Formula Grants
Census Data Are among Several Factors That Can Affect Funding Allocations Gao ID: GAO-09-832T July 9, 2009In past years, the federal government has annually distributed over $300 billion in federal assistance through grant programs using formulas driven in part by census population data. Of the more than $580 billion in additional federal spending, the American Recovery and Reinvestment Act of 2009 will obligate an estimated additional $161 billion to federal grant programs for fiscal year 2009. The U.S. Census Bureau (Bureau) puts forth tremendous effort to conduct an accurate count of the nation's population, yet some error in the form of persons missed or counted more than once is inevitable. Because many federal grant programs rely to some degree on population measures, shifts in population, inaccuracies in census counts, and methodological problems with population estimates can all affect the allocation of funds. This testimony discusses (1) how census data are used in the allocation of federal formula grant funds and (2) how the structure of the formulas and other factors can affect those allocations. This is based primarily on GAO's issued work on various formula grant programs and the allocation of federal funds.
Federal grants use various sources of population counts in their funding formulas. They include the decennial census, which provides population counts once every10 years, and also serves as the baseline for estimates of the population for the years between censuses--known as postcensal estimates. Other sources of population data include the Bureau's American Community Survey and the Current Population Survey conducted by the Bureau for the Bureau of Labor Statistics, which provides monthly data. The degree of reliance on population in funding formulas varies. For example, the Social Services Block Grant formula allocates funding based solely on a state's population relative to the total U.S. population. Other programs use population plus one or more variables to determine funding levels. Medicaid, for example, uses population counts and income to determine its federal reimbursement rate. On the basis of simulations GAO conducted of federal grant allocations by selected federal grant programs--for illustrative purposes only--we found that changes in population counts can affect, albeit modestly, the allocations of federal funds across the states. For example, in 2006 we found that compared to the $159.7 billion total federal Medicaid funding in 2004, 22 states would have shared an additional $208.5 million in Medicaid funding, 17 states would have lost a total of $368 million, and 11 states and the District of Columbia would have had their funding unchanged. In total 0.2 percent of Medicaid funds would have shifted as a result of the simulation. In addition to population data, various other factors related to the design of federal grant programs may mitigate the effect that population changes can have on the distribution of federal funds. For example, in order to prevent funding losses from a formula change, several programs include hold-harmless provisions guaranteeing that each recipient entity will receive a specified proportion of the prior year's amount or share regardless of population changes.
GAO-09-832T, Formula Grants: Census Data Are among Several Factors That Can Affect Funding Allocations
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Testimony:
Before the Subcommittee on Information Policy, Census, and National
Archives, Committee on Oversight and Government Reform, House of
Representatives:
United States Government Accountability Office:
GAO:
For Release on Delivery:
Expected at 2:00 p.m. EDT:
Thursday, July 9, 2009:
Formula Grants:
Census Data Are among Several Factors That Can Affect Funding
Allocations:
Statement of Robert Goldenkoff, Director:
Strategic Issues:
GAO-09-832T:
GAO Highlights:
Highlights of GAO-09-832T, a testimony before the Subcommittee on
Information Policy, Census, and National Archives, Committee on
Oversight and Government Reform, House of Representatives.
Why GAO Did This Study:
In past years, the federal government has annually distributed over
$300 billion in federal assistance through grant programs using
formulas driven in part by census population data. Of the more than
$580 billion in additional federal spending, the American Recovery and
Reinvestment Act of 2009 will obligate an estimated additional $161
billion to federal grant programs for fiscal year 2009.
The U.S. Census Bureau (Bureau) puts forth tremendous effort to conduct
an accurate count of the nation‘s population, yet some error in the
form of persons missed or counted more than once is inevitable. Because
many federal grant programs rely to some degree on population measures,
shifts in population, inaccuracies in census counts, and methodological
problems with population estimates can all affect the allocation of
funds.
This testimony discusses (1) how census data are used in the allocation
of federal formula grant funds and (2) how the structure of the
formulas and other factors can affect those allocations. This is based
primarily on GAO‘s issued work on various formula grant programs and
the allocation of federal funds.
What GAO Found:
Federal grants use various sources of population counts in their
funding formulas. They include the decennial census, which provides
population counts once every 10 years, and also serves as the baseline
for estimates of the population for the years between censuses”known as
postcensal estimates. Other sources of population data include the
Bureau‘s American Community Survey and the Current Population Survey
conducted by the Bureau for the Bureau of Labor Statistics, which
provides monthly data.
The degree of reliance on population in funding formulas varies. For
example, the Social Services Block Grant formula allocates funding
based solely on a state‘s population relative to the total U.S.
population. Other programs use population plus one or more variables to
determine funding levels. Medicaid, for example, uses population counts
and income to determine its federal reimbursement rate.
On the basis of simulations GAO conducted of federal grant allocations
by selected federal grant programs”for illustrative purposes only”we
found that changes in population counts can affect, albeit modestly,
the allocations of federal funds across the states. For example, in
2006 we found that compared to the $159.7 billion total federal
Medicaid funding in 2004, 22 states would have shared an additional
$208.5 million in Medicaid funding, 17 states would have lost a total
of $368 million, and 11 states and the District of Columbia would have
had their funding unchanged. In total 0.2 percent of Medicaid funds
would have shifted as a result of the simulation.
In addition to population data, various other factors related to the
design of federal grant programs may mitigate the effect that
population changes can have on the distribution of federal funds. For
example, in order to prevent funding losses from a formula change,
several programs include hold-harmless provisions guaranteeing that
each recipient entity will receive a specified proportion of the prior
year‘s amount or share regardless of population changes.
View [hyperlink, http://www.gao.gov/products/GAO-09-832T] or key
components. For more information, contact Robert Goldenkoff (202) 512-
2757 or goldenkoffr@gao.gov.
[End of section]
Chairman Clay, Mr. McHenry, and Members of the Subcommittee:
Thank you for the opportunity to be here today to discuss the role that
the nation's population count plays in the allocation of federal funds
to states and localities. As agreed with the Subcommittee, my remarks
today describe (1) how census data are used in the allocation of
federal formula grant funds, and (2) how the structure of the formulas
and other factors can affect those allocations.
My main point is that although population counts play an important role
in the distribution of federal funds, other factors, such as the design
of the grant formulas, can mitigate the effect that any population
changes have on funding levels. It does not necessarily follow that an
increase or decrease in population size would have a proportional
effect on the amount of federal assistance an entity ultimately
receives. Nevertheless, because population estimates are important for
federal funding allocations, and the decennial census is the foundation
for these estimates, an accurate enumeration in 2010--including a
reduction in the historic undercount of minority and other populations,
as previously reported[Footnote 1]--is essential.
As you well know, the decennial census is a critical national effort
mandated by the Constitution, and census data are used to apportion
congressional seats and redraw congressional districts. Data from the
decennial census, and annual estimates of the nation's population that
are derived from the decennial, directly and indirectly affect the
allocation of federal assistance to state and local governments. In
past years, the federal government distributed over $300 billion
annually in federal assistance through federal grant programs to states
and localities using formulas driven in whole or in part by census
population data. The enactment of the American Recovery and
Reinvestment Act of 2009 (Recovery Act)[Footnote 2]--which is intended
to help restore the economy, invest in our national infrastructure, and
minimize and avoid reduction in state and local government services--
will allocate additional money through grant programs. Of the $580
billion in additional federal spending associated with the Recovery
Act, the federal government will obligate an estimated additional $161
billion to federal grant programs for fiscal year 2009, including some
programs that depend on census population data in whole or in part to
determine the amount of federal assistance.
The Census Bureau (Bureau) puts forth tremendous effort to conduct an
accurate count of the nation's population. However, some degree of
error in the form of persons missed (an undercount), counted more than
once (an overcount), or in the wrong location is inevitable. Such
errors are particularly problematic because of their differential
impact on various subgroups. Minorities, renters, and children, for
example, are more likely to be undercounted by the census, while more
affluent groups, such as people with vacation homes, are more likely to
be enumerated more than once.
Further, the U.S. has an increasingly mobile population, and natural
disasters such as Hurricane Katrina can have a dramatic impact on
population counts of affected communities. For example, in the wake of
Hurricane Katrina, the Red Cross estimated that over a half a million
people were displaced and either temporarily or permanently migrated to
other areas. Because many federal grant programs rely to some degree on
population measures, shifts in population, inaccuracies in census
counts, and methodological problems with population estimates can all
affect the allocation of funds.
My remarks are based primarily on reports we have previously issued on
various formula grant programs and the allocation of federal funds
(please see the final pages of this testimony for a list of related GAO
products). To update information from our prior work, we reviewed
funding data for selected grant programs in the Office of Management
and Budget's Analytical Perspectives, Budget of the U.S. Government,
Fiscal Year 2010 and interviewed Bureau officials. We selected five
grant programs based on prior work we conducted that illustrate how
population and other factors can affect the allocation of federal
funds. According to the General Services Administration's Catalog of
Federal Domestic Assistance, the federal government administers over
1,800 different grant programs. Some grant programs use census
population data in their allocation formulas while others do not. The
five programs we selected constituted about $225.7 billion in fiscal
year 2008 obligations, and represented more than 40 percent of federal
program grant obligations in that year. The programs we selected (and
the amount of money obligated in fiscal year 2008) include:
* the Medical Assistance Program (Medicaid),[Footnote 3] which is a
joint federal-state program that finances health care for certain low-
income individuals (about $214.0 billion in fiscal year 2008
obligations);[Footnote 4]
* the Community Development Block Grant program (CDBG),[Footnote 5]
which is intended to develop viable urban communities by providing
decent housing and a suitable living environment and expanding economic
opportunities, principally for persons of low and moderate income
(about $4.9 billion in fiscal year 2008 obligations);[Footnote 6]
* the Vocational Rehabilitation Program (VR),[Footnote 7] which
administers grants for the purpose of providing vocational
rehabilitation services to persons with disabilities who are seeking
competitive employment ($2.9 billion in fiscal year 2008 obligations);
[Footnote 8]
* the Social Services Block Grant (SSBG) program,[Footnote 9] which is
a federal program that provides funds to assist states in delivering
social services to adults and children ($1.7 billion in fiscal year
2008 obligations); and:
* the Ryan White Comprehensive AIDS Resources Emergency (CARE) Act of
1990,[Footnote 10] which was enacted to address the needs of
jurisdictions, health care providers, and people with human
immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS)
and their family members (about $2.2 billion in fiscal year 2008
obligations).
Changes in Census Population Counts Can Affect the Allocation of
Federal Funds:
Federal grants use various sources of population counts in their
funding formulas. First, the Bureau conducts the decennial census,
which provides population counts once every 10 years, and also
estimates the population for the years between censuses--known as
postcensal estimates. For example, the SSBG allocation formula uses the
most recent postcensal population estimates to distribute funds.
Second, the Bureau's American Community Survey provides detailed annual
data on socioeconomic characteristics for the nation's communities and
is used to allocate federal funds for such programs as the Section 8
housing voucher program,[Footnote 11] an effort aimed at increasing
affordable housing choices for very low-income households. In addition,
the Current Population Survey conducted by the Bureau for the Bureau of
Labor Statistics provides monthly data and is used to allocate funds
for programs under the Workforce Investment Act of 1998,[Footnote 12]
which provides workforce development services to employers and workers.
Among funding formulas that rely on population data, the degree of
reliance varies. On the one hand, the SSBG formula allocates funding
based on a state's population relative to the total U.S. population. On
the other hand, some formulas use population plus one or more other
variables to determine funding levels. Medicaid, for example, uses
population counts and income to determine the federal reimbursement
rate. The Medicaid formula is based on the ratio of a state's aggregate
personal income to the same state's population relative to aggregate
U.S. per capita personal income. Other grant programs, such as CDBG,
are driven by multiple factors in addition to population such as
poverty, housing overcrowding, and the age of the housing. Population
plays a more limited role in other programs. Federal assistance under
one part of the CARE Act does not use census population counts in its
funding formula. Rather, census population counts are used in this part
as criteria for program eligibility--CARE Act funds under this part are
awarded to urbanized areas, which are determined in part by census
population counts. The actual amount of federal assistance is based on
the counts of people with HIV/AIDS.[Footnote 13]
Accurate Population Counts Are Important for Allocating Federal
Assistance:
On the basis of simulations we conducted of formula grant allocations,
we found that changes in population counts can affect, albeit modestly,
the allocations of federal funds for the programs analyzed. Note that
these simulations were for illustrative purposes only--to demonstrate
the effect that alternative population estimates could have on selected
federal grant programs.
In two prior reports, we simulated the reallocations that would have
resulted from using alternative population counts for Medicaid
allocations.[Footnote 14] In our 2003 report, based on population
estimates that differed from the 2000 Census count by about 3.2 percent
across the U.S. and varying state by state, we found that of the $110.9
billion total federal Medicaid spending in 2002, 18 states would have
shared an additional $377.0 million in Medicaid funding, 21 states
would have lost a collective $363.2 million, and 11 states and the
District of Columbia would have had their funding unchanged.
In our 2006 report, based on population estimates that differed from
the 2000 Census count by about 0.5 percent across the U.S. and varying
state by state, we found that of the $159.7 billion total federal
Medicaid funding in 2004, 22 states would have shared an additional
$208.5 million in Medicaid funding, 17 states would have lost a total
of $368 million, and 11 states and the District of Columbia would have
had their funding unchanged.[Footnote 15] In total, 0.2 percent of
Medicaid funds would have shifted as a result of the simulation. In our
2006 report, we also simulated the reallocations of SSBG funding and
found that of the $1.7 billion in SSBG allocations, 27 states and the
District of Columbia would have shared a gain of $4.2 million and 23
states would have shared a loss of $4.2 million. In total 0.2 percent
of SSBG funds would have shifted as a result of the simulation.
The Census Bureau Has Procedures For Addressing Errors In Population
Counts:
Since the completeness and accuracy of population data can modestly
affect grant funding streams and other applications of census data, the
Bureau has used a variety of programs to address possible errors in
population counts and estimates. Not all of these programs are
completed by December 31 of the decennial year--the date on which
population data are to be sent to the President for purposes of
congressional apportionment. Corrections made after this date may be
reflected in the population counts made available for redistricting or
the allocation of federal funds.
* Demographic Full Count Review: For the 2000 Census, analysts were
hired under contract by the Bureau to identify, investigate, and
document suspected data discrepancies in order to clear census data
files and products for subsequent processing or public release. Bureau
reviewers were to determine whether and how to correct the data by
weighing quality improvements against time and budget constraints.
Bureau officials told us that they expect to implement something
similar to the 2000 program, but they have not made a final decision
for 2010.
* Count Question Resolution (CQR): In addition, for the 2000 Census the
Bureau implemented the CQR program to provide a mechanism for state,
local, and tribal governments, as well as Bureau personnel, to correct
the counts of housing units and other types of dwellings and their
associated populations. Governmental entities could use the updated
information when applying for federal assistance that uses census data
as part of the allocation formula. Between the program's initiation in
June 2001 and its completion in September 2003, the CQR program
corrected data affecting over 1,180 of the nation's more than 39,000
governmental units. Although the national-and state-level revisions
were relatively small, in some cases the corrections at the local level
were substantial. For example, the Bureau added almost 1,500 persons to
the population count of Cameron, Missouri, when CQR found that a
prison's population was erroneously omitted. Bureau officials told us
that they expect to implement something similar to the 2000 program,
but they have not made a final decision for 2010.
* Census Challenge Program: Further, to permit challenges to population
estimates prepared by the Bureau, the Bureau administers a program
whereby governmental units--including states, counties, and tribal and
local governments--may file informal challenges within a designated
period of time after the estimate is released by the Bureau. In the
event that the challenge cannot be resolved informally, the
governmental unit may proceed with a formal challenge where the state
or local government unit has a right to a hearing.[Footnote 16] Using
such documentation as new construction permits, and data from water and
electrical utilities, localities can ask the Bureau to review and
update their population counts. Between 2001 and 2007, 259 challenges
led to adjustments in census population estimates.
* Coverage Measurement: Beginning with the 1980 Census, the Bureau has
had procedures in place to measure the accuracy of the census (or
"coverage") by relying on additional information obtained from an
independent sample survey of the population. However, due to concerns
over the quality of the data and other factors, the Bureau has never
used the results of its coverage measurement efforts to adjust the
census population count. For the 2010 Census, the Bureau plans to
measure coverage error for various demographic groups and geographic
areas, but does not plan to use the results to adjust the final
population counts.
Factors Other Than Population Can Affect Distribution of Federal Funds:
Although accurate population counts and estimates play an important
role in allocating federal assistance, various other factors related to
the design of federal grant programs may mitigate or increase the
effect that population changes can have on the distribution of federal
funds. These factors include floors on matching rates, floors for small
states, hold-harmless provisions, complex formula structures, lags in
data, and whether funding for a specific program is from a fixed pool
or open ended. I will describe each in greater detail.
* Floors on Matching Rates: Some grant programs employ floors in order
to mitigate the outcome that would result if a particular grant
allocation were determined by the funding formula alone. For example,
the Medicaid statute provides for a 50 percent floor.[Footnote 17] In
our 2003 report on federal formula grant funding, we found that for
certain states the Medicaid matching provisions mitigated the effect of
the Medicaid funding formula, which has a population component.
[Footnote 18] In 2002, under the statutory formula, which is based on
personal income relative to state's population, Connecticut--a state
with a high per-capita income--would have received a 15 percent federal
matching rate. Because of the statutory floor, Connecticut instead
received a 50 percent federal match.
* Floors for Small States: To ensure at least a minimum level of
funding for all states, program formula allocations with formulas that
rely on population data can include floors for small states. The VR
formula employs a floor allocation that overrides the population-based
allocations.[Footnote 19] The least-populated states receive a higher
allocation than they would have otherwise received under the formula.
* Hold-Harmless Provisions: In order to prevent funding losses from a
formula change, programs can include hold-harmless provisions
guaranteeing a level of funding that is based on a prior year's
funding. For example, one part of the CARE Act contains hold-harmless
provisions whereby some recipients are guaranteed they will receive at
least as much funding as in the previous year.[Footnote 20]
* Complex Formula Structures: Many formulas include measures other than
population to distribute funds. VR allocations depend upon three
factors: the state's 1978 allocation, population, and per capita
income.[Footnote 21] As a result, the effect of increases in population
may be mitigated by their 1978 allocations and changes to the state's
per capita income. CDBG allocations are based on a complex dual formula
structure using statistical factors reflecting several broad dimensions
of need. Each metropolitan city and urban county is entitled to receive
an amount equaling the greater of the amounts calculated under two
formulas. The factors involved in the first formula are population,
extent of poverty, and extent of overcrowded housing, weighted 0.25,
0.50, and 0.25, respectively. The factors involved in the second
formula are population growth lag, poverty, and age of housing,
weighted 0.20, 0.30, and 0.50, respectively.[Footnote 22] In these
formulas, the inclusion of population moderates the targeting impact of
the other formula factors. We previously reported that complex
approaches such as this can result in widely different payments to
communities with similar needs.[Footnote 23]
* Lags in Data Used to Allocate Funds: Statutes that require formulas
to use specific sources of data can introduce lags in the data being
used when those data are not immediately available. Lags inherent in
the collection and publication of data by statistical agencies that
gather and process data can result in a formula relying on data that
are several years old. For example, the Medicaid statute generally
specifies that matching rates for Medicaid be calculated 1 year before
the fiscal year in which they are effective, using a 3-year average of
the most recently available per capita income data reported by the
Department of Commerce.[Footnote 24] For fiscal year 2007, matching
rates were calculated at the beginning of fiscal year 2006 using 3-year
average data for 2002 through 2004--the latest then available. Where
recipients have been affected by recent changes to their population,
the recipient may view such allocations as slow to respond to these
changes in population.
* Fixed Pool versus Open Ended Funding: Most programs have a finite or
fixed pool of funds to distribute, while others do not. In a fixed pool
program, such as SSBG, when a population change results in an increased
allocation for one state, the increase is offset by decreases in
allocations to one or more other states. In open-ended programs, such
as Medicaid, states can receive more funding when states spend more
from their own source of revenue, without a corresponding decrease to
other states.
In conclusion, while population data play an important role in
allocating federal assistance through formula grant programs, other
grant-specific features--several of which I have discussed today--can
also play a role in funding allocations, and in some cases can mitigate
or entirely mute the impact of a change in population. Importantly, not
all grants work the same, and an increase or decrease in population
size may not have a proportional impact on ultimate funding levels.
Nevertheless, given the importance of census data as a baseline for
postcensal estimates used for grant programs, as well as for
congressional apportionment and redistricting, counting the nation's
population once, only once, and in the right location in 2010 is an
essential first step.
Mr. Chairman, this concludes my remarks. I will be glad to answer any
questions that you or other Subcommittee members may have.
Contacts and Acknowledgments:
For further information regarding this statement, please contact Robert
Goldenkoff, Director, Strategic Issues, on (202) 512-2757 or at
goldenkoffr@gao.gov. Contact points for our Offices of Congressional
Relations and Public Affairs may be found on the last page of this
testimony. Individuals making key contributions to this statement
included Ty Mitchell, Assistant Director; Sarah Cornetto; Erin Dexter;
Robert Dinkelmeyer; Gregory Dybalski; Amber G. Edwards; Amanda Harris;
and Tamara F. Stenzel.
[End of section]
Related GAO Products:
Ryan White CARE Act: Estimated Effect of Proposed Stop-Loss Provision
on Urban Areas. [hyperlink, http://www.gao.gov/products/GAO-09-472R].
Washington, D.C.: March 6, 2009.
2010 Census: Population Measures Are Important for Federal Allocations.
[hyperlink, http://www.gao.gov/products/GAO-08-230T]. Washington, D.C.:
October 27, 2007.
Ryan White CARE Act: Impact of Legislative Funding Proposal on Urban
Areas. [hyperlink, http://www.gao.gov/products/GAO-08-137R].
Washington, D.C.: October 5, 2007.
Vocational Rehabilitation: Improved Information and Practices May
Enhance State Agency Earnings Outcomes for SSA Beneficiaries.
[hyperlink, http://www.gao.gov/products/GAO-07-521]. Washington, D.C.:
May 23, 2007.
Medicaid: Strategies to Help States Address Increased Expenditures
during Economic Downturns. [hyperlink,
http://www.gao.gov/products/GAO-07-97]. Washington, D.C.: October 18,
2006.
Community Development Block Grants: Program Offers Recipients
Flexibility but Oversight Can Be Improved. [hyperlink,
http://www.gao.gov/products/GAO-06-732]. Washington, D.C.: July 28,
2006.
Community Development Block Grant Formula: Options for Improving the
Targeting of Funds. [hyperlink,
http://www.gao.gov/products/GAO-06-904T]. Washington, D.C.: June 27,
2006.
Federal Assistance: Illustrative Simulations of Using Statistical
Population Estimates for Reallocating Certain Federal Funding.
[hyperlink, http://www.gao.gov/products/GAO-06-567]. Washington, D.C.:
June 22, 2006.
Data Quality: Improvements to Count Correction Efforts Could Produce
More Accurate Census Data. [hyperlink,
http://www.gao.gov/products/GAO-05-463]. Washington, D.C.: June 20,
2005.
Grants Management: Additional Actions Needed to Streamline and Simply
Processes. [hyperlink, http://www.gao.gov/products/GAO-05-335].
Washington, D.C.: April 18, 2005.
Medicaid Formula: Differences in Funding Ability among States Often Are
Widened. [hyperlink, http://www.gao.gov/products/GAO-03-620].
Washington, D.C.: July 10, 2003.
Formula Grants: 2000 Census Redistributes Federal Funding Among States.
[hyperlink, http://www.gao.gov/products/GAO-03-178]. Washington, D.C.:
February 24, 2003.
2000 Census: Coverage Measurement Programs' Results, Costs, and Lessons
Learned. [hyperlink, http://www.gao.gov/products/GAO-03-287].
Washington, D.C.: January 29, 2003.
Formula Grants: Effects of Adjusted Population Counts on Federal
Funding to States. GAO/HEHS-99-69. Washington, D.C.: February 26, 1999.
[End of section]
Footnotes:
[1] GAO, 2010 Census: Communications Campaign Has Potential to Boost
Participation, [hyperlink, http://www.gao.gov/products/GAO-09-525T]
(Washington, D.C.: Mar. 23, 2009).
[2] Pub. L. No. 111-5, 123 Stat. 115 (Feb. 17, 2009).
[3] 42 U.S.C. §§ 1396 to 1396w-2.
[4] Growing obligations in fiscal years 2009 and 2010 would then be
supplemented by an estimated $79.8 billion under the Recovery Act.
[5] 42 U.S.C. §§ 5301-5321.
[6] The CDBG obligation in fiscal years 2009 and 2010 will be
supplemented by an estimated $3 billion under the Recovery Act.
[7] 29 U.S.C. §§ 720-751.
[8] The VR obligation in fiscal year 2009 will be supplemented by an
estimated $540 million under the Recovery Act.
[9] 42 U.S.C. §§ 1397-1397f.
[10] 42 U.S.C. §§ 300ff to 300ff-121.
[11] 42 U.S.C. § 1437f.
[12] Pub. L. No. 105-220, 112 Stat. 936 (Aug. 7, 1998).
[13] See, e.g., 42 U.S.C. §§ 300ff-11, 300ff-13.
[14] GAO, Federal Assistance: Illustrative Simulations of Using
Statistical Population Estimates for Reallocating Certain Federal
Funding, [hyperlink, http://www.gao.gov/products/GAO-06-567]
(Washington, D.C.: June 22, 2006) and Medicaid Formula: Differences in
Funding Ability among States Often Are Widened, [hyperlink,
http://www.gao.gov/products/GAO-03-620] (Washington, D.C.: July 10,
2003).
[15] [hyperlink, http://www.gao.gov/products/GAO-06-567].
[16] 15 C.F.R. §§ 90.1-90.18.
[17] The Medicaid statute also generally provides for an 83 percent
ceiling on the matching rate of each state's contribution. 42 U.S.C.
§1396d(b). However, 1973 is the most recent year that any state has
qualified for the 83 percent ceiling in the federal matching rate.
[18] [hyperlink, http://www.gao.gov/products/GAO-03-178].
[19] 29 U.S.C. § 730(a).
[20] See, e.g., 42 U.S.C. § 300ff-13(a)(4).
[21] 29 U.S.C. § 730.
[22] 42 U.S.C. § 5306.
[23] GAO, Community Development Block Grant Formula: Options for
Improving the Targeting of Funds, [hyperlink,
http://www.gao.gov/products/GAO-06-904T] (Washington, D.C.: June 27,
2006).
[24] 42 U.S.C. § 1301(a).
[End of section]
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