Means-Tested Programs
Information on Program Access Can Be an Important Management Tool Gao ID: GAO-05-221 April 11, 2005Federal 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.
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Director: Team: Phone:GAO-05-221, Means-Tested Programs: Information on Program Access Can Be an Important Management Tool
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Report to the Ranking Minority Member, Committee on the Budget, House
of Representatives:
United States Government Accountability Office:
GAO:
March 2005:
Means-Tested Programs:
Information on Program Access Can Be an Important Management Tool:
GAO-05-221:
GAO Highlights:
Highlights of GAO-05-221, a report to the Ranking Minority Member,
Committee on the Budget, House of Representatives:
Why GAO Did This Study:
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.
What GAO Found:
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.
The 12 Federal Means Tested Programs Reviewed:
[See PDF for image]
[End of figure]
What GAO Recommends:
GAO recommends that the Secretaries and Commissioners whose programs do
not currently use participation rate information to consider using this
information in managing their programs. GAO makes technical
recommendations on how the usefulness of these measures could be
improved. The agencies generally agreed with our recommendations.
www.gao.gov/cgi-bin/getrpt?GAO-05-221.
To view the full product, including the scope and methodology, click on
the link above. For more information, contact David Bellis (415) 904-
2272 or bellisd@gao.gov.
[End of section]
Contents:
Letter:
Results in Brief:
Background:
Use of Federal Low-Income Assistance Varies Greatly by Program and by
Subgroup:
Many Factors Influence Participation but Their Impact on Entitlement
and Non-Entitlement Programs Differs:
Program Administrators Have Strategies That Improve Both Access and
Integrity, but Federal Agencies Have Generally Focused More on
Measuring Program Integrity Outcomes:
Conclusion:
Recommendations to Executive Agencies:
Agency Comments:
Appendix I: Objectives, Scope, and Methodology:
Appendix II: Limitations Affecting Use of Participation and Coverage
Rates:
Appendix III Estimates of Improper Payments for Programs Reviewed:
Appendix IV: Comments from the Department of Education:
Appendix V: Comments from the Department of Health and Human Services:
Appendix VI: Comments from the Department of the Treasury:
Appendix VII: Comments from the Social Security Administration:
Appendix VIII: GAO Contacts and Staff Acknowledgments:
GAO Contacts:
Staff Acknowledgments:
Related GAO Products:
Tables:
Table 1: Fiscal Year 2003 Annual Expenditures and Agencies Responsible
for Administering 12 Selected Low--Income Programs:
Table 2: Descriptions of 12 Low-Income Programs:
Table 3. Level of Government Responsible for Funding and Design of 12
Low-Income Programs:
Table 4: Estimated Participation Rates for Entitlement Programs for the
Most Recent Year Data Were Available:
Table 5: Available Subgroup Participation Rate Estimates for
Entitlement Programs for the Most Recent Year Data Were Available:
Table 6: Estimated Coverage Rates for Non-Entitlement Programs for the
Most Recent Year Data Were Available:
Table 7: Coverage Rate Estimates for TANF Cash Assistance and WIC
Subgroups for the Most Recent Year Data Were Available:
Table 8: Potential Cost of Providing Benefits to Eligible Non-
participants for the Most Recent Year Data Were Available:
Table 9: Status of Agencies Identification of and Reporting on the
Amounts of Improper Payments by Program:
Table 10: Status of Agencies Efforts to Use Information on
Participation or Coverage Rates in Managing Their Programs:
Table 11: Summary of Participation and Coverage Rate Methodologies:
Table 12: Improper Payment Estimates Reported in Agency Fiscal Year
2003 Performance and Accountability Reports:
Figures:
Figure 1: Food Stamp Participation Rate Estimates for Fiscal Years 1999
to 2002:
Figure 2: Head Start Coverage Rate Estimates for 1997 to 2003:
Abbreviations:
ACF: Administration for Children and Families:
CCDF: Child Care and Development Fund:
CMS: Centers for Medicare & Medicaid Services:
CPS: Annual Social and Economic Supplement to the Current Population
Survey:
ED: Department of Education:
EITC: Earned Income Tax Credit:
FNS: Food and Nutrition Service:
FRED: Fraud Early Detection:
FY: fiscal year:
HCV: Housing Choice Vouchers:
HHS: Department of Health and Human Services:
HIPAA: Health Insurance Portability and Accountability Act:
HUD: Department of Housing and Urban Development:
IPIA: Improper Payments Information Act:
IRS: Internal Revenue Service:
NRC: National Research Council:
OMB: Office of Management and Budget:
PRWORA: Personal Responsibility and Work Opportunity Reconciliation
Act:
SCHIP: State Children's Health Insurance Program:
SIPP: Survey of Income and Program Participation:
SSA: Social Security Administration:
SSBG: Social Security Block Grant:
SSI: Supplemental Security Income program:
TANF: Temporary Assistance for Needy Families:
TRIM3: Transfer Income Microsimulation Model, version 3:
USDA: Department of Agriculture:
WIC: Special Supplemental Nutrition Program for Women Infants, and
Children:
United States Government Accountability Office:
Washington, DC 20548:
March 11, 2005:
The Honorable John M. Spratt, Jr.:
Ranking Minority Member:
Committee on the Budget:
House of Representatives:
Dear Mr. Spratt:
Each year through more than 80 means-tested programs, the federal
government provides benefits and services to individuals and families
with low incomes--just 12 of which account for as much as $330 billion
in annual federal expenditures. As stewards of these funds, federal
agencies have many roles, among them: to ensure that people have
appropriate access to this assistance and to ensure the integrity of
these programs by guarding against improper payments and unqualified
participation. These responsibilities can be complementary, but they
can also be practiced in ways that work at cross purposes. Outreach
without appropriate screening, for example, can result in service to
the wrong recipients, but cumbersome enrollment procedures can
discourage those who qualify from applying. To meet requirements
related to the Improper Payments Information Act of 2002, federal
agencies administering these programs will be required to institute new
steps to assure integrity by annually measuring and reporting improper
payments. As they step-up efforts to ensure integrity, they will be
challenged, as well, to ensure appropriate access. Without a sense of
the proportion of the population that qualifies for these programs
relative to the numbers who actually participate, however, it may be
difficult for most agencies to know whether they have struck an
appropriate balance in the weight of their strategies and whether they
need to pursue methods that better serve both access and integrity.
To better understand participation in low-income programs, we have
agreed to provide you 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. The 12 programs included in this review
are among the largest and were selected to cover a range of benefits
and services aimed at supporting needy families and individuals. They
include: the Child Care and Development Fund (CCDF), the Earned Income
Tax Credit (EITC), the Special Supplemental Nutrition Program for
Women, Infants, and Children (WIC), the Food Stamp Program, the
Supplemental Security Income program (SSI), the Head Start program, the
Pell Grant program, the Medicaid program, the State Children's Health
Insurance Program (SCHIP), the Temporary Assistance for Needy Families
(TANF) program, the Housing Choice Voucher (HCV) program, and the
public housing program.
To address our research objectives, we compiled estimates of the
proportion of those eligible who participate in each of the programs
for the most recent year for which data were available[Footnote 1]
using different methodologies. We refer to this proportion as a
participation rate when discussing entitlement programs and other
programs that provide program benefits to all eligible applicants:
EITC, food stamps, Medicaid, Pell Grants, and SSI. We refer to it as a
coverage rate when discussing non-entitlement programs that do not
necessarily provide benefits to all eligible individuals who apply for
the program: CCDF, Head Start, Housing Choice Vouchers, Public Housing,
SCHIP, TANF, and WIC. For seven programs, we contracted with the Urban
Institute to provide us with information about their microsimulation
model estimates of participation rates.[Footnote 2] These model
estimates are also used to calculate estimates of the potential cost of
serving eligible nonparticipants in a subset of programs. For the
remaining programs, we provide participation or coverage rate estimates
based on administrative and national survey data. We held discussions
with federal agency officials to discuss the reliability of program
data used in our estimates, reviewed related documentation, and ensured
that the agencies conducted tests of the data for omissions and errors.
In addition, we reviewed literature on factors that influence
participation in the 12 programs covered by the review and strategies
to improve program access and program integrity. We surveyed and
interviewed the federal agencies that administer the 12 programs on
factors they have identified that influence program participation and
on strategies they have implemented to improve program access and
program integrity. In addition, we interviewed federal, state, and
local program administrators of various programs in California,
Connecticut, Georgia, Maryland, and Minnesota, on factors that affect
participation and strategies they have employed to address the goals of
program access and program integrity. These states were chosen on the
basis of innovative programs and initiatives related to program
integrity and program access and demographic and geographic diversity.
We performed this work between November 2003 and January 2005 in
accordance with generally accepted government auditing standards. See
appendix I for additional information on scope and methodology.
Results in Brief:
For 12 federal programs supporting low-income people, we found that the
proportion of those eligible who are actually enrolled varies
substantially both between programs and among subgroups enrolled in a
single program. Given the differences in the goals, design,
administration, and funding of the 12 programs, it is not surprising
that we found substantial variation in these proportions. For
entitlement programs--those designed to support all those who qualify-
-the estimated proportion of eligible people who were enrolled ranged
from about 50 percent to more than 70 percent. For example,
approximately three-quarters of those who were eligible took advantage
of the Earned Income Tax Credit program in 1999, the most recent year
for which data were available. For non-entitlement programs--those with
limited funding and not necessarily intended to cover all eligible
persons--the estimated proportion of the eligible who were enrolled
ranged from less than 10 percent to more than 50 percent. In the Head
Start program, for example, funded enrollment was sufficient to cover
half of all potentially eligible children in 2003. Within some
programs, we found that some subpopulations were enrolled in different
proportions than other groups. For example, in the Food Stamp Program,
the participation rate for families with children was higher than the
participation rate for other groups. Some evidence shows that enrollees
tended to be those among the eligible who had greater needs--as
indicated by the levels of assistance for which they qualified. While
information on participation rates can help program managers more
effectively address issues related to program access, several factors
must be taken into consideration when interpreting this information.
For example, because of limitations of the data and methodologies used
to measure rates of participation, we could not make statistically
reliable comparisons across programs nor could we describe fluctuations
over time for most programs.
The size and type of program benefits, ease of access, misperceptions
about program requirements and eligibility verification requirements
put in place to ensure program integrity can affect program access in
both entitlement and non-entitlement programs. For example, agency
officials told us that participation in the WIC program is highest
among infants in part because infants are eligible for the highest
benefits, but that factors such as extended office hours can also
impact participation. The factors we identified can affect several
aspects of program access, including 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.
Federal, state, and local administrators have implemented a variety of
strategies to achieve both program access and program integrity, but
federal agencies generally put more emphasis on tracking information
and outcomes related to program integrity than program access. Through
federal agency surveys and site visits, we identified several
strategies currently being used that have the potential to achieve two
of the fundamental goals common to all means-tested programs--program
access and program integrity. These strategies ranged from innovative
use of information technology to special outreach programs; some were
in use nationwide and others were state or local efforts. The
initiation and control of these strategies is often beyond the direct
control of the federal agencies managing the programs. However, federal
managers do play a role in that they encourage and facilitate such
strategies, even in the most decentralized program, by emphasizing the
importance of program access and program integrity--even absent
specific related laws or regulations related to these issues. The
Improper Payments Information Act of 2002 has built upon existing
governmentwide efforts to emphasize to federal agencies the importance
of having an internal control framework to address program integrity
issues. At the same time, internal controls are important management
tools to ensure that agencies meet their basic goals of reaching
eligible families. The federal agencies that oversee these entitlement
and non-entitlement programs can benefit from having up-to-date
information on the extent to which their programs reach eligible
individuals. However, while all of the programs we reviewed have begun
to take steps to measure the extent of improper payments and all make
efforts to assess how well their programs are working, 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.
To better ensure that agencies have information on program access, we
recommend to the Secretaries and Commissioners whose programs do not
currently use participation rate information to consider the use of
participation rate information in managing their programs. We also make
some technical recommendations on how the usefulness of these measures
could be improved. The agencies generally agreed with these
recommendations.
Background:
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.[Footnote 3] Table 1 shows the agencies responsible
for each program and federal expenditures for fiscal year 2003, the
most current year available.
Table 1: Fiscal Year 2003 Annual Expenditures and Agencies Responsible
for Administering 12 Selected Low--Income Programs:
Program: CCDF;
Agency: Department of Health and Human Services (HHS), Administration
for Children and Families (ACF);
FY 2003 federal expenditures (dollars in billions)[A]: $7.3.
Program: EITC;
Agency: Department of Treasury, Internal Revenue Service (IRS);
FY 2003 federal expenditures (dollars in billions)[A]: 37.9[B].
Program: Food Stamp Program;
Agency: Department of Agriculture (USDA), Food and Nutrition Service
(FNS);
FY 2003 federal expenditures (dollars in billions)[A]: 23.9.
Program: Head Start;
Agency: HHS/ACF;
FY 2003 federal expenditures (dollars in billions)[A]: 6.6.
Program: Housing Choice Voucher Program;
Agency: Department of Housing and Urban Development (HUD), Office of
Public and Indian Housing;
FY 2003 federal expenditures (dollars in billions)[A]: 13.4[C].
Program: Medicaid;
Agency: HHS, Centers for Medicare & Medicaid Services (CMS);
FY 2003 federal expenditures (dollars in billions)[A]: 160.7.
Program: Federal Pell Grant Program;
Agency: Department of Education (ED), Office of Federal Student Aid;
FY 2003 federal expenditures (dollars in billions)[A]: 12.1.
Program: Public Housing Program;
Agency: HUD, Office of Public and Indian Housing;
FY 2003 federal expenditures (dollars in billions)[A]: 7.6[D].
Program: SCHIP;
Agency: HHS/CMS;
FY 2003 federal expenditures (dollars in billions)[A]: 4.3.
Program: WIC;
Agency: USDA/FNS;
FY 2003 federal expenditures (dollars in billions)[A]: 4.5.
Program: SSI;
Agency: Social Security Administration (SSA);
FY 2003 federal expenditures (dollars in billions)[A]: 35.2.
Program: TANF;
Agency: HHS/ACF;
FY 2003 federal expenditures (dollars in billions)[A]: $16.3.
[End of table]
Source: Federal agency officials.
[A] This includes the total amount of federal expenditures in fiscal
year 2003, which is the most recent year for which these data were
available. It includes current and prior year federal funds expended in
fiscal year 2003; it does not include state expenditures.
[B] This includes both credits paid out in refunds and reduced tax
liabilities.
[C] This includes funding for the housing choice voucher and moderate
rehabilitation programs.
[D] This includes expenditures for the public housing capital fund, the
public housing operating fund, and revitalization of severely
distressed public housing (HOPE VI).
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.
Table 2: Descriptions of 12 Low-Income Programs:
Program: CCDF;
Description: The Personal Responsibility and Work Opportunity
Reconciliation Act of 1996 (PRWORA) authorized CCDF to help provide
child care to low-income families and to give states more flexibility
to design child care policies. CCDF is funded through an annual block
grant to states and required state funds and may also include transfers
from TANF. States are permitted to transfer up to 30 percent of their
TANF block grant to CCDF. Under CCDF, child care services are available
to eligible families through certificates or contracts with providers,
and parents may select any legally operating child care provider,
including home-based or center-based providers.
Program: EITC;
Description: EITC is a refundable federal tax credit available to
eligible workers earning relatively low incomes. Because the credit is
refundable, a person does not need to owe taxes to receive benefits.
EITC is based on earned income, adjusted gross income, and the presence
of qualifying children, if any. Under current law, there are three
categories of EITC recipients: childless adults, adults with one child,
and adults with two or more children.
Program: Food Stamps;
Description: The Food Stamp Program is the primary source of nutrition
assistance for many low-income households. It enables eligible low-
income households to buy nutritious food with electronic benefit cards
at authorized retail food stores across the country. State and local
welfare offices operate the program, and the federal government
oversees the state operation of the program. Participants must meet
income and resource standards and be U.S. citizens or eligible non-
citizens, and all able-bodied individuals between 16 and 60 without
dependents must register for work, take part in an employment and
training program, or accept or continue suitable employment. Households
with incomes are expected to spend about 30 percent of their income,
after certain deductions, on food.
Program: Head Start;
Description: Head Start provides comprehensive developmental services
for low-income, pre-school children ages 3 to 5, and social services
for their families. Services can be provided through either a half-day
or a full-day program. Head Start provides diverse services in four
components: education, health, parent involvement, and social services.
Grants are awarded to about 1,400 local public or private non-profit
agencies, and the community must contribute about 20 percent of the
total cost of a Head Start program.
Program: Housing Choice Vouchers;
Description: The Housing Choice Voucher program is the federal
government's major program for assisting very low-income families, the
elderly, and the disabled with their housing needs. HUD gives public
housing agencies the funds to administer the program. Participants use
vouchers to find their own housing, including single-family homes,
townhouses and apartments. The voucher recipient pays the difference
between the actual rent charged by the landlord and the amount
subsidized by the program. Generally, the subsidy allows the tenant to
pay no more than 30 percent of adjusted monthly income towards the rent
and utilities.
Program: Medicaid;
Description: Medicaid (title XIX of the Social Security Act) is a
federal/state entitlement program that generally provides health
insurance coverage for low-income families and individuals who are aged
or disabled. Medicaid is the largest source of funding for medical and
health-related services for America's poorest people. Within broad
federal guidelines, each state can (1) establish its own eligibility
standards; (2) determine the type, amount, duration, and scope of
services; (3) set the rate of payment for services; and (4) administer
its own program. Medicaid policies for eligibility, services, and
payment are complex and vary considerably, even among states of similar
size or geographic proximity.
Program: Pell Grant;
Description: The Pell Grant program provides grants (i.e., aid that
does not have to be repaid) to needy undergraduates. It is the largest
source of grant aid for postsecondary education attendance funded by
the federal government and provided an estimated $13.1 billion to
students in fiscal year 2004. Pell Grants are intended to be the
foundation for all federal aid awarded to undergraduates and
constituted an estimated 19 percent of all federally supported aid in
fiscal year 2004 that benefited postsecondary education students. For
fiscal year 2004-2005, grants ranged from $400 to $4,050.
Program: Public Housing;
Description: Public housing was established to provide decent and safe
rental housing for eligible low-income families, the elderly, and
persons with disabilities. Public housing comes in all sizes and types,
from scattered single family houses to high-rise apartments for elderly
families. HUD contributes both capital and operating funds to local
housing agencies that manage the housing for low-income residents at
rents they can afford. HUD also furnishes technical and professional
assistance in planning, developing, and managing these developments.
Program: SCHIP;
Description: As part of the Balanced Budget Act of 1997, Congress
created SCHIP as a federal/state partnership, similar to Medicaid, with
the goal of expanding health insurance to low-income children--i.e.,
those children whose families earn too much money to be eligible for
Medicaid, but not enough money to purchase private insurance. States
can (1) use SCHIP funds to expand Medicaid eligibility to children who
previously did not qualify for the program; (2) design a children's
health insurance program entirely separate from Medicaid; or (3)
combine both the Medicaid and separate program options.
Program: WIC;
Description: WIC provides supplemental foods to low-income women,
infants, & children up to age 5 who are at nutritional risk. The WIC
target population consists of low-income, nutritionally at risk:
pregnant and breastfeeding women; nonbreastfeeding postpartum women;
infants (up to 1st birthday), and children up to their 5th birthday. It
provides supplemental nutritious foods, including infant formula;
nutrition education and counseling at WIC clinics; and screening and
referrals to other health, welfare and social services.
Program: SSI;
Description: The SSI program, title XVI of the Social Security Act, was
enacted in 1972 and implemented in 1974 to ensure a minimum cash income
to all aged, blind, or disabled persons. SSI is provided to eligible
individuals or couples who have limited income and resources (the
countable resource limit is $2,000 for an individual and $3,000 for a
couple). Federal SSI benefits are paid from federal general revenues,
but many states also supplement payments.
Program: TANF;
Description: The Personal Responsibility and Work Opportunity
Reconciliation Act of 1996 (PRWORA) replaced Aid to Families with
Dependent Children (AFDC) with TANF, which marked the end of federal
entitlement to assistance. TANF ended unlimited matching funding for
family cash welfare and created fixed-block grants to states. The block
grant covers benefits, administrative expenses, and services targeted
to needy families and gives states great flexibility to design their
own TANF programs. PRWORA imposed a 5-year limit on TANF cash
assistance paid with federal funds and required states to achieve
minimum participation rates in federally recognized work activities. In
addition, they must spend a specified amount of state funds on eligible
low-income families--at least 75 percent of the state funds they spent
in fiscal year 1994, known as the maintenance-of-effort requirement.
States may use these funds to pay for separate state programs.
Source: Federal agency documents.
[End of table]
Program Administration:
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.
Table 3: Level of Government Responsible for Funding and Design of 12
Low-Income Programs:
Program: EITC;
Funding[A]: Federal;
Design[B]: Federal;
Entitlement: Yes.
Program: Food Stamp Program;
Funding[A]: Federal;
Design[B]: Federal;
Entitlement: Yes.
Program: Medicaid;
Funding[A]: Federal/state;
Design[B]: Federal/state;
Entitlement: Yes.
Program: SSI;
Funding[A]: Federal[C];
Design[B]: Federal;
Entitlement: Yes.
Program: Pell Grants;
Funding[A]: Federal;
Design[B]: Federal;
Entitlement: No.
Program: CCDF;
Funding[A]: Federal/state;
Design[B]: Federal/state;
Entitlement: No.
Program: Head Start;
Funding[A]: Federal;
Design[B]: Federal/local;
Entitlement: No.
Program: Housing Choice Voucher;
Funding[A]: Federal;
Design[B]: Federal;
Entitlement: No.
Program: Public Housing;
Funding[A]: Federal;
Design[B]: Federal;
Entitlement: No.
Program: SCHIP;
Funding[A]: Federal/state;
Design[B]: Federal/state;
Entitlement: No.
Program: TANF cash assistance;
Funding[A]: Federal/state;
Design[B]: Federal/state;
Entitlement: No.
Program: WIC;
Funding[A]: Federal;
Design[B]: Federal;
Entitlement: No.
Source: GAO.
[A] Defined as the level of government that supplies the primary source
of funding for the support. If substantial funding comes from more than
one source, we list both sources. Some additional funding may come from
sources not listed in the table.
[B] Defined as the level of government that is primarily responsible
for availability, eligibility, and benefit amount determination.
[C] Some states contribute to the SSI program, but state funding is not
required and is not provided in all states.
[End of table]
Program Performance Management:
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.[Footnote 4]
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.[Footnote 5] 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.
Use of Federal Low-Income Assistance Varies Greatly by Program and by
Subgroup:
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 Entitlement Programs, the Proportion of Those Eligible Who Were
Enrolled Ranged from about 50 Percent to More Than 70 Percent, but
Participation Rates Are Higher among Some Groups:
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.[Footnote
6] 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.
Table 4: Estimated Participation Rates for Entitlement Programs for the
Most Recent Year Data Were Available:
Program (year)[A]: EITC (1999);
Eligibility unit: Households;
Participation rate estimates (in percent)[B]: 75%[C].
Program (year)[A]: Food Stamp Program (2001): HHS/Urban Institute;
Eligibility unit: Households;
Participation rate estimates (in percent)[B]: 46-48%[E]
Program (year)[A]: (2002): USDA/Mathematica Policy Research, Inc;
Eligibility unit: Households; Individuals;
Participation rate estimates (in percent)[B]: 54%[F].
Program (year)[A]: Medicaid (2000);
Eligibility unit: Individuals[G];
Participation rate estimates (in percent)[B]: 66-70%.
Program (year)[A]: Pell Grants;
Eligibility unit: Not available;
Participation rate estimates (in percent)[B]: Not available[H].
Program (year)[A]: SSI (2001);
Eligibility unit: Individuals and married couples[I];
Participation rate estimates (in percent)[B]: 66-73%.
Sources: GAO's analysis of CPS and IRS survey data and data from the
Urban Institute's TRIM3 model and Mathematica Policy Research, Inc.
[A] All estimates are for the calendar year indicated in the table,
except the food stamp estimates created by Mathematica, which are for
fiscal year 2002.
[B] This range represents a 95 percent confidence interval based on
estimated sampling error in the national survey data. This interval
does not take into account errors introduced by the modeling process or
by administrative data. We assessed but did not quantify these errors.
[C] The EITC participation rate shown has a sampling error that does
not exceed plus or minus 2.7 percentage points. The number of eligible
tax filers used in this estimate was adjusted to exclude those who
received EITC benefits in error. The participation rate is a
conservative estimate based on 32 percent of EITC dollars being claimed
in error; the IRS estimated between 27 and 32 percent of these tax
dollars were paid in error in 1999. Because more recent information
about EITC payment errors is not available, we were unable to provide a
more recent estimate. However, Congress has enacted new tax laws and
the IRS has taken steps to improve compliance. For more details, see
GAO, Earned Income Tax Credit Participation, GAO-02-290R (Washington,
D.C.: Dec. 14, 2001).
[D] While the Urban Institute and Mathematica each generate food stamp
participation rate estimates using data from the CPS, their estimates
differ slightly. The differences arise primarily from differences in
imputation methodology for data missing from the CPS--such as assets,
immigration/refugee status, and information on which household members
buy and prepare food together.
[E,F] Confidence intervals are not available. These estimates are from
Mathematica Policy Research, Inc., Trends in Food Stamp Program
Participation Rates: 1999 to 2002. (Washington, D.C.: Sept. 2004).
[G] Estimates do not include individuals who are institutionalized.
Estimates do account for variation in state eligibility rules and for
people who may be eligible for only part of the year.
[H] We were unable to estimate a participate rate for the Pell Grant
program because we were unable to assess the reliability of data on the
family income of students that did not apply for federal financial
assistance.
[I] No reliable national survey data exist on individuals who meet the
SSI disability criteria. Therefore, researchers made assumptions about
a person's disability based on self-reported information on inability
to work due to illness or other disability, lack of work activity in
the prior year, and receipt of disability income. Some of those assumed
eligible for SSI based on disability may not meet the criteria and vice
versa. As a result, the models may overestimate or underestimate the
number of eligible people. This estimate also does not include
institutionalized individuals and disabled children.
[End of table]
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.[Footnote 7] 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.)
Table 5: Available Subgroup Participation Rate Estimates for
Entitlement Programs for the Most Recent Year Data Were Available:
Program (year)[A]: EITC (1999);
Subgroup: All Households[C];
Participation rate estimates (percent)[B]: 75%[D].
Program (year)[A]: EITC (1999);
Subgroup: Households with No children;
Participation rate estimates (percent)[B]: 45%[E].
Program (year)[A]: EITC (1999);
Subgroup: Households with 1 Child;
Participation rate estimates (percent)[B]: 96%[R].
Program (year)[A]: EITC (1999);
Subgroup: Households with 2 Children;
Participation rate estimates (percent)[B]: 93%[G].
Program (year)[A]: EITC (1999);
Subgroup: Households with 3 or More Children;
Participation rate estimates (percent)[B]: 63%[H].
Program (year)[A]: Food Stamps (2001);
Subgroup: All Households[I];
Participation rate estimates (percent)[B]: 46-48%.
Program (year)[A]: Food Stamps (2001);
Subgroup: Households with Children;
Participation rate estimates (percent)[B]: 55-57%.
Program (year)[A]: Food Stamps (2001);
Subgroup: Households with Elderly Members;
Participation rate estimates (percent)[B]: 27-28%.
Program (year)[A]: Medicaid (2000);
Subgroup: All Individuals[J];
Participation rate estimates (percent)[B]: 66-70%.
Program (year)[A]: Medicaid (2000);
Subgroup: Adults;
Participation rate estimates (percent)[B]: 56-64%.
Program (year)[A]: Medicaid (2000);
Subgroup: Children;
Participation rate estimates (percent)[B]: 74-79%.
Program (year)[A]: Medicaid (2000);
Subgroup: Elderly;
Participation rate estimates (percent)[B]: 40-43%[K].
Program (year)[A]: SSI (2001);
Subgroup: All Individuals and Married Couples[L];
Participation rate estimates (percent)[B]: 66-73%.
Program (year)[A]: SSI (2001);
Subgroup: Elderly;
Participation rate estimates (percent)[B]: 61-68%[M].
Source: GAO's analysis of CPS and IRS survey data and the Urban
Institute's TRIM3.
[A] All estimates are for the calendar year mentioned.
[B] This range represents a 95 percent confidence interval based on
estimated sampling error in the national survey data. This interval
does not take into account errors introduced by the modeling process or
by administrative data. We assessed but did not quantify these errors.
[C] The number of eligible tax filers used in these estimates were
adjusted to exclude those who received EITC benefits in error. The
participation rate is a conservative estimate based on 32 percent of
EITC dollars being claimed in error; the IRS estimated between 27 and
32 percent of EITC dollars claimed in 1999 were paid in error. Because
more recent information about EITC payment errors is not available, we
were unable to provide a more recent estimate. However, since 1999,
Congress has enacted new tax laws and the IRS has taken steps to
improve compliance. For more details, see GAO, Earned Income Tax Credit
Participation, GAO-02-290R (Washington, D.C.: Dec. 14, 2001).
[D] The EITC participation rate for all households has a sampling error
that does not exceed plus or minus 2.7 percentage points.
[E] The EITC participation rate for households with no children has a
sampling error that does not exceed plus or minus 3.9 percentage
points.
[F] The EITC participation rate for households with one child has a
sampling error that does not exceed plus or minus 7.7 percentage
points. The actual participation rate cannot exceed 100 percent.
[G] The EITC participation rate for households with 2 children has a
sampling error that does not exceed plus or minus 8.3 percentage
points. The actual participation rate cannot exceed 100 percent.
[H] The EITC participation rate for households with 3 or more children
has a sampling error that does not exceed plus or minus 8.3 percentage
points.
[I] Estimates in the table are from the Urban Institute. Mathematica
has also estimated participation rates for these subgroups and found
that about 66 percent of eligible households with children and 28
percent of those with elderly members participated in fiscal year 2002.
While the Urban Institute and Mathematica each generate food stamp
participation rate estimates using data from the CPS, their estimates
differ slightly. The differences arise primarily from differences in
imputation methodology for data missing from the CPS--such as assets,
immigration/refugee status, and information on which household members
buy and prepare food together.
[J] Estimates do not include individuals who are institutionalized.
Estimates do account for variation in state eligibility rules and for
people who may be eligible for only part of the year.
[K] Estimates include those who are dually enrolled in Medicare and
Medicaid who thus qualify for the full Medicaid benefit and those who
only receive Medicaid assistance for their Medicare cost sharing.
Estimates do not include eligible elderly people who are
institutionalized. The participation rate may be lower for this group
in part because those over the age of 65 may have Medicare coverage.
[L] No reliable national survey data exist on individuals who meet the
SSI disability criteria. Therefore, researchers made assumptions about
a person's disability based on self-reported information on inability
to work due to illness or other disability, lack of work activity in
the prior year, and receipt of disability income. Some of those assumed
eligible for SSI based on disability may not meet the criteria and vice
versa. As a result, the models may overestimate or underestimate the
number of eligible people. This estimate also does not include
institutionalized individuals or disabled children.
[M] Estimates do not include eligible elderly people who are
institutionalized.
[End of table]
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.[Footnote 8] 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.
Figure 1: Food Stamp Participation Rate Estimates for Fiscal Years 1999
to 2002:
[See PDF for image]
[End of figure]
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.
For Non-Entitlement Programs, the Proportion of Those Eligible Who Were
Enrolled Ranged from Less Than 10 Percent to about 50 Percent:
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.[Footnote 9]
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.
Table 6: Estimated Coverage Rates for Non-Entitlement Programs for the
Most Recent Year Data Were Available:
Program (year): CCDF (2001);
Eligibility unit: Children[B];
Coverage rate estimates (percent)[A]: 18--19%[C].
Program (year): Head Start (2003);
Eligibility unit: Children[D];
Coverage rate estimates (percent)[A]: 44--54%[E].
Program (year): Housing Choice Vouchers (1999);
Eligibility unit: Households[F];
Coverage rate estimates (percent)[A]: 13--15%.
Program (year): Public Housing (1999);
Eligibility unit: Households[G];
Coverage rate estimates (percent)[A]: 7--9%.
Program (year): SCHIP (2000)[H];
Eligibility unit: Children[I];
Coverage rate estimates (percent)[A]: 44--51%.
Program (year): TANF-cash assistance (2001);
Eligibility unit: Families[J];
Coverage rate estimates (percent)[A]: 46--50%.
Program (year): WIC (1998): National Research Council;
Eligibility unit: Infants and Children[K];
Coverage rate estimates (percent)[A]: 51%[L].
Program (year): (2001): Urban Institute;
Eligibility unit: Individuals;
Coverage rate estimates (percent)[A]: 51--55%[M].
Source: The Urban Institute's TRIM3 and GAO's analysis of data from the
CPS and HUD.
[A] This range represents a 95 percent confidence interval based on
estimated sampling error in the national survey data. This interval
does not take into account errors introduced by the modeling process or
by administrative data. We assessed but did not quantify these errors.
[B] The estimates account for variations in state eligibility criteria
and are based on criteria as of October 2001. Estimates do not account
for participation in other programs that provide similar services.
[C] To increase the precision of these estimates, 3 years of CPS data
were used to estimate the eligible population; other coverage rates and
participation rates estimated using TRIM3 only use 1 year of data. As a
result, the confidence interval based on the sampling error is smaller
than for the other estimates.
[D] Head Start participation is measured by the number of funded slots,
not the number of children in the program. Therefore, this estimate may
overstate or understate the actual coverage rate because more than one
child may fill a slot in a year and some slots may go unfilled.
Estimates do not account for participation in other programs that
provide similar services.
[E] The coverage rate does not include enrolled children living above
the poverty threshold. Nonpoor children can comprise up to 10 percent
of Head Start enrollment slots.
[F] HUD's data on the number of eligible households was based on the
American Housing Survey. This survey may overestimate household income
and underestimate the number of households in poverty. These estimates
also may include households who do not qualify for the voucher despite
their low-income status. Coverage rates are based on the number of
households who successfully leased units in 1999. A total of 1,649,645
vouchers were authorized, but some of these were not used partially due
to voucher-holders' inability to find housing. Rates reflect only those
participating in the Housing Choice Voucher program; however, those
eligible may also be served by a number of other federal, state, and
local housing assistance programs.
[G] HUD's data on the number of eligible households was based on the
American Housing Survey. This survey may overestimate household income
and underestimate the number of households in poverty. Income-eligible
households may not be eligible for other reasons--for example, local
public housing authorities may deny assistance to people with habits
and practices that may be detrimental to other public housing tenants-
-and the estimate does not account for this. Coverage rates are based
on the number of public housing units that were leased; a total of
1,235,229 units were available but some were unleased for a variety of
reasons, such as resident turnover. Rates reflect only those
participating in the public housing program; however, those eligible
may also be served by a number of other federal, state, and local
housing assistance programs. GAO used an eligible population of those
who earn less than 80 percent area median income as per the eligibility
criteria; however, nationally the vast majority of those served by
public housing make less than 50 percent of the area median income.
[H] A new program established in 1997, SCHIP saw its enrollment
increase 75 percent between fiscal years 2000 and 2003; a more recent
estimate of the SCHIP coverage rate would likely be higher than the
range shown. In addition, because states' implementation of their
programs varied, awareness of SCHIP may lag in states that created
their programs more recently.
[I] Estimates account for variation in state eligibility rules, and the
estimates are based on state eligibility rules in place in 2000.
Children who are eligible for Medicaid expansion SCHIP programs and
separate state SCHIP programs are included in the estimate. Children
covered by private and other public health insurance such as Medicaid
are generally not eligible for SCHIP and are, therefore, not included
in the denominator for the calculation; to the extent that some are
included in the actual caseload under "employer buy in" programs, the
coverage rate will be slightly overestimated.
[J] Estimates account for variation in state eligibility rules. All
units receiving TANF cash assistance are included, even though a
separate state program might fund their benefits. Families receiving
non-cash benefits funded by TANF are not included, although an
increasing proportion of TANF funds are being used to provide non-cash
assistance to families. Some families or individuals that may appear
eligible according to model may not be participating because they have
not complied with program requirements, such as being involved in work
activities. However, those who have reached their state or federal TANF
time limit are appropriately excluded from eligibility in estimating
the coverage rate.
[K] Estimates only include eligible infants and children, even though
pregnant, postpartum, and breastfeeding women are eligible for this
program, because the CPS does not have data to determine a woman's
pregnancy status or whether she is breastfeeding. According to the FNS,
women account for a quarter of WIC participants.
[L] A confidence interval is not available. This estimate is based on
data from National Research Council of the National Academies,
Estimating Eligibility and Participation for the WIC Program
(Washington, D.C.: Sept. 2003). Estimates include pregnant women,
infants, and children. It does not include postpartum and breastfeeding
women.
[M] Estimates are preliminary because they are partially based on the
numbers used to create Medicaid participation rates and SCHIP coverage
rates. The Medicaid participation rate and SCHIP coverage rate for 2001
had not been completed in time to include in this report.
[End of table]
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.[Footnote 10]
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.[Footnote 11]
* 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.[Footnote 12]
* 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.[Footnote
13]
* 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.
Table 7: Coverage Rate Estimates for TANF Cash Assistance and WIC
Subgroups for the Most Recent Year Data Were Available:
Program (year): TANF-cash assistance (2001)[A];
Eligibility units: All Families;
Coverage rate estimates (percent): 46--50%.
Program (year): TANF-cash assistance (2001)[A];
Eligibility units: Families with Earners[B];
Coverage rate estimates (percent): 37--44%.
Program (year): TANF-cash assistance (2001)[A];
Eligibility units: Families with No Earners[C];
Coverage rate estimates (percent): 51--56%.
Program (year): TANF-cash assistance (2001)[A];
Eligibility units: Two-Parent Families;
Coverage rate estimates (percent): 31--36%.
Program (year): TANF-cash assistance (2001)[A];
Eligibility units: Families with Immigrants;
Coverage rate estimates (percent): 34--43%.
Program (year): WIC (2001)[D];
Eligibility units: All Individuals[E];
Coverage rate estimates (percent): 51--55%.
Program (year): WIC (2001)[D];
Eligibility units: Infants;
Coverage rate estimates (percent): 79--93%.
Program (year): WIC (2001)[D];
Eligibility units: Children Ages 1-4;
Coverage rate estimates (percent): 41--45%.
Source: GAO analysis of estimates from the Urban Institute's TRIM3.
[A] Estimates account for variation in state eligibility rules. All
units receiving TANF cash assistance are included, even though a
separate state program might fund their benefits. 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 in involved in work activities. However, those who have
reached their state or federal TANF time limit are ineligible and are
not included, unless receiving assistance through a separate state
program.
[B,C] Estimates only include families with one parent or no parents
present.
[D] Estimates are preliminary because they are partially based on the
numbers used to create Medicaid participation rates and SCHIP coverage
rates. The Medicaid participation rate and SCHIP coverage rate for 2001
had not been finalized during the time frames of this report.
[E] Estimates only include eligible infants and children, even though
pregnant, postpartum, and breastfeeding women are eligible for this
program, because the CPS does not have data to determine a woman's
pregnancy status or whether she is breastfeeding. According to the FNS,
women account for a quarter of WIC participants.
[End of table]
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.
Figure 2: Head Start Coverage Rate Estimates for 1997 to 2003:
[See PDF for image]
[End of figure]
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.[Footnote 14] 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.[Footnote 15] 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.
The Estimated Costs of Serving Eligible Non-participants Show That in
Some Programs, Those Eligible for the Largest Benefits Are More Likely
to be Enrolled:
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.
Table 8: Potential Cost of Providing Benefits to Eligible Non-
participants for the Most Recent Year Data Were Available:
Program (year): EITC (1999);
Potential annual cost of serving eligible non-participants[A,B]: $2-
3.4[C].
Program (year): Food Stamp Program (2001);
Potential annual cost of serving eligible non-participants[A,B]: 8.8-
11.5.
Program (year): Head Start (2003);
Potential annual cost of serving eligible non-participants[A,B]: 3.8-
5.6[D].
Program (year): SSI (2001);
Potential annual cost of serving eligible non-participants[A,B]: 8-9.8.
Program (year): TANF-cash assistance (2001)[E];
Potential annual cost of serving eligible non-participants[A,B]: 8-9.
Program (year): WIC (2001)[F];
Potential annual cost of serving eligible non-participants[A,B]: 1.9-
2.1.
Source: The Urban Institute's TRIM3 and GAO's analysis of data from
CPS, HHS, and IRS.
Note: Cost estimates do not include increases in administrative costs
associated with greater program participation.
[A] This range represents a 95 percent confidence interval based on
estimated sampling error in the national survey data. This interval
does not take into account errors introduced by the modeling process or
by administrative data. We assessed but did not quantify these errors.
Estimates are based on most of the same data used to estimate
participation and coverage rate estimates for the related programs and,
therefore, many of the same data and model limitations apply.
[B] Estimates do not account for policy or economic changes that would
occur if participation in these programs increased. All estimates are
based on the assumption that participation in other programs remains
constant.
[C] Estimates are from GAO, Earned Income Tax Credit Participation, GAO-
02-290R (Washington, D.C.: Dec. 14, 2001).
[D] Estimate is based on an average cost per slot multiplied by the
number of non-participating eligible children. This estimate does not
account for local variation in the cost of services, and does not
account for the possibility of more than one child filling a slot.
[E] Estimates are only for the additional cost of providing TANF cash
assistance. The program provides other supports, such as child care and
transportation, to needy families, and the cost of these services would
increase the estimate if they were included.
[F] Estimates are only for the additional cost of providing food
benefits to infants and children who are not enrolled.
[End of table]
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 Participation but Their Impact on Entitlement
and Non-Entitlement Programs Differs:
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 Benefits Can Affect Participation:
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.[Footnote 16] 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.[Footnote 17]
* 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.
Ease of Access to Program Benefits and Services Can Influence
Participation:
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.[Footnote 18] 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.[Footnote 19] 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.
Misperceptions about Program Requirements Discourage Some Individuals
from Participating:
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.
Application Process and Eligibility Verification Requirements to Ensure
Program Integrity Can Have an Effect 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.[Footnote 20] 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.[Footnote 21] 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 Rates Can also Impact Other
Aspects of Program Access Such As Targeting and Program Interactions:
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 Strategies That Improve Both Access and
Integrity, but Federal Agencies Have Generally Focused More on
Measuring Program Integrity Outcomes:
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.
Programs Have Found Ways to Improve Access by Reducing the Burden on
Applicants While at the Same Time Improving Program Integrity:
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.
Information Systems, Data Sharing, and Technological Innovation:
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.[Footnote 22]
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.
Application and Eligibility Verification Process Changes:
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.[Footnote 23] 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.
Outreach and Coordination with Other Programs:
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.
Federal Agencies Have Taken Steps to Track Improper Payments, but Few
Estimate Program Participation or Coverage Rates to Monitor Program
Access:
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:[Footnote 24]
* 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.[Footnote 25] 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.[Footnote 26]
Table 9: Status of Agencies Identification of and Reporting on the
Amounts of Improper Payments by Program:
Agency: USDA;
Program: Food Stamps;
Subject to the IPIA? Yes;
Agency included improper payment information in fiscal year 2004 annual
performance and accountability report: Yes.
Agency: USDA;
Program: WIC;
Subject to the IPIA? Yes;
Agency included improper payment information in fiscal year 2004 annual
performance and accountability report: No;
If not, has the agency reported taking some steps to identify and
monitor the amount of improper payments? Yes.
Agency: HHS/ACF;
Program: TANF;
Subject to the IPIA? Yes;
Agency included improper payment information in fiscal year 2004 annual
performance and accountability report: No;
If not, has the agency reported taking some steps to identify and
monitor the amount of improper payments? Yes.
Agency: HHS/ACF;
Program: CCDF;
Subject to the IPIA? Yes;
Agency included improper payment information in fiscal year 2004 annual
performance and accountability report: No;
If not, has the agency reported taking some steps to identify and
monitor the amount of improper payments? Yes.
Agency: HHS/ACF;
Program: Head Start;
Subject to the IPIA? Yes;
Agency included improper payment information in fiscal year 2004 annual
performance and accountability report: No[A];
If not, has the agency reported taking some steps to identify and
monitor the amount of improper payments? Yes.
Agency: IRS;
Program: EITC;
Subject to the IPIA? Yes;
Agency included improper payment information in fiscal year 2004 annual
performance and accountability report: Yes.
Agency: HHS/CMS[B];
Program: Medicaid;
Subject to the IPIA? Yes;
Agency included improper payment information in fiscal year 2004 annual
performance and accountability report: No;
If not, has the agency reported taking some steps to identify and
monitor the amount of improper payments? Yes.
Program: SCHIP;
Subject to the IPIA? Yes;
Agency included improper payment information in fiscal year 2004 annual
performance and accountability report: No;
If not, has the agency reported taking some steps to identify and
monitor the amount of improper payments? Yes.
Agency: SSA;
Program: SSI;
Subject to the IPIA? Yes;
Agency included improper payment information in fiscal year 2004 annual
performance and accountability report: Yes.
Agency: ED;
Program: Pell Grant;
Subject to the IPIA? Yes;
Agency included improper payment information in fiscal year 2004 annual
performance and accountability report: Yes.
Agency: HUD;
Program: Public Housing;
Subject to the IPIA? Yes;
Agency included improper payment information in fiscal year 2004 annual
performance and accountability report: Yes.
Agency: HHS/CMS[B];
Program: Housing Choice Voucher;
Subject to the IPIA? Yes;
Agency included improper payment information in fiscal year 2004 annual
performance and accountability report: Yes.
Source: GAO survey of federal agencies and interviews with agency
officials and agency performance and accountability reports.
[A] ACF has estimated the percentage of "over-income" families served
by Head Start in excess of the 10 percent allowed by regulation.
[B] CMS has a performance goal in its annual performance plan related
to a pilot project to develop payment error rates for both SCHIP and
Medicaid.
[End of table]
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.[Footnote 27]
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.[Footnote 28] In these ways, the agency
uses this information for program management purposes.
Table 10: Status of Agencies Efforts to Use Information on
Participation or Coverage Rates in Managing Their Programs:
Agency: USDA;
Program: Food Stamps;
Does the agency estimate a participation or coverage rate? Yes;
If so, does the agency use this rate information as a performance
measure? Yes;
If the agency estimates a participation or coverage rate, does it
include rate information in their performance report or other key
program report[A]? Yes.
Agency: USDA;
Program: WIC;
Does the agency estimate a participation or coverage rate? Yes;
If so, does the agency use this rate information as a performance
measure? No;
If the agency estimates a participation or coverage rate, does it
include rate information in their performance report or other key
program report[A]? Yes[B].
Agency: HHS/ACF;
Program: TANF;
Does the agency estimate a participation or coverage rate? Yes;
If so, does the agency use this rate information as a performance
measure? No;
If the agency estimates a participation or coverage rate, does it
include rate information in their performance report or other key
program report[A]? No[C].
Agency: HHS/ACF;
Program: CCDF;
Does the agency estimate a participation or coverage rate? Yes;
If so, does the agency use this rate information as a performance
measure? No;
If the agency estimates a participation or coverage rate, does it
include rate information in their performance report or other key
program report[A]? Yes[D].
Agency: HHS/ACF;
Program: Head Start;
Does the agency estimate a participation or coverage rate? Yes;
If so, does the agency use this rate information as a performance
measure? No;
If the agency estimates a participation or coverage rate, does it
include rate information in their performance report or other key
program report[A]? No.
Agency: IRS;
Program: EITC;
Does the agency estimate a participation or coverage rate? Yes[E];
If so, does the agency use this rate information as a performance
measure? No;
If the agency estimates a participation or coverage rate, does it
include rate information in their performance report or other key
program report[A]? No[F].
Agency: HHS/CMS;
Program: Medicaid;
Does the agency estimate a participation or coverage rate? No.
Agency: HHS/CMS;
Program: S-CHIP;
Does the agency estimate a participation or coverage rate? No.
Agency: SSA;
Program: SSI;
Does the agency estimate a participation or coverage rate? No[G].
Agency: ED;
Program: Pell Grant;
Does the agency estimate a participation or coverage rate? No[H].
Agency: HUD;
Program: Public Housing;
Does the agency estimate a participation or coverage rate? No[I].
Agency: HUD;
Program: Housing Choice Voucher;
Does the agency estimate a participation or coverage rate? No.
Source: GAO survey of federal agencies, agency annual performance
plans.
[A] Key program reports include routine reports that agencies must
prepare for Congress for the purpose of providing updated information
on the status of the programs they administer.
[B] USDA's methodology for calculating the WIC coverage rate is being
revised. The agency has not yet started reporting in its annual program
reports but it has plans to do so.
[C] HHS includes a TANF coverage rate as part of their Indicators of
Welfare Dependence report.
[D] CCDF has published a coverage rate for child care in their Biennial
Report to the Congress, which includes SSBG and TANF funds.
[E] IRS has calculated a participation rate for the EITC, but only for
selected years.
[F] IRS has plans to use a participation rate as part of their
Strategic Plan.
[G] SSA has calculated a participation rate for the years 1991-1996,
but only for a subpopulation of those participating in SSI.
[H] ED has calculated a take-up rate, which is the share of those who
applied and were found eligible for a Pell Grant who actually received
a grant.
[I] HUD has calculated a voucher utilization rate for the housing
choice voucher program, and tracks the occupancy rates of public
housing authorities.
[End of table]
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,[Footnote 29] 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[Footnote 30] 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.[Footnote 31]
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.
Conclusion:
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.
Recommendations to Executive Agencies:
Recommendations to the Secretary of the Department of Agriculture:
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.
Recommendation to the Secretaries of the Department of Education and
the Department of Housing and Urban Development:
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.
Recommendations to the Secretary of the Department of Health and Human
Services:
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:
3. quantifying errors that result from calculating these estimates to
help users better understand the accuracy of the data; and:
4. 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.
Recommendation to the Commissioner of the Internal Revenue Service:
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.
Recommendation to the Commissioner of the Social Security
Administration:
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.
Agency Comments:
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.
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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.
Sincerely,
Signed by:
David Bellis, Director:
Education, Workforce, and Income Security:
[End of section]
Appendix I: Objectives, Scope, and Methodology:
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.
Participation and Coverage Rates:
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.
Table 11: Summary of Participation and Coverage Rate Methodologies:
Program: SSI, Medicaid, CCDF, TANF, SCHIP, WIC;
Participation or coverage rate methodology: Estimate of recipients as a
percentage of potentially eligible;
Data source: The Urban Institute Transfer Income Microsimulation model,
version 3 (TRIM3), developed under contract with HHS.
Program: Food Stamp Program;
Participation or coverage rate methodology: Estimate of recipients as a
percentage of potentially eligible;
Data source: TRIM3;
Mathematica Policy Research, Inc., microsimulation model developed
under contract with USDA.
Program: EITC;
Participation or coverage rate methodology: Estimate of eligible
recipients as percentage of potentially eligible;
Data source: GAO estimate based on administrative and CPS data and
compliance information provided by IRS, see GAO, Earned Income Tax
Credit Participation, GAO-02-290R (Washington, D.C.: Dec. 14, 2001).
Program: Housing Choice Voucher, public housing;
Participation or coverage rate methodology: Estimate of eligible
recipients as percent of potentially eligible;
Data source: GAO estimate based on administrative data and data from
the HUD 1999 worst case needs report.
Program: Head Start;
Participation or coverage rate methodology: Estimate of number of
funded slots as a percentage of 3-and 4-year-old children in families
below poverty;
Data source: GAO estimate based on administrative and national survey
data from the U.S. Census Bureau's Annual Social and Economic
Supplement to the Current Population Survey (CPS).
Source: GAO.
Note: Some participation and coverage rate estimates are based on the
average monthly number of recipients and people who are eligible for a
program while others are based on the total number of recipients and
people who are eligible at any point in the year. The participation and
coverage rate for any program will differ by whether average monthly or
total numbers are used.
[End of table]
Participation and Coverage Rates Estimated by The Urban Institute:
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.
Participation and Coverage Rates We Estimated:
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.[Footnote
32] 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.[Footnote 33] 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.
Reliability of Administrative Data:
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.
Cost Estimates:
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,[Footnote 34] 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.
Factors That Affect Participation and Strategies to Improve Access and
Integrity:
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.
[End of section]
Appendix II: Limitations Affecting Use of Participation and Coverage
Rates:
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.
Limitations of National Survey Data:
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.[Footnote 35] 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.
Errors from Research Methodology:
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.
Years for Which Estimates Are Available:
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.
Availability of Alternative Programs:
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.[Footnote 36]
Cost Considerations:
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.
[End of section]
Appendix III: Agency Estimates of Improper Payments for Programs
Reviewed:
Table 12: Improper Payment Estimates Reported in Agency Fiscal Year
2003 Performance and Accountability Reports:
Agency: USDA;
Program: Food Stamp Program;
Reported amount of improper payments: $1,507,000,000.
Agency: USDA;
Program: WIC;
Reported amount of improper payments: NA.
Agency: HHS/ACF;
Program: TANF;
Reported amount of improper payments: NA.
Agency: HHS/ACF;
Program: CCDF;
Reported amount of improper payments: NA.
Agency: HHS/ACF;
Program: Head Start;
Reported amount of improper payments: NA.
Agency: IRS;
Program: EITC;
Reported amount of improper payments: $10,500,000,000.
Agency: HHS/CMS;
Program: Medicaid;
Reported amount of improper payments: NA.
Program: SCHIP;
Reported amount of improper payments: NA.
Agency: SSA;
Program: SSI;
Reported amount of improper payments: $2,740,000,000.
Agency: Education;
Program: Pell Grant;
Reported amount of improper payments: $377,500,000.
Agency: HUD;
Program: Public Housing;
Reported amount of improper payments: $650,000,000.
Program: Housing Choice Voucher (Tenant-and Project-Based);
Reported amount of improper payments: $1,877,000,000.
Source: GAO, Financial Management: Fiscal Year 2003 Performance
Accountability Reports Provide Limited Information on Governmentwide
Improper Payments, GAO-04-631T (Washington, D.C.: Apr. 15, 2004). Data
from this report were based on agency fiscal year 2003 Performance and
Accountability Reports.
[End of table]
[End of section]
Appendix IV: Comments from the Department of Education:
DEPARTMENT OF THE TREASURY:
INTERNAL REVENUE SERVICE:
WASHINGTON, D.C. 20224:
COMMISSIONER:
February 8, 2005:
Mr. David Bellis:
Director, Education, Workforce, and Income Security:
United States Government Accountability Office:
Washington, DC 20548:
Dear Mr. Bellis:
I am responding to your draft report entitled "Means-Tested Programs:
Information on Program Access Can Be an Important Management Tool" (GAO-
05-221). This report is both timely and relevant. It underscores our
recent decision to establish the Earned Income Tax Credit (EITC)
participation rate as an Agency measure under the Government
Performance and Results Act of 1993, and thereby publicly underscores
our commitment to ensuring every eligible taxpayer claims the credit.
The report comprehensively addresses the numerous factors that
influence participation in means-tested programs such as the EITC. In
addition, it also acknowledges that actions taken to improve program
access often have an effect on program integrity, necessitating a
balanced approach to program delivery that places equal emphasis on
both access and integrity.
We agree that estimating participation rates can and should be a key
component of each program, as this will further emphasize the
importance of access, in conjunction with integrity, in assessing
program results. The EITC program is structured to achieve an
appropriate balance between the two, and we have developed targets for
both and implemented program strategies that support their achievement.
Relating to improving program access and increasing participation by
eligible individuals, our efforts include a coordinated outreach
strategy that leverages community-based and national partners to
deliver key messages to target populations, as well as the development
of useful and relevant materials aimed at assisting individuals in
determining their EITC eligibility. Education about eligibility
requirements is likewise an essential component of our strategy to
maintain and improve program integrity.
We believe our plans to measure participation rates and our progress in
meeting participation rate targets are quite strong. Nonetheless, we
appreciate the report's valuable insights into, and recommendations
regarding, this aspect of program delivery and performance assessment.
The report specifically recommends that, "As the IRS moves forward on
developing participation rate estimates to use as a program performance
measure for the Earned Income Tax Credit.... 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."
We agree with your recommendation. During 2005, the IRS will perform a
participation rate study based on a match to data provided by the
Bureau of the Census, the results of which will help us update our
participation rate estimates. In reporting the results of this study,
we will include these estimates, as well as note the limitations in our
methodology and data. Moreover, as we update these estimates we will
highlight any methodological changes and their corresponding effects on
these estimates.
If you have any questions, please contact Floyd Williams, Director,
Legislative Affairs, at (202) 622-3720.
Sincerely,
Signed by:
Mark W. Everson:
[End of section]
Appendix V: Comments from the Department of Health and Human Services:
DEPARTMENT OF HEALTH & HUMAN SERVICES:
Office of Inspector General:
Washington, D.C. 20201:
MAR 1 2005:
Mr. David D. Bellis:
Director:
Education, Workforce, and Income Security Issues:
U.S. Government Accountability Office:
Washington, DC 20548:
Dear Mr. Bellis:
Enclosed are the Department's comments on the U.S. Government
Accountability Office's (GAO's) draft report entitled, "Means-Tested
Programs: Information on Program Access Can Be an Important Management
Tool" (GAO-05-221). The comments represent the tentative position of
the Department and are subject to reevaluation when the final version
of this report is received.
The Department provided several technical comments directly to your
staff.
The Department appreciates the opportunity to comment on this draft
report before its publication.
Sincerely,
Signed by:
Daniel R. Levinson:
Acting Inspector General:
Enclosure:
The Office of Inspector General (OIG) is transmitting the Department's
response to this draft report in our capacity as the Department's
designated focal point and coordinator for U.S. Government
Accountability Office reports. OIG has not conducted an independent
assessment of these comments and therefore expresses no opinion on
them.
COMMENTS OF THE DEPARTMENT OF HEALTH AND HUMAN SERVICES ON THE
GOVERMENT ACCOUNTABILITY OFFICE'S DRAFT REPORT "MEANS-TESTED PROGRAMS:
INFORMATION ON PROGRAM ACCESS CAN BE AN IMPORTANT MANAGEMENT TOOL" (GAO-
05-221):
The Department of Health and Human Services (HHS) appreciates the
opportunity to comment on the Government Accountability Office's
(GAO's) draft report.
GAO Recommendation:
We recommend that the Secretary of Health and Human Services (HHS)
consider making some improvements to the participation and coverage
rate information produced for the Child Care and Development Fund
(CCDF), Medicaid, State Children's Health Insurance Program (SCHIP),
and the Temporary Assistance for Needy Families (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 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.
HHS Comments:
CCDF Program:
Participation/Coverage Rate:
The Child Care Bureau (CCB) is pleased that GAO makes a distinction in
its report between the terms "participation rate" and "coverage rate."
However, while this distinction differentiates between entitlement and
non-entitlement programs and acknowledges State flexibility in defining
eligibility in CCDF, it does not recognize the difference between
"eligibility" and "need." Like families in the larger population,
research indicates that many low-income working families find unpaid
care by family, friends and neighbors more convenient and consistent
with what they want for their children. In addition, the child care
needs of many families are met in part or in whole through schools and
programs such as Head Start, pre-kindergarten programs and 21st Century
Community Learning Centers.
As GAO points out on page 19 in footnote 10, "HHS does not collect
information on the number of children who receive child care subsidies
through the Social Services Block Grant (SSBG), TANF and TANF
Maintenance-of-Effort Funding." However, these funds accounted for
almost $3 billion of available child care subsidy dollars in FY 2003 or
approximately one-third of the total child care subsidy funds. In many
States, these funds are used together with CCDF funds and programs are
administered to provide a seamless system of child care assistance,
regardless of funding streams. Hence, ACF believes a coverage rate that
accounts for all of these Federal and State funds is more appropriate
than just the CCDF coverage rate for demonstrating program
effectiveness. ACF has developed such a coverage rate, as noted in the
first bullet on page 19, finding a 26 percent participation rate in FY
2001. This is reported in the biennial Child Care and Development Fund
Report to Congress, submitted January 2003.
GAO notes that since non-entitlement programs are constrained by
available funding, promoting access involves the targeting of scarce
resources to specific high-priority groups of people and strategic
planning to ensure that programs are coordinated (page 4). As part of
its coverage rate analysis, ACF looks at specific CCDF priority
subpopulations including low-income families receiving or at risk of
receiving TANF funds. For FY 2001, ACF estimated a coverage rate of 42
percent for families below poverty, 53 percent for children under age
six below poverty and, 61 percent for those age three to five below
poverty.
Factors that Influence Participation Rates and Program Access:
On page 31, GAO states that CCDF is one of four non-entitlement
programs with funding limitations that could restrict the number of
those potentially eligible for participation. Because States have broad
flexibility in setting eligibility for CCDF, and have the ability to
use TANF dollars for child care services, States have significant
influence over the number of potential program participants. Similar to
TANF, CCDF provides grants directly to States and allows States
substantial flexibility in determining program eligibility and
implementation. States have four major areas of program flexibility:
eligibility limits; amount of parent payments (co-payments); amount of
reimbursement to child care providers; and determinations about which
families will receive priority for services. This flexibility has
myriad implications for program participation. Therefore, ACF thinks
the report overstates the distinction between TANF and CCDF with regard
to the impact State flexibility has on coverage rates.
Strategies to Address Access and Integrity:
Government Performance and Results Act (GPRA):
Since data collection for the GAO report began, the CCB has developed
performance measures dealing with program coverage and program
efficiency. These measures were first included in CCB's Program
Assessment Rating Tool (PART) submission in 2004 and will be included
in ACF's FY 2006 Annual Performance Plan.
CCB developed a new GPRA measure during the 2004 PART evaluation to
measure the extent to which low-income children receive child care
subsidies: the number of children below 150 percent of the Federal
poverty level receiving child care subsidies through CCDF, TANF, and
SSBG, compared to those who are eligible under State CCDF eligibility
rules. This measure will help us track program coverage over time and
support our work with States to ensure that they are using the policy
levers available through CCDF to improve access for those most in need
of services.
* Improper Payments Project:
In response to the Improper Payments Information Act of 2002, CCB is
implementing the Improper Payments Project, a partnership with 11
States (three of the five States included in this GAO study are our
partners in this project). As we learned during the first phase of the
project, State efforts to control improper payments need to be coupled
with efforts to provide effective service delivery and, therefore,
access for clients. CCB agrees with GAO's findings that if strategies
to limit improper payments (e.g., increased paperwork, verification
requirements) discourage significant numbers of parents or providers
from participating in the subsidy program, the effectiveness of the
program may be undermined. In fact, one of the States involved in the
project made changes to policies and procedures that the State
concluded were adversely affecting both access and accuracy.
Furthermore, we found that State flexibility in the administration of
CCDF results in a wide variety of approaches to service delivery, data
collection, and the sharing of data. The next phase of the project--
intensive site visits and a study of four States (two State-
administered and two locally administered)--are planned so that ACF and
the States can learn more about State data management efforts and
explore the impact of improper payments and client eligibility on
program integrity and access. These activities will provide the
foundation for technical assistance to States to support sound program
administration.
Temporary Assistance for Needy Families:
HHS has demonstrated commitment to analyzing TANF, Medicaid, CCDF, and
other program coverage rates through providing core funding for the
Transfer Income Maintenance Model (TRIM3), the source of many of the
coverage rates provided in the GAO report. Nonetheless, we do not think
it is advisable to further highlight TANF coverage or participation
rates as a measure of program performance in key program reports as
recommended by GAO. We would note that one of the four purposes of the
TANF program is to end the dependence of needy parents on Government
benefits by promoting job preparation, work, and marriage. It would
seem more consistent with the multiple goals of TANF to focus
performance measures on issues related to employment and healthy
marriage. An over-emphasis on the coverage rate as a performance
indicator could undermine other program goals, including the goal of
ending dependence through work.
GAO should be aware that ACF reports a form of the TANF coverage rates
in at least two Congressionally mandated reports. The Annual TANF
Report to Congress presents the participation rate of the U.S.
population (e.g., 6th Annual Report, Chart 1:2, page A-205). In
addition, the Indicators of Welfare Dependence, an annual report to
Congress, presents the participation rate of the eligible population,
similar to the rate calculated by GAO (e.g., 2004 report IND 4 page II-
8).
Factors to consider in estimating the costs of serving eligible non-
participants:
While GAO alludes in table notes to some of the problems involved in
estimating the costs of serving eligible non-participants, the inherent
uncertainties with this type of estimate should be made more explicit
for the reader. For example, footnote "c" on page 24 that says the
"estimates do not account for policy or economic changes that would
occur if participation in these programs increased" could be expanded
to indicate that the estimates do not account for behavioral changes,
such as reduced work effort. Nor does GAO appear to take into account
such factors as program interactions (e.g., between TANF and Food
Stamps) and the fact that expanded coverage in the TANF program in the
short-term would lead more participants to exhaust their time-limited
benefits, and the possibility that covering certain groups of non-
participants may result in higher error rates.
Participation and coverage rates tend to understate the extent to which
"needs" are met:
The report notes 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" (page 23). This finding would be true for
most, if not all, of the programs and suggests that targeting may be
better than indicated by the participation and coverage rate. And,
since the report estimates the cost of serving un-served eligible
families, this calculation should be possible (subject to the caveats
described in the report and above) for all of the calculated estimated
costs for providing benefits to eligible non-participants.
Raising, participation and coverage rates may conflict with other TANF
program goals:
The report notes that the goals of ensuring program access (as
indicated by participation and coverage rates) and program integrity
may conflict. There are conflicts with other goals as well that should
be discussed. One of the main goals of TANF is to move people from cash
assistance to self-sufficiency. Achieving this goal can be inconsistent
with achieving a higher coverage rate. Several examples illustrate this
point:
First, expansion in earnings disregards that has occurred since welfare
reform was enacted, though the primary motive was an incentive to
increase work, also caused an increase in eligibility. Moreover, this
increase in eligibility was among earners who typically are eligible
for smaller grants and tend to have lower participation rates than
families without earnings. This is an example where the goal of
promoting work (through expansions in earned income disregards) may
have had a negative effect on the overall coverage rate.
Second, Congress established a five-year time limit on Federal TANF
assistance. Although the coverage rate estimates take into account the
number of families who lost aid due to the time limit (and do not count
such families in the denominator of the coverage rate estimate), they
do not make any allowance for families staying off of TANF to conserve
their time-limited assistance months. The coverage rate could be
increased by encouraging such families to return to the rolls, but this
would have the potentially undesirable effect of causing some families
to use up their limited months of assistance, especially if they are
receiving relatively small benefits. This would not be consistent with
the goal of maximizing long-term family well-being.
Third, expansions in work supports, child care, and other forms of non-
assistance benefits make it more attractive for some otherwise eligible
TANF cash assistance recipients to leave the TANF rolls to combine work
with these various non-assistance benefits. Some families receive help
with basic needs through diversion programs or post-employment bonuses
or other payments. These cash payments are considered non-assistance
and are not included in the official TANF caseload counts. Yet, the
coverage rate estimates ignore the TANF-eligible families who do not
receive cash assistance, but who do receive these other TANF-funded
benefits.
Also note that reducing spending on work-related, non-assistance
benefits and only providing cash would increase the coverage rate, but
this would be counter-productive to the TANF goals of increasing self-
sufficiency.
Throughout the study, GAO discusses the dual goals of access and
program integrity and seems to imply a larger Federal role and
responsibility in TANF than is provided for by statute. It also appears
that access is equated with outreach; we need to close the gap between
those who are eligible for the program and those who participate.
However, this is inconsistent with the very design of the program-time-
limited assistance with State flexibility in the design, which includes
pre-application job search and grant diversion.
To address the issue of eligibility versus participation, we conducted
a study entitled "Study of the TANF Application Process" (issued April,
2003) to assess the changes between the Aid to Families with Dependent
Children (AFDC) and the TANF programs and to determine the impact of
the changes on applicants and potential applicants. One of the
interesting conclusions was that potential applicants (those who were
informally diverted and who did not complete the application process)
were no worse off, and in some cases fared better, than those who went
on to receive cash assistance. The study also recognized the extensive
non-assistance benefits (such as transportation and child care)
provided through the program.
Head Start:
The report appears to estimate Head Start eligibility based on the
number of poor three-and four-year-olds. A very fundamental question
about the estimate is why the coverage rate includes three-and four-
year-olds, rather than just four-year-olds? This choice assumes that
the goal of the program should be to provide two years of Head Start to
all eligible children, rather than just one year. One reason the report
may include both age groups is because the program actually serves many
three-year-olds. This may simply be because the program has effectively
reached full coverage among four-year-olds, given that many may not
participate in Head Start because they are in prekindergarten or other
subsidized preschool programs or child care arrangements.
The GAO report should note that it oversimplifies Head Start
eligibility by ignoring some eligibility factors. For example, Head
Start eligibility includes "families that are eligible for public
assistance or would potentially be eligible in the absence of child
care services" (see "The 2003 Family Income Guidelines," Information
Memorandum, No. ACYF-IM-HS-03-03, April 17, 2003). This is not
reflected in the estimate on page 29.
Medicaid and SCHIP:
HHS believes the findings reinforced HHS' approach, which is to promote
ways that States can ensure that eligible individuals have access to
Medicaid and SCHIP while maintaining program integrity. However, it
believes that the report must more strongly recognize and reflect the
Federal-State nature of these programs. Medicaid and SCHIP are Federal
and State partnership programs. The Federal and State Governments
jointly finance the program while the States administer it within broad
Federal guidelines. Within those broad guidelines, each State
establishes eligibility criteria and monitors program integrity. The
Centers for Medicare & Medicaid Services (CMS) are very proud of its
efforts to promote access to health care for Medicaid and SCHIP-
eligible populations while at the same time promoting program
integrity. SCHIP continues to represent the largest single expansion of
health insurance coverage for children in more than 30 years. With the
goal of improving the quality of life for millions of vulnerable
children less than 19 years of age, SCHIP has made significant strides
in providing needed health coverage for low-income children, even
during periods of slow economic growth. Enrollment in SCHIP has
continued to build and SCHIP covered over 5.8 million children in the
Federal Fiscal Year (FFY) 2003, a 9 percent increase over the 5.3
million who were covered in FY 2002.
Additionally, multiple sources have found that SCHIP is contributing to
the decrease in low-income uninsured children, SCHIP's targeted
population. The Centers for Disease Control and Prevention reported
that the percent of uninsured children declined from 13.9 percent in
1997 to 10.1 percent in 2003 and that public coverage of near-poor
children has nearly tripled from 24 to 74 percent between 1997 and
2003. Clearly, SCHIP continues to substantially contribute to the
reduction in the number of low-income uninsured children, which shows
that SCHIP is reaching its targeted population.
This Administration is committed to increasing the number of eligible
children enrolled in SCHIP and Medicaid. President Bush has announced
his billion dollars "Cover the Kids" campaign, which would combine
Federal, State, and community-based efforts to identify children
eligible for SCHIP and Medicaid and help to enroll them in these
programs. President Bush firmly believes that this campaign will bring
millions of eligible children into the Medicaid and SCHIP programs.
CMS is very proud of the fact that States have used the flexibility
provided by SCHIP and Medicaid to come up with innovative ways to bring
children into the program, including innovative outreach techniques and
continued streamlining and simplification of the application and
eligibility determination process. Many States continue to focus on
efforts to simplify enrollment and retention processes for applicants
and enrollees, and to find ways to increase the number of uninsured low-
income children receiving child health assistance, even during times of
budgetary constraints.
Generally, in the face of declining funds for outreach, States have
become more innovative in how they use available funds to reach out to
low-income targeted families. States have reported partnering with
other Government agencies or private groups to maximize the use of
funds and focusing their outreach efforts more directly on hard-to-
reach populations. States also are using technology to make it easier
to enroll in SCHIP. Almost two dozen States allow some type of
application over the Internet and many States also allow application by
phone.
The SCHIP statute requires that States screen all SCHIP applicants for
Medicaid eligibility, and if found to be eligible for Medicaid, the
State must enroll them in Medicaid. Many States have reported that
SCHIP has had a significant impact on their Medicaid programs. While
SCHIP outreach and enrollment activities are intended to reach families
eligible for SCHIP, one of the benefits of the SCHIP program has been
to make more and more low-income uninsured families aware that they are
entitled to assistance that provides health care coverage for their
children.
In August 2001, CMS released a guide entitled "Continuing the Progress:
Enrolling and Retaining Low-Income Families and Children in Health Care
Coverage." Several chapters of this guide provided guidance to States
on addressing factors that affect eligible individuals' participation,
such as misperceptions about program requirements and eligibility
verification procedures. A separate chapter, "Program Monitoring by
States," specifically addressed how States could ensure program
integrity. Many States have told us that this guide has assisted them
in accomplishing both goals. CMS continues to provide technical
assistance to States in both areas.
CMS recently published a proposed Payment Error Rate Measurement (PERM)
regulation that takes steps to have States strengthen post-eligibility
controls by requiring a review of the correctness of eligibility
determinations.
In addition, CMS is committed to being able to calculate eligible but
unenrolled children, and as indicated above, the Assistant Secretary
for Planning and Evaluation (ASPE) is funding the Urban Institute's
model TRIM3 (now version 3) used by GAO in this report. ASPE and the
Urban Institute are still working on refining the TRIM3 model, but CMS
has taken other steps to continue to measure progress towards covering
eligible but uninsured children while the TRIM3 model is being refined.
CMS has a GPRA goal for SCHIP and Medicaid enrollment data that all
Sates must report on their progress towards covering uninsured children
on an annual basis. In addition, we believe that our final PERM
regulations will allow us to better quantify error rates resulting from
improper eligibility determinations.
CMS will continue to work with ASPE to refine the participation rates;
however, the GAO report does not recognize how difficult it is to
calculate valid and timely participation rates. In estimating the
number of eligibles, first, we must determine the eligibility criteria
across all States. Eligibility can differ across States by age, income,
assets, geographic area, and other criteria. Second, we have to
determine who is not yet covered using demographic data. Also, because
the participation rates rely in part on Medicaid and SCHIP enrollment
data, there is always a lag between State reports of enrollment data
and using it in the TRIM3 model. Finally, the individuals enrolled have
to be compared to who is eligible. Because these rates are so hard to
calculate on a timely basis, SCHIP has statutory reporting requirements
that serve as proxies for the participation rates described by GAO.
States are required to submit a report on their SCHIP programs on an
annual basis. One of the elements required by Title XXI is the State's
progress towards covering low-income children, typically children with
family incomes at or below 200 percent of the Federal poverty level.
This number of low-income uninsured children is a rough proxy for the
number of children eligible for SCHIP. By measuring State progress
towards reducing the uninsured, the States can assess their progress
towards reaching eligible children. The estimates also are timely in
that States report on their progress annually.
The GAO reported a 44 to 51 percent participation rate in SCHIP in
2000. The participation rates cited for SCHIP and Medicaid are based on
old data. This is more of a problem in SCHIP because the participation
rate is based on FY 2000 enrollment data and SCHIP was implemented in
FY 1998. SCHIP is a new program and, as noted in GAO's findings,
enrollment in SCHIP has almost doubled since FY 2000. The number of
eligibles has also changed with the improving economy and changes in
State programmatic features. CMS believes that the population rate
described for Medicaid is strong given the types of eligibles included
in the rate, i.e., adults and children. However, CMS believes that the
participation rate for children only in Medicaid is much higher.
Finally, as we discussed earlier, it is very difficult to calculate
timely and valid participation rates. While CMS works to improve the
participation rates, it will continue to use a proxy in SCHIP. CMS has
included information on State progress towards covering the uninsured
in its statutorily required report to Congress and the Office of the
Inspector General has also reported on State progress towards covering
the uninsured.
CMS does not produce regular reports to Congress for the Medicaid
program. However, CMS will continue its efforts to help States reduce
the rate of eligible but uninsured individuals, particularly children,
while ensuring program integrity.
[End of section]
Appendix VI: Comments from the Department of the Treasury:
DEPARTMENT OF THE TREASURY:
INTERNAL REVENUE SERVICE:
WASHINGTON, D.C. 20224:
COMMISSIONER:
February 8, 2005:
Mr. David Bellis:
Director, Education, Workforce, and Income Security:
United States Government Accountability Office:
Washington, DC 20548:
Dear Mr. Bellis:
I am responding to your draft report entitled "Means-Tested Programs:
Information on Program Access Can Be an Important Management Tool" (GAO-
05-221). This report is both timely and relevant. It underscores our
recent decision to establish the Earned Income Tax Credit (EITC)
participation rate as an Agency measure under the Government
Performance and Results Act of 1993, and thereby publicly underscores
our commitment to ensuring every eligible taxpayer claims the credit.
The report comprehensively addresses the numerous factors that
influence participation in means-tested programs such as the EITC. In
addition, it also acknowledges that actions taken to improve program
access often have an effect on program integrity, necessitating a
balanced approach to program delivery that places equal emphasis on
both access and integrity.
We agree that estimating participation rates can and should be a key
component of each program, as this will further emphasize the
importance of access, in conjunction with integrity, in assessing
program results. The EITC program is structured to achieve an
appropriate balance between the two, and we have developed targets for
both and implemented program strategies that support their achievement.
Relating to improving program access and increasing participation by
eligible individuals, our efforts include a coordinated outreach
strategy that leverages community-based and national partners to
deliver key messages to target populations, as well as the development
of useful and relevant materials aimed at assisting individuals in
determining their EITC eligibility. Education about eligibility
requirements is likewise an essential component of our strategy to
maintain and improve program integrity.
We believe our plans to measure participation rates and our progress in
meeting participation rate targets are quite strong. Nonetheless, we
appreciate the report's valuable insights into, and recommendations
regarding, this aspect of program delivery and performance assessment.
The report specifically recommends that, "As the IRS moves forward on
developing participation rate estimates to use as a program performance
measure for the Earned Income Tax Credit.... 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."
We agree with your recommendation. During 2005, the IRS will perform a
participation rate study based on a match to data provided by the
Bureau of the Census, the results of which will help us update our
participation rate estimates. In reporting the results of this study,
we will include these estimates, as well as note the limitations in our
methodology and data. Moreover, as we update these estimates we will
highlight any methodological changes and their corresponding effects on
these estimates.
If you have any questions, please contact Floyd Williams, Director,
Legislative Affairs, at (202) 622-3720.
Sincerely,
Signed by:
Mark W. Everson:
[End of section]
Appendix VII: Comments from the Social Security Administration:
SOCIAL SECURITY:
The Commissioner:
February 4, 2005:
Mr. David Bellis:
Director, Education, Workforce and Income Security Issues:
U.S. Government Accountability Office:
301 Howard Street, Suite 1200:
San Francisco, CA. 94105:
Dear Mr. Bellis:
Thank you for the opportunity to review and comment on the draft
report, "Means-Tested Programs: Information on Program Access Can Be an
Important Management Tool" (GAO-05-221).
Our response and technical comments to the draft report are enclosed.
If your staff has questions about the comments, they may contact
Candace Skurnik, Director, Audit Management and Liaison Staff, at (410)
965-4636.
Sincerely,
Signed by:
Jo Anne B. Barnhart:
Enclosure:
COMMENTS ON THE GOVERNMENT ACCOUNTABILITY OFFICE (GAO) DRAFT REPORT,
"MEANS-TESTED PROGRAMS: INFORMATION ON PROGRAM ACCESS CAN BE AN
IMPORTANT MANAGEMENT TOOL" GAO-05-221:
We appreciate the opportunity to comment on the draft report. We have
published a rich array of statistics about the Supplemental Security
Income (SSI) program and SSI recipients based on administrative program
records. Many of those statistics are updated monthly on the Agency's
Internet site, while others are published annually both in print and on
our Internet site. Over the past several years, we developed the
Financial Eligibility Model for estimating SSI eligibility and
participation and for considering the potential effects of SSI policy
changes on eligibility, participation, benefits, and poverty. To date,
we have produced participation rate estimates for the elderly
population (aged 65 years and older) for 1991 and 1996, using data from
the Survey of Income and Program Participation (SIPP) matched to
administrative data on SSI and Social Security benefits. There are many
limitations to updating those estimates on a more regular basis and
estimating categorical eligibility for the working-aged population is
inherently difficult. However, we continue to study the issues and
refine our methods. We also expect that SSA's role in administering the
subsidies for low-income persons under Part D of Medicare will increase
participation in SSI and will assist in identifying those who are not
participating.
Our response to the specific recommendation for SSA and a technical
comment are below.
Recommendation:
In order to ensure the Agency has information on program access, SSA
should consider the feasibility of providing participation rate
information (from existing source or another source) in SSA program
management reports.
Comment:
We agree. We have considered the feasibility of providing participation
rates and have found that there are major issues to be resolved prior
to producing such estimates. For example, SSA would need to determine
how best to estimate categorical eligibility among the working-aged
population based on self-reported survey data on both work and
individual functional limitations. We noted that the estimates in this
draft report suffer from this same limitation. GAO, which used the
Current Population Survey (CPS) in its work, estimates an SSI
participation rate that is quite high in comparison to our previous
estimates and prevailing estimates in the literature. Inherent
limitations in the CPS, including the lack of data on assets and the
measurement of annual income rather than monthly income, call into
question the validity of GAO's participation rate and program cost
estimates. The CPS is particularly weak in measuring SSI participation,
with many respondents confusing SSI with Social Security. While the
SIPP may help overcome some of these shortcomings in the CPS, that
survey has its own limitations. Despite these important issues, which
will require careful research and consideration, we agree that
estimating SSI participation rates on a regular basis could provide an
important tool for SSA in managing and developing long-range plans for
the SSI program.
Technical Comment:
Page 2, 1st paragraph-"the Supplemental Security Insurance Program"
should be revised to read, "the Supplemental Security Income Program."
[End of section]
Appendix VIII: GAO Contacts and Staff Acknowledgments:
GAO Contacts:
Gale Harris (202) 512-7235, harrisg@gao.gov;
Kathryn Larin (202) 512-5045, larink@gao.gov:
Staff Acknowledgments:
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.
[End of section]
Related GAO Products:
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.
FOOTNOTES
[1] The most recent participation rate estimates are available for the
years 1999 to 2003 depending on the program.
[2] The Transfer Income Microsimulation Model (TRIM3), developed by the
Urban Institute and funded by HHS, uses national survey data from the
Annual Social and Economic Supplement to the Current Population Survey
(CPS), the Survey of Income and Program Participation (SIPP), the
National Survey of America's Families, and information on eligibility
rules to estimate the population eligible for means-tested programs,
including CCDF, food stamps, Medicaid, SCHIP, SSI, TANF, and WIC. The
model estimates the amount each individual or household would receive
based on their characteristics.
[3] Two of these agencies, the Centers for Medicare & Medicaid Services
and the Administration for Children and Families, are part of the
Department of Health and Human Services.
[4] See GAO, Standards for Internal Control in the Federal Government,
GAO/AIMD-00-21.3.1(Washington, D.C.: Nov. 1999).
[5] Improper payments can include both overpayments and underpayments.
[6] While the Pell Grant program is not an entitlement program, we have
included it in this group because program administrators told us that
they manage it to allow all eligible people who apply to receive
benefits.
[7] For more details, see GAO, Earned Income Tax Credit Participation,
GAO-02-290R (Washington, D.C.: Dec. 14, 2001).
[8] We estimated a food stamp participation rate for another subgroup,
eligible individuals in working families, in prior work and found that
52 percent of these individuals were enrolled in 2001. See GAO, 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.: Mar. 5, 2004).
[9] In recent years WIC has been funded at levels that allow the
program to serve all or nearly all applicants who have sought services
and meet program eligibility criteria. However, WIC is a non-
entitlement program whose funding is determined annually through the
congressional appropriations process. In addition, because the SCHIP
and TANF programs provide grants directly to states and allow states
substantial flexibility in determining program eligibility and
implementation, funding constraints contribute to, but do not determine
coverage rates to the extent that they do for the remaining programs.
[10] Under CCDF, states may provide child care subsidies to families
with up to 85 percent of state median income, if they are working or
involved in education or training. States determine the income criteria
up to this maximum. See GAO, Child Care: Recent State Policy Changes
Affecting the Availability of Assistance for Low-Income Families, GAO-
03-588 (Washington, D.C.: May 5, 2003).
[11] HHS does not collect information on the number of children who
receive child care subsidies through the SSBG, TANF and TANF
Maintenance of Effort funding. Therefore, the agency estimated the
number of children served through those other funding sources by
dividing the total amount spent on child care services from each source
by the average cost of serving a child under CCDF.
[12] Even so, in some areas, Head Start programs are underenrolled. See
GAO, Head Start: Better Data and Processes Needed to Monitor
Underenrollment, GAO-04-17 (Washington, D.C.: Dec. 4, 2003).
[13] For more information on those who receive TANF-funded services
other than cash assistance, see GAO, 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.: Apr. 10,
2002).
[14] For more information on recent program changes see GAO, Supports
for Low-Income Families: States Serve a Broad Range of Families Through
a Complex and Changing System, GAO-04-256 (Washington, D.C.: Jan 26,
2004).
[15] While the exact effect of the methodological changes has not been
quantified, Urban Institute staff and HHS do not believe that the
methodological changes are driving measured changes in participation
rates. See U.S. Department of Health and Human Services, Indicators of
Welfare Dependence: Annual Report to Congress, 2004, (Washington,
D.C.:2004).
[16] Currie, Janet, The Take Up of Social Benefits, NBER Working Paper
10488, (Cambridge Mass.: National Bureau of Economic Research, May
2004). This study reviews literature on participation and coverage
rates among social programs in both the United States and the United
Kingdom.
[17] This decline in participation is consistent with national data
provided by USDA. Nationally, there is about a 30 percent decline in
enrollment when the value of a child's benefit decreases. The average
benefit declines by about 60 percent after the child's first birthday.
[18] Most programs waive the requirement for a face-to-face interview
in hardship cases.
[19] GAO, Child Care: States Exercise Flexibility in Setting
Reimbursement Rates and Providing Access for Low-Income Children, GAO-
01-894 (Washington D.C.: Sept. 2002).
[20] M. Bitler, J. Currie, and J. Scholz, WIC Eligibility and
Participation, Institute for Research on Poverty Discussion Paper 1255-
02 (Madison, WI: Institute for Research on Poverty, June 2002, revised
March 2003).
[21] SB/SE Research, Participation in the Earned Income Tax Credit
Program for Tax Year 1996 (Greensboro, N.C.: January 2002).
[22] See GAO, The Challenge of Data Sharing: Results of a GAO-Sponsored
Symposium on Benefit and Loan Programs, GAO-01-67 (Washington, D.C.:
Oct. 20, 2000), and GAO, Benefit and Loan Programs: Improved Data
Sharing Could Enhance Program Integrity, GAO/HEHS-00-19 (Washington,
D.C.: Sept. 13, 2000).
[23] Individuals receiving SSI are assured eligibility for Medicaid in
39 states and the District of Columbia. The remaining 11 states may use
different or more restrictive standards for disability, income or
assets; thus, SSI beneficiaries in these 11 states may not have assured
eligibility for Medicaid. These 11 states are known as 209(b) states
based on section 209(b) of the Social Security Amendments of 1972.
[24] See GAO, Standards for Internal Control in the Federal Government,
GAO/AIMD-00-21.3.1 (Washington D.C.: Nov. 1999), and GAO, Internal
Control Management and Evaluation Tool, GAO-01-1008G (Washington, D.C.:
Aug. 2001).
[25] Agency focus on program integrity might also be encouraged by
other agency-specific OMB guidance, the Presidents Management Agenda as
well as the GAO's High-Risk series--all strategies that encourage or
require agencies to focus on integrity.
[26] For more information on the implementation of the IPIA
governmentwide, see GAO, Financial Management: Fiscal Year 2003
Performance Accountability Reports Provide Limited Information on
Governmentwide Improper Payments, GAO-04-613T (Washington, D.C.: Apr.
15, 2004).
[27] Studies on program effectiveness typically do not provide
information on the number or characteristics of those eligible but not
participating in low-income programs.
[28] USDA also provides performance bonuses to reward states for their
performance in administering the Food Stamp Program. Awards focus on
payment error rates, negative error rates, participant access rates,
and timeliness of application processing.
[29] Pub. L. No. 103-432 (1994).
[30] CCDF's coverage rate also includes an estimate of the children
served through the TANF block grant and the Social Services Block
Grant.
[31] ED monitors the share of student financial aid applicants found
eligible for a Pell Grant who receive a grant. We would refer to this
as a "take-up" rate rather than a participation rate as we have defined
it, because it does not provide information on individuals who are
eligible but do not complete an application. Similarly, HUD monitors
the utilization rate in its housing choice voucher program. This
measure tracks the extent to which voucher recipients are able to
redeem their benefits by leasing apartments. Like the Pell Grant "take-
up" rate, this rate provides program managers with important
information they need to manage their programs, but it does not provide
them with a sense of the extent to which their programs are reaching
all eligible households and is, therefore, not comparable to a
participation or coverage rate for monitoring program access.
[32] For more details, see GAO, Earned Income Tax Credit Participation,
GAO-02-290R (Washington, D.C.: Dec. 14, 2001).
[33] For more details, see U.S. Department of Housing and Urban
Development, Trends in Worst Case Needs for Housings, 1979-1999: A
Report to Congress on Worst Case Housing Needs (Washington, D.C.:
December 2003).
[34] For more details, see GAO, Earned Income Tax Credit Participation,
GAO-02-290R (Washington, D.C.: Dec. 14, 2001).
[35] The SIPP collects a detailed inventory of real and financial
assets once a year and conducts more frequent measures of assets
relevant for assistance programs.
[36] HHS does not collect information on the number of children who
receive child care subsidies through the SSBG, TANF and TANF
Maintenance of Effort funding. Therefore, the agency estimated the
number of children served through those other funding source by
dividing the total amount spent on child care services from each source
by the typical cost of serving a child under CCDF.
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