The federal government funds a wide array of programs intended to provide benefits or services to low-income individuals, families, and households. The 12 programs included in this review include the largest of these programs, Medicaid, as well as some relatively small programs such as WIC. The 12 programs are administered by seven different federal agencies. Table 1 shows the agencies responsible for each program and federal expenditures for fiscal year 2003, the most current year available. These programs provide different benefits and services to different target populations. Some of the programs provide benefits that phase out gradually, so some people may be eligible for a very low benefit. For example, in fiscal year 2005, monthly food stamp benefits for a three- person household can be as low as $1 per month. Other programs, such as Medicaid, generally offer comparable benefits to every resident of a state who meets eligibility requirements. Table 2 provides a brief description of each of the programs covered in this report and the types of benefits offered by each program. The programs covered by this review represent both entitlement and non- entitlement programs; programs that are administered entirely by federal agencies and those that are administered through federal partnerships with state and/or local agencies; programs that allow substantial state and local variation and those that provide uniform benefits throughout the country. Table 3 summarizes the level of government with whom responsibility for funding and design resides for each of the 12 programs. Although state and local agencies responsible for administering several of the programs have some control over program design and implementation, primary responsibility for setting priorities, guiding policy, and measuring performance rests with the federal agencies that oversee the programs. The programs covered by this review may have many different goals and objectives of varying degrees of importance, but all of these programs— regardless of size, target population, funding structure, or types of benefits offered—were established to assist persons with limited income, and as such, all were tasked with the overarching goal of reaching and serving those eligible for program benefits or services. Likewise, all means-tested programs share the common goal of ensuring that the funds allocated for program benefits are provided only to those eligible. A key factor in achieving desired program outcomes, including program access and program integrity, is the implementation of appropriate internal control. As discussed in our prior work on this topic, internal control is an integral component of an organization’s management that provides reasonable assurance that agencies are achieving outcomes related to the effectiveness and efficiency of operations and compliance with laws and regulations, among other things. Federal agencies have several key management tools and program reports that they use to provide information about the programs they administer, develop policy, help with management decision-making, and help focus program administrators at all levels of government on achieving the federal agency’s highest priorities. For example, through their strategic and annual performance plans and accountability reports, federal agencies set program goals, measure program performance against those goals, and report publicly on their progress. Some programs also issue annual or biennial reports to Congress on specific programs they administer; these generally include important program information. A number of governmentwide initiatives have resulted in increased emphasis by program managers on program integrity issues, including OMB guidance, the President’s Management Agenda, GAO’s High-Risk series and the Improper Payments Information Act of 2002 (IPIA). The IPIA requires the head of each federal agency to annually review all programs and activities that the agency administers and to identify all such programs and activities that may be susceptible to significant improper payments. For each program and activity identified, the agency is required to estimate the annual amount of improper payments and submit those estimates to Congress before March 31 of the following applicable year. OMB guidance then directs federal agencies to include a measure of improper payments in their annual Performance and Accountability Reports. All 12 programs we reviewed are subject to these requirements. The proportion of those eligible who are actually enrolled in 12 selected low-income programs varies substantially both between and within programs, but several factors must be considered to understand the implications of this information for program access. The estimated proportion of eligible people who were enrolled in entitlement programs— those designed to support all those who apply and qualify—ranged from about 50 percent to more than 70 percent. In contrast, the estimated proportion of the eligible who were enrolled in non-entitlement programs—those with limited funding and not necessarily intended to cover all eligible persons—ranged from less than 10 percent to about 50 percent. Within programs, we found that subpopulations were enrolled in different proportions. Some evidence also suggests that enrollees in some programs, such as the Food Stamp Program, tend to be those who are eligible for larger benefit amounts. For four of the five entitlement programs we examined, the proportion of eligible people who were enrolled varied from around 50 percent in the Food Stamp Program to more than 70 percent in the EITC and SSI programs; and within programs, different types of participants, such as children or the elderly, were enrolled in varying proportions. Table 4 provides estimated participation rates for each of these programs, expressed in ranges to reflect potential errors in sample survey data. The actual participation rates may be outside the range of estimates shown because some types of uncertainty in the estimation of participation rates cannot be quantified. Estimates for the Food Stamp, Medicaid and SSI programs were developed by the Urban Institute under contract with HHS and Food Stamp Program estimates were developed by Mathematica Policy Research, Inc., under contract with USDA. HHS and USDA are the only two agencies to regularly estimate participation rates in low-income programs. We estimated the EITC participation rate for 1999. However, we were unable to estimate an enrollment rate for the Pell Grant program because of concerns about the reliability of some of the data needed to estimate the rate. These estimates indicate that between half and three quarters of those eligible are participating in four of the entitlement programs. Although differences in years, data sources, and estimation methodologies make it inappropriate to compare participation rates across programs, these estimates provide a general sense of the extent to which programs are reaching those eligible for benefits. Specifically, we found: For the EITC program, we estimated in prior work that about 75 percent of eligible households took advantage of this credit in 1999. This estimate was adjusted to account for tax dollars that were distributed in error that year. However, Congress has enacted new tax laws and the IRS has taken steps to improve EITC program compliance. Two organizations, the Urban Institute and Mathematica Policy Research, Inc., have estimated food stamp participation rates using different methodologies but both found that about 48 percent of eligible households participated in this program in 2001 and 2002, respectively. In addition, Mathematica found that 54 percent of eligible individuals were enrolled in 2002. An estimated 66 to 70 percent of eligible, noninstitutionalized people were enrolled in Medicaid in 2000. This estimate does not include institutionalized people, such as those in nursing homes. We were unable to estimate Pell Grant participation rates because we were unable to assess the reliability of available data on the family income of enrolled students who did not apply for federal financial aid. For SSI, an estimated 66 to 73 percent of eligible adult individuals and married couples received benefits in 2001. This estimate also does not include institutionalized people or disabled children. Participation rates also can vary substantially even within a single program. Disaggregating program participation rates by targeted subpopulations can help us to better understand the implications of overall program participation rates. In table 5, we provide participation rate estimates for selected subgroups within the four entitlement programs for which we have participation rate estimates. As in table 4, these estimates are expressed in ranges to reflect potential errors that result from using sample survey data. (See the footnotes to table 5 for more details.) As shown, participation in low-income programs varies markedly across subgroups. For example, a smaller share of elderly people eligible for low income programs tend to participate in the Food Stamps and Medicaid programs than among the total eligible population. The elderly may participate in the Food Stamp Program at a lower rate than other households because most elderly households receive Social Security and are eligible for relatively small food stamp benefits. For example, in 2000, 44 percent of all households with elderly members eligible for food stamps were eligible for a monthly benefit of only $10 or less, the minimum benefit for households of one or two persons. In comparison, 12 percent of households without elderly members eligible for food stamps receive benefits that low. Similarly, Medicaid participation among the elderly may be low because Medicare also covers many elderly people who are eligible for Medicaid. In contrast, families with children tend to participate in food stamps, Medicaid, and the EITC at higher than average rates than those households without children. Although we were unable to disaggregate participation rates by geographic area, program participation rates can also vary by state or locality. Information on trends in program participation rates over time can also help in interpreting participation rate estimates, but we were only able to provide information on trends in participation for one program. Mathematica Policy Research, Inc., estimates food stamp participation rates annually under contract with USDA and has taken steps to ensure that estimates are comparable over time. As shown in figure 1, food stamp participation rates remained fairly stable between fiscal years 1999 and 2002, declining slightly from 52 percent in fiscal year 1999 to 48 percent in fiscal year 2002 among eligible households and 56 percent in fiscal 1999 to 54 percent in fiscal year 2002 among eligible individuals. We were not able to provide information on trends in participation rates for the Medicaid and SSI programs because the most recent participation rate data available for these programs is not comparable to prior year estimates. While prior year estimates are available, because of changes from 1 year to the next in the methodology used to estimate participation rates, estimates for prior years are not perfectly comparable with the most recent estimates and are therefore not shown in this report. The participation rate estimate for the EITC was available for only 1 year. Among the seven non-entitlement programs we reviewed, the share of those eligible who participate ranges from less than 10 percent to about 50 percent. These programs are generally not funded to serve all eligible applicants, and many have other design features, such as the prioritization of certain subgroups and eligibility criteria specific to a state or locality, that would not necessarily allow for all eligible people who apply to receive benefits. Consequently, we refer to these estimates as coverage rates rather than participation rates. Table 6 provides estimated coverage rates for each of these programs, expressed in ranges to reflect potential errors in survey data. The actual coverage rates may be within a broader range of estimates than shown because other errors that may have resulted from calculating these estimates could not be quantified. Estimates for the CCDF, SCHIP, and TANF cash assistance programs were developed by the Urban Institute under contract with HHS. We also include a WIC estimate developed by the National Research Council, and another WIC estimate developed by the Urban Institute under contract with us. We estimated the Head Start and housing programs using administrative and national survey data. Generally less than half of those eligible participate in the seven non- entitlement programs. Coverage rates also have limitations such as data sources, and estimation methodologies that make it inappropriate to compare the estimates across programs. However, they provide a general sense of the extent to which these programs are reaching eligible people. Specifically, we found: Almost 20 percent of children who meet state-defined eligibility criteria are receiving child care services through CCDF. This estimate does not reflect participation in child care funded by other federal sources. HHS estimates that about 26 percent of CCDF-eligible children are receiving child care services through either CCDF (including the Child Care and Development Block Grant, state CCDF funds or TANF transfers to CCDF), or child care services funded directly through the Social Services Block Grant (SSBG), TANF, or TANF state funds. The Head Start program funded enough slots to serve about 44 to 54 percent of eligible 3- to 4-year-old low-income children in 2003. An estimated 13 to 15 percent of households eligible for Housing Choice Vouchers on the basis of income both received a voucher and were able to successfully lease a housing unit in 1999, the most recent year for which these data were available. In addition, less than 10 percent of households eligible on the basis of income were served through the Public Housing program in 1999. While HCV and public housing are the two largest federal housing programs, there are other federal, state, and local housing programs from which eligible households could receive assistance. HUD estimated that in 1999 about a quarter of all households eligible for any kind of housing assistance received assistance. In 2000, about 44 to 51 percent of eligible children participated in SCHIP. Since 2000, SCHIP enrollment has increased by nearly 3 million children, but the impact this has had on the coverage rate is not known because information on how the eligible population may have changed over this time period is not available. In addition, because states’ implementation of their programs varied, awareness of SCHIP may lag in states that created their programs more recently. About half of all eligible households receive cash assistance through TANF. This estimate does not account for families that receive other services, such as transportation and child care, that are offered through this program, but who do not receive cash assistance. WIC participation rates were available from two sources. The National Research Council using the Survey of Income and Program Participation found that 51 percent of eligible infants, children ages 1 to 4 and pregnant women were enrolled in WIC in 1998. The Urban Institute, using the Current Population Survey, found that about 51 to 55 percent of eligible infants and children participated in 2001. Coverage rates for these programs can also vary substantially by subgroup, and they do vary within the TANF and WIC programs, the only non-entitlement programs for which we have this information. Understanding the extent to which different subgroups are covered by non-entitlement programs can be particularly important precisely because these programs are not necessarily funded to cover all those eligible. Table 7 provides coverage rates for groups of people eligible for TANF cash assistance and WIC. As shown, families with no income earners tend to receive TANF cash assistance at a higher rate in the TANF program than families with earners or two-parent families. The data also suggest that families with immigrants have a lower coverage rate than families without immigrants. As noted earlier, some families within these subpopulations may be receiving other services funded by TANF, although data are not available on this. The participation rate among infants eligible for WIC is higher than among children ages 1 to 4. We were unable to provide estimates of changes in coverage rates over time for most of the non-entitlement programs covered in this review, but we did find an increase in the coverage rate for the Head Start program over the past several years. Since 1997, Head Start coverage rates have increased from about 40 percent to 50 percent. However during this time period, the coverage rate increased between 2000 and 2001 from about 50 percent to 58 percent and then gradually declined. The coverage rate increased by this amount within 1 year because slots increased by nearly 40,000 for the Head Start program while the number of children eligible decreased by about nearly 130,000. Since 2001 the number of funded Head Start slots has increased, but the coverage rate fell because the child poverty rate, and thus the number of eligible children, increased. Figure 2 shows Head Start coverage rate estimates for 1997 to 2003. Because of changes in the methodology used to estimate coverage rates from 1 year to the next, we cannot reliably compare the most recent coverage rate estimates for SCHIP and TANF to those of prior years, but there is compelling evidence that coverage rates for these two programs changed significantly over time. SCHIP was first implemented in 1997 and the number of children in the program grew from 660,351 in fiscal year 1998 to over 3 million in fiscal year 2000. As states continued to reach out to eligible children in subsequent years, participation continued to increase to nearly 6 million in fiscal year 2003. This eightfold increase in the number of children enrolled in SCHIP since fiscal year 1998 almost certainly had a significant impact on the coverage rate. Meanwhile, as states implemented welfare reforms during the strong economy of the late 1990s and other changes occurred in programs serving low-income families, the number of families receiving TANF cash assistance declined, falling by about 50 percent between fiscal years 1997 and 2003. This also likely had a significant impact on the program coverage rate. HHS has reported that about 70 percent of families eligible for TANF cash assistance were enrolled in the program in 1997, compared to less than 50 percent in 2001, but we were unable to quantify how much of this change was caused by changes in estimation methodology. It is also important to note that states’ TANF programs have changed over this time. States have more flexibility in the types of non-cash assistance they may provide families, and some families eligible for cash assistance may be receiving other forms of aid instead. In addition, some families or individuals that may appear eligible according to the model may not be participating because they have not complied with program requirements, such as being involved in work activities. Our estimates of the costs of providing benefits to eligible non-participants show that for some programs, those currently participating in the programs are generally eligible for a greater benefit amount than those not participating. For these programs, the estimated costs of serving those eligible but not currently receiving benefits may be less than one might expect based on the participation or coverage rates we estimated. This is not surprising, as it makes sense that, for example, a person eligible for a $10 food stamp benefit might be more likely to forgo that benefit than a person eligible for a $150 benefit. More specifically, Mathematica found that the 48 percent of households participating in the Food Stamp Program in fiscal year 2001 received about 62 percent of the total amount of benefits that would be paid out if all eligible households received benefits. As shown in table 8, we were able to estimate the additional cost of providing benefits to eligible nonparticipants for 6 of the 12 programs we reviewed. These cost estimates take into consideration the characteristics of non-participants and the benefits for which they would be eligible but do not account for increases in administrative costs that could result from participation increases. We were unable to estimate the cost of providing benefits to eligible, non-participants in the six other programs—CCDF, HCV, Medicaid, Pell Grants, Public Housing, and SCHIP—because we did not have enough information to determine how the characteristics of the non-participants would have affected the benefit amounts they could have received. Although Medicaid is by far the largest program we reviewed, developing reliable estimates of the costs of serving those eligible but not enrolled in the Medicaid program is difficult for a number of reasons. These reasons include a lack of information about the health status of eligible non- participants, the many variables that affect health care costs, and the open-ended nature of health care benefits. The costs included in the table do not reflect the total costs that would be incurred if all eligible people enrolled in these programs. Probable increases in administrative costs that would be incurred are not included, and we did not estimate how the cost of goods and services offered through the Food Stamp, Head Start, and WIC programs would change if more participants were demanding them. However, the costs do include some additional costs that would be incurred by states in programs where states are required to cover some of the program costs. Recognizing the differences in goals, design, administration, and funding in the 12 programs, it may be neither feasible nor desirable to provide program benefits to all those eligible. Because alternative programs could offer the similar benefits and services as the programs we reviewed, some of these programs, especially those with limited funding, may be best administered by only serving a certain subgroup of their eligible population. For example, in localities where school systems offer pre- kindergarten classes to 4-year-old children, Head Start programs may want to focus more on enrolling 3-year-olds from low-income families. Also, limited administrative resources may prevent federal, state, and local agencies from serving all those eligible. Full participation among eligible people also may not be feasible because some choose not to enroll in means-tested programs. Given these constraints, some programs may focus on targeting their resources to those most in need of program services. Finally, while participation and coverage rate estimates as well as estimates of potential program costs provide important program information that can be useful to both policymakers and program administrators, these estimates must be interpreted carefully to take into consideration such factors as survey data, research methodology, timeliness of estimates, and the availability of alternative programs. These factors limit our ability to compare rates across programs and would need to be considered in efforts to define appropriate or desired participation or coverage rate levels. For a detailed discussion of the factors that affect use of these estimates, see appendix II. Many factors influence access to means-tested programs, including the benefits provided by the program, ease of access, misperceptions about program requirements, and eligibility verification procedures put in place to ensure program integrity, based on our literature review and agency interviews. These factors influence participation by affecting the number of people who participate in a program as well as the type of people who participate. Entitlement programs may focus on addressing factors that affect access in order to increase program participation. However, because coverage rates in non-entitlement programs are determined primarily by funding levels, non-entitlement programs are more likely to be concerned about the impact of these factors on other aspects of program access, such as the composition of the program caseload and how the program interacts with alternative programs that provide similar benefits. The size and type of program benefits can affect whether or not an individual participates in a program. Numerous studies show that the size or value of the benefit influences program participation, and this depends largely on the structure of program benefits. Some programs, such as the Food Stamp Program, determine benefit levels based on income, allowing a three-person household to receive as little as $1 per month depending on household income. Other programs, such as Medicaid, generally offer comparable benefits to every resident of a state who meets eligibility requirements. A recent National Bureau of Economic Research study showed that across a range of programs and within programs, larger benefits were associated with higher participation and coverage rates. In addition, our literature review, site visits, and analysis of participation rates for selected programs showed that participation and coverage rates tend to be higher among subgroups eligible for larger benefits. For example: Elderly individuals are generally eligible for small food stamp benefits; their participation rate in the program is lower than for other groups. Families with infants participate in WIC at higher rates than families with older children, in part because the value of the WIC voucher is greater for families with infants. WIC officials in Connecticut reported to us that 10 percent of families stopped participating in the program when their youngest child reached age 1. On average, families with children who are eligible for the EITC receive a higher EITC benefit than individuals and families without children, and they participate at a higher rate. The type of benefits offered can also influence whether someone eligible for a program participates. Some programs—such as EITC and SSI—offer cash benefits while other programs—such as Head Start and Medicaid— offer direct services, such as educational or health services. Our research on participation in low-income programs generally shows that participation and coverage rates are higher among programs that provide cash benefits than among programs that provide direct services. One reason for this difference is the flexibility cash benefits give to individuals. Although the recipient may need the services provided by programs in which they are enrolled, these types of benefits do not allow individuals to shift resources away from program purposes toward what they might consider more pressing needs. Our site visits confirmed that the type of benefits influence participation and coverage rates. For example, we found that: SSI recipients who participated in a pilot project that allowed them to receive their food stamp allotment in cash expressed a strong preference for this over traditional food stamp coupons. Some individuals who need subsidized housing may prefer the Housing Choice Voucher program, which allows individuals to choose their housing in neighborhoods that offer better educational and employment opportunities or choose to remain in a place while paying less rent, over the Public Housing program that does not give the individuals flexibility to choose where they live. Factors that influence the ease with which potential participants can access a program—including office hours, program location, and the ability of program participants to redeem or use their benefits—can also affect the number and groups of people who participate in the programs. Several of the programs we reviewed require applicants to visit the program office to establish and maintain eligibility. For instance, local WIC, TANF, and Food Stamp Program offices typically require face-to-face interviews before individuals can receive benefits. Those programs that keep traditional office hours—8:00 a.m. to 5:00 p.m.—pose a barrier to potential applicants who work and would have to take time away from their job in order to apply. Studies on child care and WIC programs identify traditional office hours as a barrier for working families. Similarly, Medicaid officials in California told us that one of their barriers to participation is office hours that do not accommodate working families. Although many program officials suggested that having flexible office hours is important to participants, some offices are challenged to extend their operating hours. WIC officials in Connecticut told us that they have attempted to promote extended hours and have made some progress; however, instituting extended hours remains problematic due to limited funding and contracts governing the workforce. The location of the program office can also affect participation and caseload composition. For many individuals—like the elderly, individuals with disabilities, and families living in rural areas—traveling to a program office that is outside the limits of their available mode of transportation makes it difficult for them to receive needed benefits. The USDA published in its National Survey of WIC Participants that one of the top barriers in the WIC program is transportation with 30 percent of participants reporting that they missed appointments because they lack transportation to the office. Studies on the Housing Choice Voucher, child care, Head Start, and Food Stamp programs reported similar findings. Many state and local officials we visited agreed that transportation is a barrier to participation. A TANF, Food Stamp, and Medicaid official in Washington County, Maryland, told us that public transportation is limited and getting to and from the program offices poses a barrier to participation for many individuals, especially those in rural communities. According to officials, participants without vehicles have to seek rides from family members or acquaintances to access services. For many of these participants being seen going to the welfare office is difficult and sometimes stigmatizing. Some programs—including child care, Housing Choice Voucher, and Medicaid—offer benefits that can be difficult for participants to use, as some service providers—landlords, day care workers, or health care providers—will not exchange their services for program benefits. For example, our prior work found that the proportion of providers who will accept child care subsidies varied widely by state, ranging from 23 to 90 percent. Even in cases where providers accepted subsidies, the number of slots for children that used child care subsidies was limited. Additionally, several state and local officials suggested that participants are sometimes challenged to find health care providers that accept Medicaid. According to officials in Chisago County, Minnesota, participants have to drive up to 200 miles to visit a dentist that accepts Medicaid. From our literature review and interviews with program officials, we also found that many individuals do not participate in low-income programs because they do not know that they are potentially eligible for benefits. Numerous studies have documented instances where participation was compromised because individuals were unaware of program benefits or had misconceptions about eligibility. For example, several EITC, Medicaid, Food Stamp, Head Start, and SSI studies indicate that one of the primary barriers to participation is that individuals do not know that they are eligible for these benefits. For some individuals—like the elderly and non-English speakers—this unfamiliarity with program benefits is even more widespread, creating a larger barrier to participation and an under representation of these individuals in the caseload. Many program officials we visited agreed and explained that individuals also have misconceptions about program eligibility. For example, some individuals do not believe that they are eligible for benefits because they are employed while others do not want to be attached to the perceived stigma associated with the programs. In Los Angeles, Medicaid officials noted that rumors circulated about the eligibility criteria for Medicaid prevent many potential recipients from applying for the program. Particularly in non-English speaking communities, information about social services is often received through word of mouth; thus, when incorrect information circulates, it can have a significant impact on participation. Eligibility verification requirements—rules put in place to improve program integrity by ensuring that only those eligible for program benefits receive them—can also affect the overall number and characteristics of people who participate in the program. Each low-income program in this study has a set of verification requirements that individuals must complete to establish and maintain eligibility. Common requirements among the programs include completing application forms and providing necessary documentation. In addition, some programs require applicants to take additional steps, such as attending face-to-face interviews, documenting parental or spousal assets, or participating in orientation classes. According to our literature review, the complexity of verification requirements can impact the number of enrollees, especially for individuals with mental disabilities or who are homeless. One WIC study reviewed participation rate differences among states and found that states that required applicants to provide proof of income (before it was federally mandated) and had stricter program rules had lower program participation than states that did not require income documentation. Additionally, another study examined EITC participation rates across states and found that differences in participation rates are due in part to the applicant having help completing the complex tax forms. Many state and local officials agree that strict and/or complicated verification requirements can decrease participation, particularly among certain groups of people. For example, we found: According to officials, the Pell Grant application is very long and complicated and can be difficult for students and their parents to complete. Staff from an organization in St. Paul, Minnesota, dedicated to assisting low-income students to access higher education told us that many low-income students in the area would not be able to complete the forms correctly without their assistance. CCDF Officials in Connecticut and Georgia told us that the application process can be complex and difficult for applicants and, as a result, many applicants submit their applications late or incomplete. Because there is very high demand for child care subsidies, these families are often denied benefits or removed from the waiting list. Local SSI officials told us that participants face many life changes such as frequent hospitalization and institutionalization, moving into different family households, and changes in the hours that they work. To remain eligible for program benefits, SSI recipients must report these types of changes within 10 days from the end of the month of the change. Finally, while each program has its own set of verification requirements, these requirements become even more challenging when participants are applying or maintaining eligibility for multiple programs. Program officials in Maryland told us that one of the biggest barriers to accessing multiple means-tested programs is the many different eligibility criteria and reporting requirements of the various programs. According to state officials in Maryland, the TANF and Food Stamp Programs are relatively well aligned, but Medicaid has not coordinated as much with the other programs. According to officials, this can be problematic because a participant who is turned down for one program might assume that he or she is ineligible for other low-income programs and may fail to apply for benefits for which they are eligible. Factors that influence participation also impact other aspects of program access such as targeting and program interactions among all low-income programs, but particularly among non-entitlement programs whose enrollment levels are determined largely by funding levels. The non- entitlement programs covered in this review—CCDF, Head Start, Housing Choice Vouchers, Public Housing, SCHIP, and TANF—have funding limitations that could restrict the total number of people who could potentially participate in the programs and, as a result, coverage rates for these programs may be determined, at least in part, by funding. However, among programs that allow states substantial flexibility in determining program eligibility and implementation such as CCDF, SCHIP, and TANF, funding constraints contribute to, but do not determine coverage rates to the extent that they do for programs that allow less state and local flexibility. Given funding constraints for non-entitlement programs, agencies are challenged to allocate scarce resources appropriately by targeting their benefits to specific groups of people and planning strategically to ensure that the program complements a broader range of programs administered by the same agency or that provide similar services or benefits to the program’s eligible population. Because factors that influence participation often affect the composition of a program’s caseload, some agencies that administer programs with limited funding have put measures in place to ensure that their caseloads reflect program priorities—whether that involves targeting certain groups or ensuring that benefits do not disproportionately favor or exclude certain subpopulations. For example, although the public housing program generally does not target benefits to households with the lowest incomes, it allows priority to be given to elderly and disabled recipients. Agency officials reported that they track participation of these groups to ensure that their share of the total caseload does not change dramatically from 1 year to the next. Similarly, state child care officials told us that funds are generally provided to recipients based on priority groups that favor families receiving public assistance and those with the greatest financial need. Additionally, many agencies are cognizant of how their programs interact with and complement other programs that serve the same population. For example, some child care programs pair with half-day Head Start programs to provide continuous care to children of working parents; Medicaid and SCHIP programs within some states coordinate their enrollment processes to facilitate access to health insurance for individuals in the state; and between 1998 and 2003, HUD responded to a decrease in the number of public housing units available for low-income households by increasing resources available through its voucher program to maintain coverage for families. Likewise, in allocating TANF resources, programs often coordinate with local workforce development agencies, child care programs, and other programs that provide similar services to best meet the needs of their clients without duplicating an existing effort. In these ways, programs acknowledge and respond to access issues and ways in which factors affect access other than participation levels and rates. Program administrators have implemented many strategies to achieve desired program outcomes, including those related to program access and program integrity, but while agencies have generally taken steps to monitor and disseminate information on program integrity, few track and report on the extent to which they are serving their eligible populations. The programs we reviewed have many goals and objectives of varying degrees of importance to the agencies that administer them, among them program access and program integrity. Strategies implemented at the federal, state, and local level to address these two issues include information systems, data sharing, and technological innovation, changes to the application and eligibility verification process, and outreach and coordination with other programs. Although federal agencies do not have direct control over many of the strategies we identified—including those mandated by law and those initiated at the state and local level—federal managers can play a role in encouraging and facilitating such strategies by emphasizing program access and program integrity as federal agency priorities. In response to the Improper Payments Information Act of 2002, all of the federal agencies we reviewed have taken at least some steps to identify and begin reporting information to Congress and others on the extent of improper payments. We also found, however, that for several of the programs we reviewed, federal agencies have not taken steps to identify and use participation or coverage rate information in managing their programs. Having up-to-date information on the extent to which their programs reach eligible individuals can help agencies plan strategically, set priorities, and ensure that agencies are reaching eligible families. The state, local and federal program officials we spoke with identified several strategies that they believe may improve either of the two objectives—program access or program integrity—without harming, and in many cases improving, the other. As mentioned, some efforts to increase program integrity and prevent fraud, such as increasing the amount of eligibility verification required, may actually hurt access to the program by deterring even those eligible from applying. However, program administrators told us of several strategies that increase access while maintaining and even improving integrity. The complementary strategies we identified are enabled by information systems, data sharing, and technological innovations, changes in the application and eligibility verification process, and outreach and coordination with other programs. Improved information systems, sharing of data between programs, and use of new technologies can help programs to better verify eligibility and make the application process more efficient and less error prone. These strategies can improve integrity not only by preventing outright abuse of programs, but also by reducing chances for client or caseworker error or misunderstanding. They can also help programs reach out to populations who may face barriers. One strategy involves sharing verified eligibility information about applicants across programs. Data sharing prevents applicants from having to submit identical verification to multiple programs for which they may be eligible, and it can also speed up the sometimes-lengthy application process. In addition, data sharing allows programs to check the veracity of information they receive from applicants with other databases. In Minnesota, WIC caseworkers are able at the time of application to determine participant eligibility by accessing basic eligibility information via technology systems from other means-tested programs, such as Medicaid, food stamps and TANF. SSI administrators told us that during the application interview, income data is entered in their computer system. This information is then checked with a number of other databases including those of the IRS, the Department of Veterans Affairs, and the state Civil Service Administration to quickly verify earnings and other eligibility requirements and inconsistencies are flagged. Similarly, Georgia has an interactive computer system that aggregates client information for TANF, Medicaid, and the Food Stamp Program and calculates benefits for all three programs. Additionally, when clients need to make a change in their eligibility information, these data are automatically changed for all three programs, so that clients can receive the appropriate level of benefits based on their most current eligibility information. Furthermore, the data reliability matches may include information from the Department of Labor wage match, SSI benefits, prison information, and information on a person’s death. If any of the matched information conflicts with the information provided by the client, a caseworker is to ask additional questions of the client. In all these ways, caseworkers can accelerate the application process while capitalizing on verified eligibility information already provided to other programs. Some administrators told us that such data sharing, however, can be complicated by concerns over ensuring privacy and by insufficient technological capacity. Local program administrators told us that eligibility data for Medicaid and SCHIP is tightly controlled because of Health Insurance Portability and Accountability Act (HIPAA)—a law that limits access to an individual’s health information—but that its data might be shared, if warranted, with proper consent. Data sharing can be impeded by technological limitations, such as computer systems that cannot communicate directly with other systems over the Internet or some other network, or a lack of software needed to translate information into formats that other computers can understand. Our prior work on data sharing identifies strategies agencies have implemented to address concerns about privacy and technological capacity issues. Some agency officials told us of ways in which on-line applications can improve both access and integrity. As stated, program integrity is compromised not only by willful misrepresentation, but also by applicant and caseworker error. Web-based or partially web-based applications can automatically check that all required fields are completed before an application is submitted for review and automatically calculate benefits thereby reducing error. Moreover, having the option of an on-line application can increase access to those who are eligible for benefits but who may have difficulty physically getting to program offices. Minnesota has instituted an on-line interactive application for Medicaid that program administrators believe will make the application process easier for both participants and caseworkers. In addition to making the process easier, the system will also check verification information with a variety of other data sources and thus reduce the likelihood of errors as well. In this way, a potentially burdensome application process becomes simpler, more accessible, and less error prone. Similarly, eight states accept food stamp applications through the Internet. Of course, this strategy is less viable or effective where access to computers is limited or where the on-line environment cannot be adequately secured. Program administrators told us about several changes in the application and eligibility verification process that have improved their ability to promote access and ensure integrity. Efforts to increase the accuracy of eligibility and benefit determination can increase access by reducing the number of applicants who were incorrectly denied benefits or whose benefit determinations resulted in underpayments. For example, streamlining or simplifying the application and providing applications in other languages can increase access, but also promote program integrity by reducing errors or misunderstanding in the application process. Simplifying applications by clarifying confusing wording and removing redundant questions as well as providing applications in an applicant’s native language can reduce the possibility of these types of errors. According to federal officials, most states use a simplified application form for the SCHIP program to remove application barriers for families. For example, the SCHIP program applications in both Connecticut and California have been reduced from 17 and 27 pages respectively to only 4 pages each without sacrificing required information, according to state officials. In many cases, the SCHIP streamlined application forms caused corresponding changes in state Medicaid applications as well. In addition, many of the program administrators with whom we spoke told us that their applications and forms were available in many languages. For example, the Minnesota Department of Revenue now has state EITC tax forms and fact sheets directing them to the federal EITC in eleven languages. Another way in which programs can streamline the application process is through categorical eligibility with other programs, which can be set at the federal or state level depending on the program. Categorical eligibility, also known as adjunctive eligibility, allows an individual who has been found eligible for one program to be automatically granted eligibility for another program, typically one with less stringent eligibility criteria. For example, if an individual is receiving SSI, federal legislation generally requires that that person be automatically eligible for Medicaid. Similarly, if a pregnant woman is receiving Food Stamps, Medicaid, or TANF, then she automatically qualifies for WIC benefits—and thus does not need to provide income verification once again when applying for the program. States also have flexibility to grant automatic eligibility for other programs. A state WIC program, for example, may grant automatic eligibility for families receiving Free and Reduced Price School lunches. These adjunctive or automatic eligibility policies allow ultimately for simpler applications, which may enhance access and reduce error. In fact, federal administrators at USDA noted that adjunctive eligibility is one of the most important tools now used to address program integrity and access issues in a way that cuts across programs. The provision of more comprehensive in-person assistance in filling out applications can encourage a candidate eligible for benefits to complete an otherwise lengthy, complicated, or intimidating application process. Such personal assistance can also prevent errors that result from misunderstanding of application questions or requirements or even fraud by reminding applicants in person that fraudulent claims are punishable by law. For example, to increase access to the program, California program officials told us that the SCHIP program developed a training process that certified staff from other entities, such as schools and community-based organizations, as “application assistants.” These “application assistants” are also trained to recognize when applicants seem to be submitting false information and are prohibited from assisting families who have previously been found to have committed fraud. In a Maryland SSA office, SSI program administrators told us that they had abbreviated their application form so that most information is now collected in an interview. This process helps improve access for those with limited literacy or those who may be discouraged by a long paper application. Officials also noted that this process helps program integrity because the interviews allow caseworkers the opportunity to remind clients that fraudulent claims are punishable by law. Similarly, EITC officials in Minnesota told us that free tax preparation assistance could make the process less complicated for filers and could also cut down on fraud from tax preparers. As one official explained, many low-income families live near a high concentration of paid tax preparers, who have incentives to fraudulently file for a high credit. While more in depth application assistance has these benefits, it can pose challenges to programs in ensuring the quality of the assistance offered and it can be costly. According to California SCHIP officials, funding to train “application assistants” for the SCHIP program in California was ended in May 2002 due to budget constraints. Lastly, some policies put in place to prevent fraud at the time of application can also help with program access. Connecticut Department of Social Services has begun a fraud prevention program, termed FRED (Fraud Early Detection), which was instituted to address an increase in the amount of fraud and error detected in the program. The purpose of FRED is to identify potential fraud cases before benefits are paid out to prevent improper payments rather than identifying fraud after the payments have been made. Under FRED, cases that meet 1 of 12 risk criteria are to be referred to a fraud investigator who is to visit the home within 10 days of the referral. While the investigator is visiting the home, he/she is to interview the client about aspects of the risk criteria, and make a recommendation regarding eligibility. While the primary purpose of the visit is to prevent fraud, in practice investigators have found that their role is also to explain the eligibility criteria more clearly to applicants and to explain what steps they need to take in order to be eligible for program benefits. In addition, investigators are trained to provide additional information to the family on other resources available to them and to assist them with referrals, thereby increasing access to an array of related social services. Targeted outreach to populations that might have more barriers to accessing the program has the potential to increase access without necessarily compromising integrity. Many program officials we spoke with told us that they had outreach strategies to reach out to populations—such as rural-dwellers, the elderly, or those with limited English proficiency— that have had trouble accessing the program. Such strategies include information sessions or pamphlets in ethnic community centers or partnering with advocacy groups. In addition, cross agency referrals for applicants already found to be eligible and more overall agency coordination can improve access without sacrificing integrity. Many agency officials with whom we spoke told us that they coordinated with other programs to reach potential clients. In Maryland, the Department of Social Services invites the Volunteer Income Tax Assistance program to work out of its office, so that those low-income earners already in contact with social services can have better access to the EITC. Some offices in California participate in an open door policy program in which clients can access any social service program through referrals at any state government office they walk in to. Some program administrators told us that program co-location can help increase access. This happens when an individual applying for one program in an office is referred to and immediately serviced by another program in that same location. Some examples we found had Food Stamps located in TANF offices and a WIC clinic collocated with the state Children’s Health Insurance Program. All of the programs we reviewed emphasize both program access and program integrity, and as we have described, many federal, state, and local program administrators have implemented strategies intended to achieve access and integrity goals. However, not all agencies responsible for administering these programs have established management practices, in keeping with standards of internal control, that will consistently guide them in achieving these outcomes. Among the standards that are particularly relevant for agencies responsible for administering means- tested programs are: establishing and maintaining a control environment, a culture of accountability that sets a positive and supportive attitude toward achieving management objectives; monitoring program performance over time; and recording and communicating relevant, reliable, and useful information to management and others who need it to carry out their internal control and operational responsibilities. To achieve desired program outcomes and safeguard federal funds, these standards should be part of an agency’s operational and management practices. While the agencies we reviewed have taken steps to establish internal controls for improper payments and program integrity, not all have established similar controls for achieving desired program access outcomes. There are many ways in which federal agencies can establish a culture of accountability, one that “sets the tone” for program administrators at all levels of government to emphasize certain priorities. One way to do this is to monitor progress toward achieving desired program outcomes, and another is to effectively communicate program information in a broad sense, with information flowing down, across, and up the organization. Depending on the program, some aspects of an achievement-oriented environment are codified in laws, regulations, and federal policies. For example, the Improper Payments Information Act of 2002 requires those programs and activities susceptible to significant erroneous payments to calculate annual improper payment estimates and sets statistical sampling confidence and precision levels for estimating those payments. As shown in table 9, some of the federal agencies covered by this review have already begun to monitor improper payments for the programs they administer and, as directed by OMB guidance, communicate this information by including a measure of improper payments in their annual Performance and Accountability Reports. Including measures of improper payments in agency annual performance plans and accountability reports is one way to provide officials with important information on areas of success and areas that need improvement and to send a signal to all working on agency programs that the measured goal is a priority. (For information on the amounts of improper payments reported by agencies, see app.III.) To varying degrees, the other agencies included in this review have begun taking steps to identify and report on improper payments as well. While agencies are taking steps, much remains to be accomplished before a comprehensive picture is available of the amount of improper payments for these programs. While an internal control framework is emerging for addressing financial program integrity issues, few of the agencies responsible for administering the programs we reviewed have established a similar framework for achieving desired program access outcomes, although they have implemented numerous strategies to increase program participation. The 12 programs we reviewed have numerous program goals and objectives of varying degrees of importance to the agencies that administer them. Because the most fundamental purpose of these programs is to serve low- income individuals and families, all track measures that provide some information about program participation and access. For example: All of agencies responsible for administering the programs we reviewed track the number of people participating in their programs. Some federal agencies—such as HUD—measure the extent to which program participants redeem or use benefits provided to them. Others use other measures related to access. CMS tracks the number of individuals who are uninsured each year. Many agencies track participants and participant outcomes through program effectiveness studies. Through these efforts, agencies have demonstrated their concern about program access, yet, the ways in which most of these agencies measure program participation do not inform administrators about the extent to which they are meeting overall need and therefore do not provide all the information they need to monitor access. As discussed above, access encompasses not only the number of program participants, but also the extent to which programs reach the total population eligible for benefits and services, how well agencies are allocating resources among targeted subpopulations, and, from an agencywide or even governmentwide perspective, how well specific means-tested programs complement and interact with programs that serve similar populations or provide for similar needs. While concerns about the allocation of scarce resources and interactions with other programs apply to all low-income programs, they may be of particular importance to non-entitlement programs whose participation is limited by funding constraints. Participation or coverage rate information can guide program administrators in setting priorities and targeting scarce resources, even among programs that were not intended to serve everyone eligible for program benefits. As shown in table 10, only one of the agencies we reviewed, USDA, regularly estimates participation rates for the programs it administers and communicates and disseminates information on these rates in a way that promotes a culture of accountability supportive of achieving program access outcomes. USDA has been estimating participation rates annually for the Food Stamp Program since 1975. The agency uses this information to get a better understanding of how well they are reaching certain priority subpopulations such as the working poor, single-parent families with children, and SSI recipients; and to identify states in need of outreach assistance. In addition, USDA has established a performance goal to increase participation rates in the Food Stamp Program and reports food stamp participation rates in its annual performance report. In these ways, the agency uses this information for program management purposes. USDA has taken steps to develop a reliable participation rate measure for the WIC program and plans to estimate the WIC participation rate annually. Because the WIC program is not an entitlement and participation is determined by the appropriated funds, FNS officials told us they do not plan to establish a performance goal related to the WIC participation rate. However, officials told us that they do think it is important to monitor and report on the WIC participation rate for policy, planning, and budgeting purposes, and the agency plans to use these data in managing the program by highlighting the measure in the program’s budget reports and its annual report to Congress. HHS plays a key role in estimating participation rates for several means- tested programs. Since 1973, HHS’s Office of the Assistant Secretary for Planning and Evaluation has funded TRIM3 for the purposes of policy development, analysis, and research on such topics as the interactive effects of programs serving low-income families. The Welfare Indicators Act of 1994, requires HHS to submit annual reports to Congress on welfare receipt in the United States and key indicators and predictors of welfare dependence. These reports, produced annually since 1997, include participation and coverage rates from TRIM3 for TANF (and its predecessor program, Aid to Families With Dependent Children), SSI, and food stamps. HHS includes CCDF coverage rates in the biennial congressional report and plans to include a performance measure related to participation rates in its annual performance reports starting in fiscal year 2006. However, HHS generally does not use participation rate estimates it has available from TRIM3 in managing its other programs by highlighting the information in its annual performance plans or congressionally mandated program reports. For example, TANF participation rates are not included in the agency’s TANF Annual Report to Congress and Medicaid and SCHIP participation and coverage rates are not included in any of the other congressionally mandated reports disseminated by CMS, the agency that administers these programs. Only one of the other agencies we reviewed, the IRS, has plans to estimate and report on participation rates for the programs they administer. IRS plans to begin estimating the participation rate in the EITC program on an annual basis starting in fiscal year 2005 and to use the EITC participation rate as a performance measure in its annual performance report. However, the other agencies we reviewed, including SSA, HUD, and ED, do not estimate participation or coverage rates for the SSI, Housing Choice Voucher, Public housing, or Pell Grant programs and reported no plans to do so. There are several reasons agency officials cited for not collecting participation rate information. For some programs, information on certain eligibility criteria can be difficult or costly to obtain. For example, reliable data on the disability status of children who do not receive SSI is not readily available from national survey data. We were unable to provide a participation rate estimate for this group for this reason. Absent a legislative or other mandate to estimate participation and coverage rates, agency officials may not consider conducting such estimates a priority. However, some agency officials that do not regularly estimate participation or coverage rates indicated they would find such estimates useful. For example, HUD officials indicated that the agency finds its estimates of worst case housing needs, which include some coverage rate measures for all housing programs, useful for policy and planning purposes. Similarly, while Head Start officials do not publish or report coverage rate estimates in any agency documents, they indicated that they occasionally estimate participation rates informally for internal use in policy, planning, and budgeting. Federal agencies responsible for administering means-tested programs are charged with ensuring that those eligible for program benefits and services are able to access them and with ensuring prudent oversight of taxpayer dollars by maintaining program integrity, including preventing improper payments. Program administrators may find it challenging to achieve these goals in part because they may conflict—ensuring program integrity can potentially come at the expense of program access. While we identified a number of strategies that have been implemented by federal, state, and local agencies that could potentially achieve both of these goals, unless agencies track progress toward meeting these goals in a way that signals to program administrators at all levels of government that both access and integrity are federal priorities, there is a risk that one of the goals may be compromised. Estimating participation rates for means-tested programs is difficult—and more difficult for some than for others—and cannot be considered “an exact science.” Nevertheless, when done rigorously—in a way that ensures that estimates are comparable over time and quantifies the errors that result from the estimation methodology—these estimates can provide a basic understanding of the extent to which needy populations are being served by federal programs and can be a key component of a federal agency’s efforts to establish a culture of accountability that emphasizes the importance of program access. Federal agencies responsible for administering only four of the programs we covered in this review—CCDF, food stamps, WIC, and EITC—either currently collect and report information on the extent to which they are reaching their target populations in key performance and program reports or plan to do so. As a result, the federal agencies that administer the other nine programs covered by this review may lack data that could inform their budgetary and programmatic decisions, assist them in ensuring that their programs are coordinated with and appropriately complement other programs available to their target populations, help them to manage their programs effectively, and enable them to provide policymakers with the information they need to make decisions. As the department moves forward with participation rate estimates for the WIC program, we recommend that the Secretary: 1. take steps to clarify to users the limitations of the estimates; and 2. comparability between estimates by reanalyzing data as estimation methodologies change, so that consistent methods are applied over time. To help ensure that agencies have information on program access, we recommend that the Secretaries of Education and HUD study the feasibility of calculating participation or coverage rates and including them in key program management reports. We recommend that the Secretary of HHS consider making some improvements to the participation and coverage rate information produced for the CCDF, Medicaid, SCHIP, and TANF programs, such as: 1. quantifying errors that result from calculating these estimates to help users better understand the accuracy of the data; and 2. ensuring, to the extent possible, that estimates are comparable over time. We also recommend that the Secretary include participation and coverage rate estimates in key program reports for these four programs. We also recommend that the Secretary study the feasibility of estimating the coverage rate for the Head Start program on a regular basis and to include these estimates in key Head Start program reports. As the IRS moves forward on developing participation rate estimates to use as a program performance measure for the Earned Income Tax Credit, we recommend that the Commissioner of the Internal Revenue Service take steps to quantify errors that may result from estimating these participation rates to help users better understand the accuracy of the data and ensure that estimates will be comparable over time. To help ensure that the agency has information on program access, we recommend that the Commissioner consider the feasibility of providing participation rate information (from the existing source or another source) in SSA program management reports. We provided drafts of this report to and received comments from the Departments of Agriculture, Education, Health and Human Services, and Housing and Urban Development; the Internal Revenue Service; and the Social Security Administration. They generally agreed with our conclusions and recommendations. Agency written comments appear in appendixes IV through VII. On February 3, 2005, we met with FNS officials to discuss their comments. The officials said they agreed with our conclusions and recommendations. They stated that they recognize the importance of tracking both program access and program integrity and their ongoing efforts to estimate participation rates in the food stamp program reflect their commitment to balancing the goals of access and integrity. They stated that as they move forward in developing a participation rate estimate for the WIC program, they plan to take steps to clarify to users the limitations of the estimates and to ensure that the estimates will be comparable over time. Agency officials also provided technical comments, which we incorporated in the report where appropriate. The Department of Education agreed that data sources now available would not provide sufficient information to develop a reliable participation rate estimate for the Pell Grant program. However, the department cited a study currently being conducted by the National Center for Education Statistics that will determine the feasibility of implementing a system of collecting data on all postsecondary students. This study will also provide information that could be used to examine the feasibility of estimating participation rates for the Pell Grant program. The Department of Health and Human Services provided comments related to each of the five programs under its jurisdiction. The department noted that it has taken steps to measure program access in the TANF, CCDF, Medicaid, and SCHIP programs through their funding of TRIM3, although they do not always report these estimates in key program reports. With regard to CCDF, HHS recognized the importance of coupling efforts to control improper payments with efforts to provide effective service delivery, and therefore access. The department noted that it has recently established a performance measure related to coverage rates for the CCDF program. We incorporated this information into the report. HHS also thought that we overstated the differences between CCDF and TANF in the impact of state flexibility on coverage rates so we changed that section of the report. With regard to TANF, HHS raised the concern that increasing coverage rates may conflict with other TANF program goals and consequently, coverage rates are not an appropriate performance measure for the TANF program. We recognize that increasing the coverage rate is not an explicit goal of TANF and believe this concern is consistent with the report’s conclusion that increasing program access may not be feasible or desirable for some programs. Nevertheless, we continue to believe that including program participation and coverage rates in key program reports can help inform policymakers and program administrators at all levels of government and assist them making budgetary and programmatic decisions. In its discussion of SCHIP and Medicaid, HHS indicated that the report reinforced the agency’s approach to promoting both access and integrity. The department noted that CMS is working to improve its coverage rate estimates for SCHIP and meanwhile, it continues to measure progress toward increasing coverage among children under 200 percent of poverty, a proxy for the program coverage rate. HHS also highlighted several other issues that we believe are already sufficiently discussed in the report. These include the fact that not all those eligible and not participating need program services; that some programs allow states considerable flexibility in implementing programs and determining eligibility; that participation or coverage rates can be challenging to estimate accurately; and that uncertainties and limitations surrounding participation and coverage rate estimates should be made clear to users of this information. HHS also reiterated some of the limitations of our cost estimates and our Head Start coverage rate estimates. Agency officials also provided technical comments, which we incorporated in the report where appropriate. Department of Housing and Urban Development officials provided us with technical comments, which we incorporated in the report where appropriate. The Internal Revenue Service agreed with our conclusions and recommendation. The IRS recognizes the interactions between efforts to improve program access and those intended to improve program integrity, and as part of their efforts to utilize a balanced approach that emphasizes both goals, the IRS has recently established the EITC participation rate as a GPRA measure. As it moves forward in developing the EITC participation rate, the IRS plans to take steps to quantify errors that may result from estimating these participation rates to help users better understand the accuracy of the data and ensure that estimates will be comparable over time. Agency officials also provided technical comments, which we incorporated in the report where appropriate. The Social Security Administration agreed with our conclusions and recommendation. The agency noted that it has considered the feasibility of estimating participation rates in the past and has calculated participation rates among the elderly. However, the agency also noted that limitations of the national survey data make such estimates challenging for the SSI program. The agency agreed that estimating participation rates on a regular basis could provide an important management tool. As agreed with your office, unless you publicly announce its contents earlier, we plan no further distribution of this report until 30 days after its issue date. At that time we will send copies of this report to the Secretaries of the Departments of Agriculture, Education, Health and Human Services, and Housing and Urban Development; the Commissioners of the Internal Revenue Service and the Social Security Administration; relevant congressional committees; and others who are interested. Copies will be made available to others upon request, and this report will also be available on GAO’s Web site at http://www.gao.gov. If you or your staff have any questions about this report, please contact me on (415) 904-2272. Additional GAO contacts and acknowledgments are listed in appendix VIII. We designed our study to provide information on (1) the proportion of those eligible who are participating in 12 selected low-income programs; (2) the factors that influence participation in those programs; and (3) strategies used by federal, state, and local administrators to improve both access and integrity, and whether agencies monitor access by measuring participation rates. To obtain information on these issues, we compiled estimates of participation and coverage rates for each of the programs covered by the review for the most recent year for which data were available, we reviewed literature on participation in programs for low-income people, and we gathered information directly from both federal program officials and state and local administrators. To determine the completeness and accuracy of data obtained from various sources, we took several steps, described below, to assess the data and determined that the data were sufficiently reliable for use in this report. We performed this work between November 2003 and January 2005 in accordance with generally accepted government auditing standards. To obtain information on the proportion of those eligible who are participating in 12 selected low-income programs, we used information developed by the Urban Institute under contract with HHS about the participation and coverage rates they estimated for 7 programs—CCDF, Medicaid, TANF, food stamps, SCHIP, SSI, and WIC. Also, we estimated the coverage rates for the Head Start program using administrative data and CPS data and for the Housing Choice Voucher and Public Housing programs using data from a HUD report on worst case housing needs in 1999. The participation rate estimate for the EITC program was from our previous work. In addition, we performed a literature review to obtain information about program participation and coverage rates that were estimated by other organizations. When possible, we obtained rates from 1997 to the most recent year available, but as mentioned in the report, we did not present many estimates of rates prior to the most recent year available because changes in methodologies did not allow us to determine whether changes in the rates over time were actual changes in participation rates or resulted from changes to the estimation methodology. We were unable to provide a Pell Grant program participation rate because we were unable to assess the reliability of available data on the family income of students who did not apply for federal financial assistance, which is necessary for determining program eligibility. Table 11 summarizes the methodologies used to calculate participation and coverage rates for the 12 programs covered in this review. The Urban Institute estimated participation and coverage rates for CCDF, Medicaid, TANF, food stamps, SCHIP, SSI, and WIC under a contract with the Department of Health and Human Services (HHS). In order to evaluate the reliability of these data and to determine whether it met our standards for reporting quantitative information, we contracted with the Urban Institute to obtain additional information about these estimates and the methodologies used to calculate them, including the Transfer Income Model, version 3 (TRIM3). The TRIM3 microsimulation model was used to determine the number of people who would be eligible for a program if they applied. This model simulates the process that a caseworker would undergo to determine eligibility by reviewing individual or household characteristics such as household composition, income, disability, and other factors as appropriate for the programs. TRIM3 primarily relies on the Census Bureau’s Annual Social and Economic Supplement to the Current Population Survey to estimate the eligible population. For some programs, this data source does not include all information needed to determine a person’s or household’s eligibility. For example, the data do not include information on the value of certain assets that might be considered during eligibility determination for some programs. In these instances, the Urban Institute researchers used TRIM3 to assign eligibility-related characteristics to individuals included in the CPS who they believed were likely to have them, a process referred to as imputation. The estimates of the eligible population were used as the denominators of the participation and coverage rates, and administrative data on the number of participants were generally used as the numerator. In general, groups excluded from the TRIM3 eligibility estimate used for the denominator (such as those who are institutionalized) were also excluded from the administrative data used for the numerator. The CPS data limitations and the process of assigning characteristics may have resulted in errors in the estimates of the eligible population and, therefore, the participation and coverage rates for seven programs. These include sampling error, non-sampling error, error related to the imputation process, and error related to program implementation. GAO statisticians and social science analysts reviewed the Urban Institute’s TRIM3 technical documentation, interviewed the Urban Institute researchers, requested additional TRIM3 calculations from the Urban Institute, and reviewed available academic and government literature on the sources of error in microsimulation models of low-income program participation to determine what errors existed. Although there are several types of potential errors, not all the errors could be quantified. The CPS, like all sample surveys, is subject to sampling error. This error reflects the difference between (1) the results that are obtained from the members of the sample that are actually surveyed and (2) the results that would be obtained if each member of the population were surveyed. We contracted with the Urban Institute to calculate the sampling error of CPS data used in TRIM3, and we verified that they used the appropriate procedures to make these calculations. We used the estimates of sampling error provided by the Urban Institute to calculate a range for the most recent TRIM3 estimates at the 95 percent confidence level, and these ranges are presented in the report. However, the ranges underestimate the total error in TRIM3 estimates. The CPS data used in TRIM3 are also subject to non-sampling error that has not been quantified. These errors can occur if survey respondents have difficulty interpreting a particular question, lack information necessary to answer a question, are uncomfortable with accurately reporting certain sensitive information, or do not answer certain questions, among other factors that affect data collection and measurement. Such non-sampling errors are likely to have affected variables that are used by TRIM3, such as labor force participation for example. According to a 2002 Census Bureau report, the 1996 CPS covers a smaller proportion of the Black population (84 percent) than it does of the White population (94 percent). The Census Bureau reported that this low coverage rate biases labor force estimates, because those who are left out of the sampling frame are quite different from those who are included in it. Yet, the full extent of non-sampling error in the CPS is unknown. The process of assigning characteristics when CPS data are not available—the imputation process—also can produce error. In most instances, efforts were not made to quantify the error associated with these imputed data. However, a National Research Council (NRC) panel attempted to quantify such error when reviewing methods for estimating participation rates for WIC and found that estimates can vary noticeably depending on whether imputed or reported monthly income data are used to determine eligibility. During this review, the NRC panel compared TRIM-adjusted CPS data, in which monthly income is imputed on the basis of annual income, and Survey of Income and Program Participation (SIPP) data, in which monthly income is collected directly from survey respondents. Specification error can result when the variables in a microsimulation model incorrectly represent the process for determining program eligibility that actually occurs between caseworkers and applicants. For example, in its TANF module, TRIM3 does not consider certain aspects of program eligibility, including specific work requirements, behavioral requirements such as school attendance and immunizations, and sanctions from failing to comply with work rules or child support rules. These exclusions could cause TRIM3 to overestimate eligibility and therefore underestimate participation and coverage rates. Similarly, while several means-tested programs base their eligibility on the federal poverty guidelines, there is no universal administrative definition of “family,” or “household” that is valid for all programs that use the poverty guidelines. To the extent that federal programs use administrative definitions that differ somewhat from the statistical definitions used by the CPS, estimates of the eligible population could be affected. We estimated the participation and coverage rates for the Head Start, Housing Choice Vouchers, Public Housing, and EITC (in prior work). These estimates are also limited by the data sources and assumptions of who may be eligible for these programs. The EITC and Head Start rates were estimated using the CPS and, therefore, estimates are subject to sampling and non-sampling errors mentioned earlier. In addition, because the CPS did not have complete information to determine who may be eligible for the EITC, we made assumptions about whether children were in a household long enough for them to be counted as a member for tax purposes. We also assumed that the lack of data on certain assets would not significantly affect participation rate estimates. For Head Start, the administrative data did not allow us to determine the number of children who are actually served in the program. The data were only on the number of program slots funded, and more than one child can be served with each slot over the course of a program year if there is turnover in participation. However, for the purposes of calculating Head Start coverage rates, we assumed that only one child filled a slot. We used a HUD report on the households with worst case housing needs in 1999 and administrative data to estimate the Housing Choice Vouchers and Public Housing coverage rates. HUD used data from the American Housing Survey in this report. We assessed the reliability of the survey data and determined that the data were sufficiently reliable for use in this report. In conducting this assessment, we reviewed Bureau of the Census studies on the survey. Census reported that the American Housing Survey underestimates income and overestimates poverty for households, variables used to determine the number of people with housing needs. We were unable to quantify the error this may have produced in the estimates. We determined that the administrative data used to estimate participation and coverage rates were reasonably reliable for this purpose. As a part of this assessment, we reviewed the data on the number of participants and we discussed this information with federal agency officials. However, with the exception of the EITC data, we did not adjust the number of participants to account for those who may have received program benefits and/or services in error. As a result, the administrative data could have produced errors in the estimates due to potential inaccuracies in reporting the number of eligible participants. To obtain the estimated cost of providing benefits to those eligible and not participating in the Food Stamp Program, SSI, TANF cash assistance and WIC, we contracted with the Urban Institute to provide us with these estimates. The organization used the TRIM3 model to estimate the total benefit amount for eligible non-participants, and these estimates were based on the amount that each individual or household would receive based on their characteristics. These estimates have similar limitations as their related participation and coverage rates, and not all of their errors could be quantified. The EITC cost estimate was based on our prior work, but the Head Start cost estimates were done during the course of this project. We estimated the potential costs for Head Start using administrative data on the average cost per slot and the number of eligible non-participating children we estimated using the CPS. We assume that only one child would be served with a slot, even though in actuality more one than can. We also did not account for variation in program cost at the local level, and we did not account for variation in local eligibility criteria. All of the estimates have two major limitations. We did not include the administrative costs of serving the non-participants; this would increase the cost estimates for all programs. For some programs, federal, state, and local governments would share these administrative costs. We also did not factor in policy or economic changes that may occur if participation increased in these programs. In addition, for all programs, we calculated the estimates for each program individually and we did not account for how changes in the participation for one program could influence benefit amounts in another. We were unable to estimate the cost of serving eligible, non-participants in the five other programs—CCDF, HCV, Medicaid, Pell Grants, Public Housing, and SCHIP—because we did not have enough information to determine how the characteristics of the non-participants would have affected the benefit amounts they could have received. To obtain information about factors that affect participation and strategies to improve access and integrity for the 12 selected programs, we conducted a literature review, obtained documentation from federal officials, interviewed federal officials and interviewed state and local officials in California, Connecticut, Georgia, Maryland, and Minnesota. The literature review consisted of studies on factors that affect participation and program integrity issues that we found through searches of the Internet and social science research databases and recommendations from federal agency officials. Among the documentation we reviewed for this objective were the available fiscal year 2004 and 2005 annual plans for each program and agency reports to Congress to determine whether the relevant agencies had stated measures for program integrity and access outcomes. We selected states to visit primarily based on their innovative practices to address barriers to participation for multiple programs we reviewed. We obtained information on innovative practices from federal officials, federal agency publications and a database on state and local initiatives complied by the Administration for Children and Families and several non-profit, non-partisan agencies. We also considered state efforts to ensure program integrity, program aspects that may create barriers to access and demographic and geographic diversity in making our selection. We were not able to address all the programs we reviewed during every site visit, and information from these site visits cannot be generalized to all states and localities and to all programs we reviewed. In addition, we did not assess the effectiveness of the strategies we presented. While participation and coverage rate estimates provide important program information that can be useful to both policymakers and program administrators, these estimates must be interpreted carefully to take into consideration such factors as survey data, research methodology, timeliness of estimates and the availability of alternative programs. These factors limit our ability to compare rates across programs and must be considered in efforts to define appropriate or desired participation or coverage rate levels. There are two national household level surveys conducted by the Census Bureau that can be used to estimate the total number of people eligible for low-income programs, the Annual Social and Economic Supplement to the Current Population Survey (CPS) and the Survey of Income and Program Participation (SIPP) and each has advantages and disadvantages. The CPS is the larger of the two surveys and data from this survey are available annually for the prior year. In addition, it has detailed information about income, household composition, labor force participation, and receipt of many federal benefits, but it does not include all the information that may be needed to determine program eligibility. For example: Although the value of assets such as automobiles and savings accounts are considered when determining financial eligibility for some of programs we reviewed, the CPS does not collect some of these data. The CPS also omits institutionalized individuals, some of whom may be eligible for Medicaid and SSI. Researchers at the Urban Institute and Mathematica told us that, while they were aware of these disadvantages, they continue to use CPS data in their calculations because of the relatively large sample size and because the CPS is conducted annually, which makes it a good source for yearly snapshots of participation. To compensate for the limitations in the data, researchers either make assumptions and assign information needed to determine eligibility, such as asset values, to individuals in order to determine their program eligibility or they omit certain subpopulations such as institutionalized individuals or pregnant and postpartum women from their participation rate estimates. The SIPP is a smaller survey than the CPS, but because it was designed specifically to better measure low-income program participation, it has some advantages over the CPS. Specifically, it includes more detailed information about individual characteristics, monthly labor force activity, monthly income, and household assets that factor in program eligibility determinations. However, the SIPP is designed as a panel study (following the same individuals for 2½ to 4 years) and thus may be more suited for use in examining detailed characteristics of participants and reasons for movement into and out of social programs. In addition, the sample faces attrition over the survey period, and some data needed to determine eligibility are available only for a limited number of years. The National Research Council used the SIPP to estimate WIC participation rates. This estimate included pregnant women in addition to infants and children, but by 2003 when this estimate was published, the most recent estimate they could create using SIPP was for 1998. There are some low-income programs for which neither the CPS nor the SIPP provide sufficient information to estimate participation rates. For example, to estimate the proportion of enrolled students eligible for a Pell Grant would require information on student enrollment status in addition to family income information. The National Center for Education Statistics within the Department of Education conducts a survey, the National Postsecondary Student Aid Study, that includes both student enrollment and family income information. However, concerns have been raised about the reliability of the family income data for students who did not apply for federal financial assistance. We were unable to assess the reliability of this data element and thus were unable to determine whether the data were sufficiently reliable for our purposes. As a result, we did not estimate a participation rate for this program. Because no existing national data provide every piece of information needed to determine the exact size of the eligible population for low- income programs, all participation rate estimates involve certain assumptions and generalizations. These assumptions can create errors that are difficult or impossible to quantify. Consequently, the margins of error we present, which only capture errors that result from sampling, could understate the true range within which participation rate estimates are most likely to fall. One way to better understand how these estimates are affected by the research methodology is to compare them to alternative participation rate estimates that have been calculated using different assumptions. While the Urban Institute and Mathematica Policy Research, Inc., both estimate food stamp participation rates based on CPS data, they use slightly different assumptions to estimate the eligible population. For example, because the CPS does not include information on which household members purchase and prepare food together, model estimates had to make assumptions about household food preparation habits. Despite differences in assumptions, the participation rates estimated by the Urban Institute and Mathematica were very similar. The most recent participation rate data available varies by program, and all estimates are at least 3 years old. As a result, changes in legislation, state policy, program administration, the national economy, and other factors that may have influenced the participation rate over the past few years are not reflected in these estimates. The EITC participation rate estimate is based, in part, on an estimated 32 percent of EITC claims being made in error in 1999. Since that time, Congress has enacted new tax laws and the IRS has taken steps to improve compliance. The total number of people receiving food stamps and Medicaid fell after passage of the Personal Responsibility and Work Opportunity Reconciliation Act of 1996 when participation in these programs was “de-linked” from participation in TANF. Since 2000, however, states have implemented policies to ensure that those eligible for food stamps and Medicaid continue to receive benefits when they leave TANF. Since 2000, the national economy has emerged from a recession, but economic growth, until recently, has been slow and uneven and marked by slow job growth. Economic conditions have historically been correlated with low-income program participation. None of these factors are reflected in the numbers we presented in this report. When interpreting the participation and coverage rate estimates we provided, it is important to keep in mind that those eligible but not participating in the programs we reviewed may not be living without assistance; many could be receiving assistance from alternative programs. In some cases, people could be eligible for more than one program we reviewed and able to receive similar services from these programs. Those eligible could also have access to state and local programs that address similar needs. This is particularly relevant for the non-entitlement programs covered by our review. The coverage rates we provide for the two housing programs in this review are calculated in isolation, and as a result, some of the households that appear eligible but not participating in the Public Housing program are receiving Housing Choice Vouchers (HCV), and vice versa. In addition, while HCV and public housing are two of the largest federal housing programs, there are several other federal, state, and local housing programs from which eligible households could receive assistance. HUD estimated that in 1999 about a quarter of all households eligible for any kind of housing assistance received assistance. The availability of alternative programs could also affect coverage rates for CCDF and Head Start. For example, state-financed pre-school programs provide child care and educational development services for many 4-year-olds who appear eligible but are not enrolled in Head Start. Children could be eligible for both programs but only receiving services in one, but this would not be reflected in program coverage rate estimates. HHS officials have recognized that other federal programs, such as TANF and Social Services Block Grant (SSBG), also provide child care to children eligible for CCDF. Because the CCDF participation rate does not reflect these additional sources of federal child care funds, HHS has produced a different coverage rate, estimating that about 26 percent of CCDF-eligible children were receiving child care services through one of four federal funding streams—CCDF, SSBG, TANF, and TANF state funds in 2001. State and localities are able to set the eligibility criteria for some of these programs, and the cost estimates do not account for the policy changes agencies may make if the current criteria resulted in increased participation. For example, if states found that current eligibility limits may result in increased TANF participation, they may change eligibility criteria or benefit levels to ensure state costs do not increase. Either of these changes may reduce the total additional costs. All cost estimates were calculated individually and, therefore, do not account for how participation changes in one program may influence benefit amounts in another. For example, Food Stamp Program costs may not be as high if participation in the SSI program increased because some eligible non-participants would qualify for lower food stamp benefits due to the cash assistance. Also, as mentioned earlier, other federal, state, and local programs may provide similar benefits that non-participants could be receiving, and, therefore, they may not need or want the benefits from the programs we covered. For example, food stamp eligible non-participants with short-term nutritional needs may decide to receive assistance through food banks. In addition, the TANF estimate we provide is only the cost of providing cash assistance to eligible people who are not participating; this program offers other supports to needy families, such as transportation to work and child care, that is funded by the federal and state government. Carolyn Blocker, Cheri Harrington, Danielle Giese, Amanda Mackison, and Kim Siegal also made significant contributions to this report. Jay Smale, Mark Braza, Doug Sloane, Ed Nannenhorn, and Beverly Ross provided technical assistance in developing and evaluating the reliability of participation rate and potential program cost estimates; Lise Levie provided key technical assistance; and Johnnie Barnes, Carrie Watkins, and Charles Wilson provided information on the two housing programs covered in the report. Food Stamp Program: Farm Bill Options Ease Administrative Burden, but Opportunities Exist to Streamline Participant Reporting Rules among Programs. GAO-04-916. Washington, D.C.: September 16, 2004. Food Stamp Program: Steps Have Been Taken to Increase Participation of Working Families, but Better Tracking of Efforts Is Needed. GAO-04-346. Washington, D.C.: March 5, 2004. SSA Disability Decision Making: Additional Steps Needed to Ensure Accuracy and Fairness of Decisions at the Hearing Level. GAO-04-14. Washington, D.C.: November 12, 2003. Federal Student Aid: Expanding Eligibility for Less Than Halftime Students Could Increase Program Costs, but Benefits Uncertain. GAO-03-905. Washington, D.C.: September 10, 2003. Social Security Disability: Reviews of Beneficiaries’ Disability Status Require Continued Attention to Improve Service Delivery. GAO-03-1027T. Washington, D.C.: July 24, 2003. Welfare Reform: States Provide TANF-Funded Work Support Services to Many Low-Income Families Who Do Not Receive Cash Assistance. GAO-02-615T. Washington, D.C.: April 10, 2002. Food Stamp Program: States’ Use of Options and Waivers to Improve Program Administration and Promote Access. GAO-02-409. Washington, D.C.: February 22, 2002. Medicaid and SCHIP: States’ Enrollment and Payment Policies Can Affect Children’s Access to Care. GAO-01-883. Washington, D.C.: September 10, 2001. Food Stamp Program: Program Integrity and Participation Challenges. GAO-01-881T. Washington, D.C.: June 27, 2001. Medicaid and SCHIP: Comparisons of Outreach, Enrollment Practices, and Benefits. HEHS-00-86. Washington, D.C.: April 14, 2000. Medicaid Enrollment: Amid Declines, State Efforts to Ensure Coverage after Welfare Reform Vary. HEHS-99-163. Washington, D.C.: September 10, 1999. Food Stamp Program: Various Factors Have Led to Declining Participation. RCED-99-185. Washington, D.C.: July 2, 1999. Medicaid: Demographics of Nonenrolled Children Suggest State Outreach Strategies. HEHS-98-93. Washington, D.C.: March 20, 1998.

Summary: Federal agencies that administer means-tested programs are responsible for both ensuring that people have appropriate access to assistance and ensuring the integrity of the programs they oversee. To balance these two priorities appropriately, it is important for agencies to have information on program integrity and program access. Knowing the proportion of the population that qualifies for these programs relative to the numbers who actually participate can help ensure that agencies can monitor and communicate key information on program access. To better understand participation in low-income programs, this report provides information on: (1) the proportion of those eligible who are participating in 12 selected low-income programs; (2) factors that influence participation in those programs; and (3) strategies used by federal, state, and local administrators to improve both access and integrity, and whether agencies monitor access by measuring participation rates. For 12 federal programs supporting low-income people, we found that the proportion of those eligible who are enrolled varies substantially both between and within programs. Among entitlement programs--those programs that provide benefits to all applicants that meet program eligibility criteria--these rates range from about 50 to more than 70 percent. Among non-entitlement programs--those with limited funding--these rates ranged from less than 10 percent to more than 50 percent. While it may be neither feasible nor desirable for programs to serve 100 percent of those eligible for benefits, information on the share of those eligible who are enrolled in means-tested programs and on particular recipient groups such as the elderly or families with children, can help program managers more effectively address issues related to program access. However, participation rate estimates must be interpreted carefully because of limitations in the data sources and estimation methodologies used to calculate the estimates. Many factors influence access to low-income programs--including the type of benefits, ease of access, misperceptions about program requirements, and application and eligibility verification procedures. These factors can impact not only the share of eligible people who participate in low-income programs, but other aspects of program access as well, including the composition of the program caseload and how programs work together to serve low-income individuals and families. Federal, state, and local administrators have implemented many strategies to achieve the goals of access and integrity, but federal agencies generally put more emphasis on tracking information and outcomes related to program integrity than program access. To better ensure that program administrators achieve program integrity goals, agencies have begun to develop measures to track and report on program integrity. Federal agencies have developed participation rate estimates for several low-income programs, but only four--CCDF, food stamps, WIC, and EITC--either currently collect and report information on the extent to which they are reaching their target populations or plan to do so. Such information can guide administrators in setting priorities and targeting scarce resources, even among programs that were not intended to serve everyone eligible for program benefits.