive, provisions for emergency assistance, and flexibility in the frequency of benefit payments.
Research on Features of Assistance Program Administration That Will Reduce Barriers to Access by All Population Groups
The passage of legislation or implementing regulations to improve the government’s safety net for low-income families with children is necessary but insufficient to achieve the desired reductions in child poverty and other priority outcomes. In addition to being run as efficiently as possible, programs need to focus on ensuring equitable access to all families who qualify for benefits. In this report we have documented disparities in program take-up rates (e.g., for SNAP benefits) both among states and among demographic groups. While a number of factors may produce such disparities, cumbersome or demeaning enrollment procedures can prevent potential beneficiaries from accessing resources to which they are entitled. Another barrier to access is simply the lack of awareness that programs are available, including awareness of any new program features, such as the provision of emergency assistance. Multifaceted experimentation and other research on ways to reduce these kinds of barriers ought to be high priorities.
RECOMMENDATION 9-3: Relevant federal departments and agencies should prioritize research and experimentation designed to improve the administration of assistance programs, especially to facilitate full and equitable access to the benefits to which low-income families are entitled. Such research should focus not only on streamlining program processes but also on making outreach about programs more effective, enhancing the communication skills of program staff, and strengthening program staff’s ability to interact with all population groups.
Research on Reducing Barriers to the Effectiveness of Assistance Programs Resulting from Contextual Factors Affecting Families
Not all low-income families face the same problems as they attempt to climb out of poverty with the help of government assistance programs. Families that live in urban neighborhoods with concentrated poverty (with poverty rates of 40 percent or higher)2 or in depressed rural areas that lack transportation and community resources are particularly likely to face obstacles to gainful employment and other means of improving their economic situations. Families in which a parent has a chronic disease or is disabled face similar challenges, as do families that routinely encounter discrimination in employment, housing, medical care, and other areas because of their race or ethnicity. Compounding the obstacles to economic betterment that confront minority low-income families is the fact that they are more likely than White families to live in areas of concentrated poverty and to have a parent involved in the criminal justice system.
Income assistance programs, which are the focus of our report, cannot in isolation be expected to significantly reduce neighborhood segregation, discrimination in realms such as employment, or mass incarceration. However, as described in Chapter 8, these programs can help reduce the negative impacts of such conditions on families’ access to and use of benefits designed to reduce child poverty. Meanwhile, research is needed to identify and combat discriminatory behaviors, such as neglecting to inform minority families of child care vouchers and other available benefits. Along with that, experimentation is needed to find ways to improve minority families’ job prospects. The latter may include providing active assistance in job searches, working directly with major employers to help low-income and formerly incarcerated parents gain a foothold in the labor market, and helping families move to neighborhoods with better public transportation and other supports.
It is also important to note that administrative changes that give more discretion to case workers, for example so they can respond to families experiencing emergencies, may also increase opportunities for discriminatory behavior. This is a tradeoff that needs to be explicitly recognized, studied, and addressed.
RECOMMENDATION 9-4: Relevant federal departments and agencies should prioritize research and experimentation designed to find ways to mitigate the effects of contextual factors that impair the effectiveness of current programs to combat child poverty. These contextual
2 For more information on concentrated poverty, see https://www.cbpp.org/sites/default/files/atoms/files/11-3-15hous2.pdf.
factors include (1) detrimental neighborhood conditions, such as those found in urban areas of concentrated poverty and rural areas with limited transportation and/or access to community resources; (2) racial and social discrimination in employment and housing; and (3) adverse consequences of the criminal justice system, which disproportionately affect poor people, especially minorities. Such research should focus on population groups that are known to be most harmed by discrimination and bias and most likely to face adverse contexts that worsen their families’ poverty and their ability to overcome it.
Better data can be just as important as closing the research gaps in the effort to assess promising anti-child-poverty initiatives. Improved federal statistics on income and poverty threshold components are also needed to better inform policy makers and the public.
We have prioritized four improvements in data and measures: (1) the addition of relevant variables to surveys and administrative records to better assess the impact of contextual factors on child poverty programs; (2) the expansion of sample sizes for small populations of policy interest; (3) the use of administrative records to correct reported income and program benefits in the Current Population Survey Annual Social and Economic Supplement (CPS ASEC), which is the basis of both the Official Poverty Measure (OPM) and the SPM; and (4) an assessment of the merits of a Health-Inclusive Poverty Measure (HIPM, see Chapter 7) to capture more fully than the SPM does the effects on child poverty of changes to Medicaid and other medical care assistance programs. Improvement of household expenditure data would also be helpful for analyzing consumption patterns and the relationship between income poverty and consumption poverty, and in the longer run it would be helpful for developing a consumption-based measure of poverty.
Collecting Relevant Variables to Analyze Program Effectiveness and Child Poverty
The portfolio of ongoing federal household surveys provides a rich array of data for tracking child poverty and other indicators of child well-being. However, some important variables are systematically missing from both surveys and program administrative records. Having family members involved in the criminal justice system, about which surveys rarely collect information, is a prime example. Surveys rarely ask whether family members are or have been incarcerated or on probation or parole
(see National Academies of Sciences, Engineering, and Medicine, 2017a). Similarly, criminal justice records are rarely linked to assistance program records. More generally, it is important for relevant program agencies and statistical agencies to systematically review the extent to which existing and proposed data collections include important variables for the analysis of low-income families’ participation in assistance programs, characteristics of parents that are important for understanding child outcomes, and trends in child poverty and other indicators of child well-being. Based on that review, the next step is for agencies to identify priority data gaps and to develop plans, in conjunction with OMB’s Statistical Policy Division and relevant OMB budget units, for filling these gaps.
RECOMMENDATION 9-5: Relevant federal program agencies and statistical agencies, working with the U.S. Office of Management and Budget, should review relevant data collection programs and proposed programs, including surveys and administrative records, to ensure that they include measures for monitoring and assessing the effects of assistance programs, family characteristics, and contextual factors on child poverty and other child outcomes. For example, surveys on income, wealth, and program participation should obtain information about family members who are currently incarcerated or on parole or probation, using techniques that are known to facilitate response, to support research on how these circumstances may increase child poverty.
Collecting Data on Small Populations for Analyzing Child Poverty
Household surveys use probability samples to collect information, a method that costs less and imposes less of a burden on respondents than a complete population census would. Surveys intended to yield the data necessary for analyzing income and poverty, such as the CPS ASEC, employ a sufficient sample size for major population groups (the CPS ASEC includes 100,000 households each year), but their sample size is not sufficient to allow the analysis of small population groups that merit particular attention in the context of child poverty. While the American Community Survey, which includes 3 million households each year,3 can provide poverty estimates for small population groups, it lacks the richness of content to support detailed analysis of program effects on child outcomes.
An important example of this problem concerns the American Indian and Alaska Native (AIAN) population, about which there is a dearth of
data, particularly on children. Because of the relatively small size of this population, it often goes uncounted in national surveys or is combined with other small racial/ethnic groups. Moreover, evaluations of the effectiveness of programs and policies designed to combat child poverty—whether provided by a tribe or by federal or state governments—have rarely been conducted for this population, even though AIAN families have very high poverty rates and other deficits, such as poor health.
Other groups for which small sample sizes make analysis difficult (assuming the group is identified in the first place) include children with disabilities and children with one or both parents incarcerated or on parole. Data on such small populations can be obtained by adding supplemental samples to existing surveys on a periodic basis. For example, additional samples can be rotated so that one small group, such as AIAN households with children, is oversampled in one year and another group, such as households that have children with disabilities, is oversampled in another. In addition, targeted surveys can be fielded at regular intervals. Finally, program agencies could be required to include relevant variables, such as child disabilities and AIAN status, in their administrative records.
RECOMMENDATION 9-6: Federal program agencies and statistical agencies working with the U.S. Office of Management and Budget should explore ways to obtain sufficient sample sizes for the analysis of small population groups of concern for child poverty. Such groups include American Indian and Alaska Native families, families that have children with disabilities, and families with one or both parents involved in the criminal justice system. Methods to consider include adding supplemental samples to existing surveys on a rotating basis, fielding targeted surveys periodically, and ensuring that assistance program records include relevant variables for analysis.
Improving Measures of Income and Poverty
Estimates of income, poverty, and assistance program participation that are derived from major federal household surveys, including the CPS ASEC, the American Community Survey, and the Survey of Income and Program Participation (SIPP), are followed closely by policy analysts and researchers and serve to inform the public as well as policy makers. However, over time the completeness and accuracy of survey respondents’ reports have declined.
When CPS ASEC estimates of recipients and amounts of income from various programs are compared with administrative records, one finds high rates of net underreporting. In 2006–2007, for example, the CPS captured only 83 percent of benefits paid out from the EITC, only 68 percent of
unemployment insurance benefits, and only 54 percent of SNAP benefits (Meyer, Mok, and Sullivan, 2009, Tables 3, 8, 10). Similarly, child support receipts reported in the 2017 CPS are only 75 percent of payments distributed to families recorded by the Office of Child Support Enforcement (Grall, 2018; and Office of Child Support Enforcement, 2018). This underreporting has persisted even after the Census Bureau has imputed missing amounts for respondents who say they participated in a program but did not provide an amount, and even after it has reweighted the data to reproduce population estimates by age, gender, and race and ethnicity.
In Chapter 2 we described the TRIM3 model procedures for correcting the underreporting of receipt and amounts of major assistance programs, specifically SNAP, SSI, and Temporary Assistance to Needy Families (TANF), in the CPS ASEC; without such adjustments, the SPM poverty rate for children in 2015 would have been 3.3 percentage points higher. Yet the TRIM3 adjustments, which use published aggregate statistics such as total SNAP beneficiaries, cannot be as accurate as adjustments that could be made by the Census Bureau using administrative records for individuals and households. Moreover, TRIM3 does not attempt to adjust for underreporting of other income types, such as child support, pensions, interest, or dividends (see Chapter 2). Several reports by expert panels of the Committee on National Statistics have recommended that the Census Bureau use administrative records to correct for reporting errors in the CPS ASEC and the SIPP (see, e.g., National Research Council, 1989, 2009). To date, the Census Bureau has used the administrative records to which it has access for statistical purposes to evaluate reporting in its surveys, but not to adjust the data.
One impediment is that the Census Bureau lacks ready access to most state administrative records. (States maintain records for SNAP, Medicaid, unemployment insurance, TANF, and workers’ compensation.) Also, the Census Bureau would require additional budget resources to redesign its questionnaires and processes to permit integration of survey responses and administrative records. There are also concerns as to the legal authority for using records to replace survey responses, although Title 13 of the U.S. Code4 authorizes the Secretary of Commerce (on behalf of the Census Bureau) to obtain and use records to the extent possible in place of direct inquiries.
Over the past decade there has been a growing recognition of the need to use administrative records together with surveys to improve the quality of the data on which important statistics are based by adopting a multiple-data-sources paradigm instead of a survey paradigm (see National Academies of Sciences, Engineering, and Medicine, 2017b, III-3). In 2014,
4 U.S. Code, Title 13, Chapter 1, Subchapter I, § 6.
OMB issued guidance stating that the use of federal administrative records should be routinely considered when compiling federal statistics (Office of Management and Budget, 2014). The more recent report of the Commission on Evidence-Based Policymaking (2017, Ch. 2) includes several recommendations for enhancing the government’s ability to use administrative records for evidence-based program evaluation and policy research.5
We add our voice to those of other institutions underscoring the importance of producing high-quality statistics that accurately reflect levels of and trends in household income, poverty, and program participation. Organizations such as the Urban Institute (in producing its TRIM3 model) and the Congressional Budget Office have done invaluable service by producing adjusted income statistics to inform policy debate. Nonetheless, it ought to be the role of the responsible federal statistical agency, which can gain access to microlevel administrative records for statistical purposes, to regularly produce authoritative income statistics to ensure that everyone is using the same high-quality information for public discussion and policy analysis.
It would also be useful for the Census Bureau to conduct or commission research on the OPM, anchored SPM, unanchored SPM, and consumption-based measures of poverty to see which of these measures more accurately track other measurements of disadvantage and hardship, such as food insecurity, both over time and across space.
RECOMMENDATION 9-7: Relevant federal departments and agencies, together with the Office of Management and Budget, should work with the Census Bureau to obtain and use administrative records in conjunction with household surveys to improve the quality of the official income, poverty, and program participation estimates that are needed by the public, policy makers, program analysts, and researchers. It is understood that research access to microdata for linked datasets would be governed by relevant laws and regulations for protecting data confidentiality and individual privacy.
Developing a Health-Inclusive Poverty Measure (HIPM)
Extensive evidence points to the positive effects of Medicaid and the Children’s Health Insurance Program (CHIP) on child outcomes. Yet the SPM measure used throughout this report, while a significant improvement on the OPM, provides no way to translate the resources transferred to low-income families by health insurance coverage into a trustworthy estimate of poverty reduction. While the SPM takes into account medical
out-of-pocket (MOOP) expenses, such as premiums and copayments, its thresholds do not include an allowance for medical care needs, and its measurement of family resources does not directly capture the benefits of Medicaid or other health insurance coverage.
In Chapter 7, we describe an approach that seeks to turn the SPM into an HIPM by adding needs for health care insurance to the SPM poverty thresholds and adding health insurance coverage benefits (net of MOOP) to SPM-defined family resources. The proposal uses the Affordable Care Act’s Silver Plan provisions as the basis for the threshold amounts and benefits, including caps on premium and nonpremium MOOP expenses, so that families never have benefits added that exceed what the Affordable Care Act deems to be acceptable cost-sharing. Using this HIPM, Medicaid is estimated to have reduced child poverty by over 5 percentage points in 2014 (Korenman, Remler, and Hyson, 2017).
We urge the agencies that produce the SPM—namely, the Bureau of Labor Statistics, which produces the thresholds, and the Census Bureau, which measures family resources and produces poverty estimates—to work with OMB and the Department of Health and Human Services on a plan to evaluate and move toward implementation of an HIPM.
RECOMMENDATION 9-8: The Bureau of Labor Statistics and the U.S. Census Bureau, working with the U.S. Office of Management and Budget and the U.S. Department of Health and Human Services, should move expeditiously to evaluate a Health-Inclusive Poverty Measure (HIPM) of the kind illustrated in this report. Using the evaluation results, these agencies should proceed to implement an HIPM that builds on the Supplemental Poverty Measure. Such a measure would permit a fuller assessment of the effectiveness of health insurance programs, such as Medicaid, in reducing measured child poverty.
Provided that the above-described improvements can be made in research and data sources to fill important gaps in what is known about effective child anti-poverty programs, executive branch agencies and Congress (when legislation is needed) should be able to identify promising program features to implement at scale. It is important that program budgets, whether for new or current programs, include sufficient resources for data collection to enable continuous monitoring of program operations and child outcomes.
Needed data may require the inclusion of additional variables in ongoing federal household surveys, additional variables collected in the course of program administration, and new targeted surveys. Budgets also need
to include sufficient resources for regular program evaluation and research to support further improvements in program effectiveness. Similarly, budgets for block grant programs like TANF—which allow state governments considerable latitude in their design and administration—need to include resources for data collection, program evaluation, and research.
In other words, implementation of a new or modified income assistance program, whether at the federal or state level, should not signal an end to relevant data collection and research, as occurred to some extent following welfare reform in the mid-1990s. Instead, it ought to be standard practice for policy makers to require continued monitoring and evaluation and to ensure that resources are available to determine where program innovations are and are not working and what further improvements may be possible.
Our recommendation in this regard comports with recommendations for program evaluation contained in the 2017 report by the Commission on Evidence-Based Policymaking. Recommendations 5-1 through 5-6 from that 2017 report call for each department to have a chief evaluation officer, a trained evidence-building workforce, and a multiyear learning agenda; for OMB to coordinate evidence-building activities across departments; for streamlined procedures for approving data collection to support evidence-based policy; and for sufficient resources to support evidence-based program design, implementation, and evaluation. Several of these recommendations by the Commission are adopted in the administration’s June 19, 2018, report, Delivering Government Solutions in the 21st Century—Reform Plan and Reorganization Recommendations, which includes a section on strengthening federal evaluation.6 They are also included in the recently passed Foundations for Evidence-Based Policymaking Act of 2018.7
RECOMMENDATION 9-9: Federal and state executive agencies and legislatures should ensure that child anti-poverty assistance programs require and include adequate resources for regular monitoring of program operations and child outcomes, as well as for rigorous program evaluation and research on ways to improve program effectiveness.
Our report lays out packages of anti-poverty programs that have the potential to cut child poverty and deep poverty by one-half within 10 years.
It also identifies priorities for research and data collection to fill important gaps in the evidence base, thereby paving the way for further improvements in the effectiveness of programs designed to combat child poverty. We hope the relevant agencies and the U.S. Congress will take our conclusions and recommendations seriously and act on them.
As we noted earlier, however, responsibilities for administering the federal safety net are spread among half a dozen cabinet departments: the U.S. Departments of Agriculture, Energy, Health and Human Services, Housing and Urban Development, Labor, and Treasury, as well as the U.S. Social Security Administration. Responsibilities for data collection, program evaluation, and research on program improvements are similarly dispersed. State agencies, working with their federal counterparts, play an important role in the administration of many assistance programs.
Assuming that stakeholders—Congress, federal and state agencies, and the public—agree that further reduction of child poverty is a priority goal for U.S. policy, we offer a final recommendation: A coordinating mechanism should be put in place to ensure that our report is followed up and that well-considered decisions are made establishing priorities for new and improved assistance programs and supporting the associated research and data needed for monitoring, evaluation, and further improvement. We believe that the Office of Management and Budget is the appropriate agency to coordinate the assessment of our conclusions and recommendations and to put together an action plan.
In response to the 1995 National Research Council report calling for a new approach to poverty measurement, OMB acted on the report’s recommendation that it play a lead role by establishing a technical working group of relevant agencies to assess and refine the panel’s recommendations. The result of that action was the SPM. Similarly, OMB regularly leads interagency committees on such matters as the content of the decennial census, the American Community Survey, and SIPP. In its 2017 report (p. 6), the Commission on Evidence-Based Policymaking specifically assigned a lead role to OMB to coordinate evidence-based policymaking in the federal government:
REC. 5-3: The Congress and the President should direct the Office of Management and Budget (OMB) to coordinate the federal government’s evidence-building activities across departments, including by undertaking any necessary reorganization or consolidation within OMB and by bolstering the visibility and role of interagency councils.
We conclude our report with a similar recommendation:
RECOMMENDATION 9-10: The Office of Management and Budget (OMB) should convene working groups of appropriate federal program, research, and statistical agencies to assess this report’s conclusions about program packages that are capable of reducing child poverty by half within 10 years of adoption. OMB should also convene working groups charged with assessing the report’s recommendations for research and data collection to fill important gaps in knowledge about effective anti-child-poverty programs. These working groups should be tasked with recommending action steps, and OMB should work with the relevant agencies to draw up implementation plans and secure appropriate resources. The working groups should consult with the relevant state agencies and outside experts, as appropriate, to inform their deliberations.
Commission on Evidence-Based Policymaking. (2017). The Promise of Evidence-Based Policymaking. Washington, DC. Available: https://cep.gov/content/dam/cep/report/cep-finalreport.pdf.
Deaton, A., and Cartwright, N. (2018). Understanding and misunderstanding randomized controlled trials. Social Science & Medicine, 210, 2–21.
Grall, T. (2018). Custodial Mothers and Fathers and Their Child Support: 2015. Current Population Reports. Washington, DC: U.S. Census Bureau.
Grogger, J., and Karoly, L.A. (2005). Welfare Reform: Effects of a Decade of Change. Cambridge, MA: Harvard University Press.
Gueron, J.M., and Rolston, H. (2013). Fighting for Reliable Evidence. New York: Russell Sage Foundation.
Haskins, R., and Margolis, G. (2014). Show Me the Evidence: Obama’s Fight for Rigor and Results in Social Policy. Washington, DC: Brookings Institution Press.
Korenman, S., Remler, D.K., and Hyson, R. (2017). Accounting for the Impact of Medicaid on Child Poverty. Washington, DC: The National Academies Press.
Meyer, B., Mok, W.K.C., and Sullivan, J.X. (2009). The Under-Reporting of Transfers in Household Surveys: Its Nature and Consequences. NBER Working Paper No. 15181. Cambridge, MA: National Bureau of Economic Research. Available: https://doi.org/10.3386/w15181.
Mitchell, T. (2018). Some House Leaders Ignore Evidence, Cite Flawed Reports to Justify Taking Basic Assistance Away from Needy Individuals. Washington, DC: Center for Budget and Policy Priorities. Available: https://www.cbpp.org/sites/default/files/atoms/files/4-18-18tanf.pdf.
National Academies of Sciences, Engineering, and Medicine. (2016). Commercial Motor Vehicle Driver Fatigue, Long-Term Health, and Highway Safety: Research Needs. Washington, DC: The National Academies Press.
________. (2017a). Improving Collection of Indicators of Criminal Justice System Involvement in Population Health Data Programs: Proceedings of a Workshop. Washington, DC: The National Academies Press. Available: https://doi.org/10.17226/24633.
________. (2017b). Principles and Practices for a Federal Statistical Agency, Sixth Edition. Washington, DC: The National Academies Press. Available: https://doi.org/10.17226/24810.
National Research Council. (1989). The Future of the Survey of Income and Program Participation. Washington, DC: National Academy Press. Available: https://doi.org/10.17226/2072.
________. (1995). Measuring Poverty: A New Approach. Washington, DC: National Academy Press.
________. (2001). Evaluating Welfare Reform in an Era of Transition. Washington, DC: The National Academies Press. Available: https://doi.org/10.17226/10020.
________. (2009). Reengineering the Survey of Income and Program Participation. Washington, DC: The National Academies Press. Available: https://doi.org/10.17226/12715.
________. (2010). The Prevention and Treatment of Missing Data in Clinical Trials. Washington, DC: The National Academies Press. Available: https://doi.org/10.17226/12955.
Office of Child Support Enforcement. (2018). Preliminary Report FY 2017. Washington, DC: U.S. Department of Health and Human Services. Available: https://www.acf.hhs.gov/css/resource/fy-2017-preliminary-data-report.
Office of Management and Budget. (2014). Guidance for Providing and Using Administrative Data for Statistical Purposes. OMB Memorandum M-14-06. Washington, DC: Office of Management and Budget. Available: https://obamawhitehouse.archives.gov/sites/default/files/omb/memoranda/2014/m-14-06.pdf.