Federal Assistance: Illustrative Simulations of Using Statistical Population Estimates for Reallocating Certain Federal Funding
Published: 2006-06-23T00:00:00

Fast Facts:

Highlights:
section_title: Why GAO Did This Study
paragraphs: Decennial census data need to be as accurate as possible because the population counts are used for, among other purposes, allocating federal grants to states and local governments. The U.S. Census Bureau (Bureau) used statistical methods to estimate the accuracy of 1990 and 2000 Census data. Because the Bureau considered the estimates unreliable due to methodological uncertainties, they were not used to adjust the census results. Still, a key question is how sensitive are federal formula grants to alternative population estimates, such as those derived from statistical methods? GAO was asked to identify (1) the top 20 formula grant programs based on the amount of funds targeted by any means, and (2) the amount of money allocated for Medicaid and Social Services Block Grant (SSBG), and the prospective impact of estimated population counts from the 1990 and 2000 Censuses on state allocations for these two programs. Importantly, as agreed, GAO's analysis only simulates the formula grant reallocations. We used fiscal year 2004 Medicaid state expenditure and 2005 SSBG state allocation data, the most recent data available.
section_title: What GAO Found
paragraphs: In fiscal year 2004, the top 20 formula grant programs together had $308 billion in obligations, or 67 percent of the total $460.2 billion obligated by the 1,172 federal grant programs. Medicaid was the largest formula grant program, with obligations of $183.2 billion, or nearly 40 percent of all grant obligations. The federal government allocated $159.7 billion to states in Medicaid funds (not including administrative costs such as processing and making payments to service providers) and $1.7 billion in SSBG funds. Recalculating these allocations using statistical population estimates from the Accuracy and Coverage Evaluation and the Post Enumeration Survey--independent sample surveys designed to estimate the number of people that were over- and undercounted in the 2000 and 1990 Censuses--would have produced the following results. First, a total of 0.23 percent ($368 million) of federal Medicaid funds would have been shifted overall among the states in fiscal year 2004 and 0.25 percent ($4.2 million) of SSBG funds would have shifted among the states in fiscal year 2005 as a result of the simulations using statistical population estimates from the 2000 Census. Second, with respect to Medicaid, 22 states would have received additional funding, 17 states would have received less funding, and 11 states and the District of Columbia would have received the same amount of funding using statistical population estimates from the 2000 Census. Based on a fiscal year 2004 federal Medicaid allocation to the states of $159.7 billion, Nevada would have been the largest percentage gainer, with an additional 1.47 percent in funding, and Wisconsin would have lost the greatest percentage--1.46 percent. Third, with respect to SSBG, 27 states and the District of Columbia would have gained funding, and 23 states would have lost funding using statistical population estimates from the 2000 Census. Based on a fiscal year 2005 SSBG allocation of $1.7 billion, Washington, D.C. would have been the biggest percentage gainer, receiving an additional 2.05 percent in funding, while Minnesota would have lost the greatest percentage funding--1.17 percent. Fourth, statistical population estimates from the 2000 Census would have shifted a smaller percentage of funding compared to those using the 1990 Census because the difference between the actual and estimated population counts was smaller in 2000 compared to 1990.

section_title: Letter
paragraphs: Data from the decennial census are used to apportion congressional seats,  redraw congressional districts, and allocate federal assistance to state and  local governments through certain formula grant programs, as well as for a  number of other public- and private-sector purposes.  As a result, it is  essential that census data be as complete and accurate as practicable.   Although the U.S. Census Bureau (Bureau) puts forth tremendous effort to  conduct a complete and accurate population count, some amount of error  is inevitable because of the nation’s size and demographic complexity, and  the inherent limitations of census-taking methods.
To estimate the accuracy of the 2000 Census and possibly adjust for any  errors, the Bureau conducted the Accuracy and Coverage Evaluation  (A.C.E.), which was an independent sample survey designed to estimate  the number of people that were over- and undercounted in the census, a  problem the Bureau refers to as “coverage error.”
In 1999, the Supreme Court ruled that the Census Act prohibited the use of  statistical sampling for purposes of apportioning seats in the House of  Representatives, but the Supreme Court’s decision did not specifically  address the use of statistical sampling for other purposes, including  adjusting the data used to allocate federal assistance via formula grants.   However, after conducting a number of evaluations of the A.C.E. samples  and methodology, the Bureau concluded that the A.C.E. population  estimates were flawed and that all potential uses of these data would be  inappropriate.  As a result, the Bureau’s parent agency, the Department of  Commerce, determined that the A.C.E. estimates should not be used for  any purpose that legally requires data from the decennial census. We have  also stated that the A.C.E. statistical population estimates are unreliable.
Still, a key question that arises is how sensitive are federal formula grants  to alternative population estimates, such as those derived by statistical  methods?  With that in mind, you asked us to examine how statistical  population estimates might have redistributed federal assistance among  the states had they been used to calculate formula grants rather than the  actual population counts.   In response, and as requested, we recalculated  certain federal assistance to the states using the A.C.E. population  estimates from the 2000 Census, as well as the population estimates  derived from the Post-Enumeration Survey (PES)—the independent  sample survey the Bureau administered to evaluate the accuracy of the  1990 Census.  While only the actual census numbers should be used for  official purposes, our analysis shows the extent to which alternative  population counts would impact the distribution of federal grant funds and  can help inform congressional decision making on the design of future  censuses.  As agreed with your offices, we identified (1) the top 20 formula  grant programs based on the amount of funds targeted by any means, and  (2) how much money would have been allocated using census data for  certain formula grant programs, and the prospective impact of using  estimated population counts from the 1990 and 2000 Censuses to  recalculate state allocations for these grant programs.
To address the first objective, we used expenditure and obligations data  from the fiscal year 2004 Consolidated Federal Funds Report (CFFR), the  most recent year for which data were available.  For the second objective,  we recalculated the amount of federal funding allocated to the states for  Medicaid using the 2005 fiscal year Federal Medical Assistance Percentage  (FMAP) with 2004 state expenditure data, and recalculated the Social  Services Block Grant (SSBG) state allocations using 2005 fiscal year  allocation data.  In both cases we used the most recent year for which data  were available. We based our calculation on the official population counts  from the 1990 and 2000 Censuses. We then recalculated the allocations  using the PES population estimates from the 1990 Census, and the A.C.E.  population estimates from the 2000 Census.
The federal share of total Medicaid program costs is determined using a  statutory formula that calculates each state’s FMAP.  SSBG receives an  annual appropriation that is distributed in proportion to each state’s  population.  We selected these programs for our analysis because they  would be particularly sensitive to alternative population estimates.   Medicaid is the largest formula grant program; thus any changes would  redistribute more money compared to other programs. Further, any  changes in SSBG would have a proportional impact on the distribution of  state funds.
Importantly, our analysis only simulates the formula grant reallocations  using A.C.E. data and was done for illustrative purposes—to show the  sensitivity of these two formula grant programs to alternative population  estimates.  (See app. I for a more detailed description of our methodology.)   We use the term “allocation” to include Department of Health and Human  Services (HHS) reimbursement to states of Medicaid expenditures subject  to the FMAP formula (net of administrative costs) and SSBG state  allotments. (Appendix II has additional details on Medicaid and the formula  used to allocate money; app. III has the same information for SSBG.)  We  use the term “statistical population estimates” to refer to the results of the  coverage measurement programs that the Bureau conducted following the  1990 and 2000 Censuses (but were not used to adjust the actual census  counts).
We conducted our work between November 2005 and May 2006 in  accordance with generally accepted government auditing standards.   Because we did not evaluate the policies or operations of any federal  agency to develop the information presented in this report, and because we  are not making any recommendations, we did not seek agency comments.   However, we discussed a statement of facts for this report with Census  Bureau officials, who provided us with technical comments that we have  incorporated where appropriate.
subsections: section_title: Background
paragraphs: To help measure the quality of the 2000 Census and to possibly adjust for  any over- or undercounts of various demographic groups, the Bureau  designed the A.C.E. program, a separate and independent sample survey  conducted as part of the 2000 Census. When matched to the census data,  A.C.E. data were to enable the Bureau to use statistical estimates of net  coverage errors to adjust final census tabulations. However, in March 2003,  after much research and deliberation, the Bureau decided against using any  A.C.E. estimates of coverage error to adjust the 2000 Census, because of  several methodological concerns.
The Bureau measured the accuracy of the 1990 Census as well, and  recommended statistically adjusting the results.  However, the Secretary of  Commerce determined that the evidence to support an adjustment was  inconclusive and decided not to adjust the 1990 Census.  In 1999 we  examined how these statistical population estimates might have  redistributed federal assistance among the states had they been used to  calculate formula grants.
Looking toward the 2010 Census, the Bureau plans to use statistical  population estimates to (1) produce estimates of components of census net  and gross coverage error (the latter includes misses and erroneous  enumerations) in order to assess accuracy, (2) determine whether the  strategic goals of the census are met, and (3) identify ways to improve the  design of future censuses.  The Bureau does not plan to use statistical  estimates of the population for adjusting census data based on its belief  that the 2000 Census demonstrated “that the science is insufficiently  advanced to allow making statistical adjustment to population counts of a  successful decennial census in which the percentage of error is presumed  to be so small that adjustment would introduce as much or more error than  it was designed to correct.”
section_title: The Top 20 Formula Grant Programs Represented Two Thirds of All Federal Grant Programs
paragraphs: In fiscal year 2004, the federal government administered 1,172 grant  programs, with $460.2 billion in combined obligations.  However, as shown  in table 1, most of these obligations were concentrated in a small number  of grants.  For example, Medicaid was the largest formula grant program,  with federal obligations of $183.2 billion, or nearly 40 percent of all grant  obligations, in fiscal year 2004.  The top 20 grant programs comprised  around two-thirds of all federal grant programs, with $307.9 billion in  obligations for fiscal year 2004 (SSBG is not included in table 1, because  with obligations of $1.7 billion, it is not among the top 20 formula grant  programs).
section_title: Prospective Impact of Statistical Population Estimates on Medicaid and SSBG Allocations
paragraphs: Based on our simulations, recalculating allocations of key programs using  statistical population estimates, states would have shifted less than 0.25  percent of $161.4 billion in Medicaid and SSBG formula grant funding. The  two key programs analyzed—Medicaid and SSBG—together received  federal allocations of $161.4 billion in fiscal year 2004. Federal allocations  for Medicaid (excluding such administrative costs as processing, making  payments to service providers, and monitoring the quality of services to  beneficiaries) were $159.7 billion, by far the highest federal allocation in  fiscal year 2004. Using statistical population estimates to recalculate  federal Medicaid allocations to states, states would have shifted 0.23  percent of $159.7 billion in federal Medicaid funds in fiscal year 2004 and  0.25 percent of $1.7 billion in SSBG funds would have shifted as a result of  the simulations in fiscal year 2005. (Appendix IV contains tables showing  the difference between using estimated and actual population data from  the 1990 and 2000 Censuses for Medicaid and SSBG.)
Because the two programs allocate state funding using different formulas,  funding reallocations for the two programs may produce results that are  different from one another for a particular state.  For example, using the  2000 statistical population estimates, which were lower for Minnesota than  the official census population count, Minnesota’s Medicaid allocation  would have remained the same.  This is because Medicaid allocations are  subject to a floor, and Minnesota was already receiving the minimum  required reimbursement.  However, it would have lost funding under SSBG,  because the statistical population estimates from the 2000 Census, and the  subsequent recalculations, would have reduced funding. In another  example, the District of Columbia allocation would have remained the  same for 2000 under Medicaid, because the District of Columbia receives a  special rate that is higher than its calculated rate, but it would have gained  funding under SSBG because its population, as measured by the 2000  Census, was originally lower than the census population estimates. (For  information on how these formulas are calculated, see app. I.)
subsections: section_title: States Would Have Shifted 0.23 Percent of Medicaid Funds Using Statistical Population Estimates Based on the 2000 Census to Recalculate State Medicaid Allocations
paragraphs: Using statistical population estimates to recalculate federal Medicaid  allocations, states would have shifted 0.23 percent of $159.7 billion of  federal Medicaid funds overall in fiscal year 2004 as a result of the  simulation. If statistical population estimates had been used, of the overall  allocation of $159.7 billion of federal funds, 22 states would have received  more Medicaid funding, 17 states would have received less, while 11 states  and the District of Columbia would have received the same. The gaining  states would have received an additional $208.5 million, and the losing  states would have received $368 million less in funding. Based on our  simulation of the formula funding for Medicaid---Nevada would have gained  1.47 percent in grant funding and Wisconsin would have lost 1.46 percent.  (Appendix IV contains tables showing the difference between using  estimated and actual population data from the 1990 and 2000 Censuses to  recalculate Medicaid allocations.)
Figure 1 shows the state-by-state result—gain or loss--of recalculated  Medicaid grant funding using the statistical population estimates. Most of  the estimated increases in state allocations would have tended to  congregate in the northwestern, southwestern, and southeastern regions of  the country and Hawaii and Alaska. Most of the estimated decreases in  state allocations would have tended to congregate in the northcentral  region of the country. The southeastern and northeastern regions would  have experienced both increases and decreases in funding and all  southeastern states except Florida would have experienced increases.
Figure 2 shows how much (as a percentage) and where Medicaid funding  would have shifted as a result of using statistical population estimates for  recalculating formula grant funding by state. We estimate that 20 states  would have received an increase in allocations from more than 0 to less  than 1 percent, while 2 states would have increased by more than 1 percent.  Conversely, 7 states would have experienced a decrease in allocations of  greater than one to less than 1.5 percent; 10 states’ allocations would have  decreased by more than 0 to less than 1 percent; and 11 states and the  District of Columbia would have experienced no change because the shift  would have fallen below the floor and above the ceiling that are built into  the FMAP formula.
section_title: Statistical Population Estimates from the 2000 Census Would Have Reallocated 0.25 Percent of SSBG Funds Among the States
paragraphs: Using statistical population estimates to recalculate federal SSBG  allocations, 0.25 percent of $1.7 billion in SSBG funds would have shifted in  fiscal year 2005 as a result of the simulation. The total $1.7 billion SSBG  allocation would not have changed, because SSBG receives a fixed annual  appropriation.  In other words, those states receiving additional funds  would have reduced the funds of other states.  In short, 27 states and the  District of Columbia would have gained $4.2 million and 23 states would  have lost a total of $4.2 million. Based on our simulation of the formula  funding for SSBG, Washington, D.C. would have gained 2.05 percent in  grant funding and Minnesota would have lost 1.17 percent. (Appendix IV  contains tables showing the difference between using estimated and actual  population data from the 1990 and 2000 Censuses for SSBG funding.)
Figure 3 shows the state-by-state result—gain or loss—of recalculated  SSBG grant funding using statistical population estimates. Because the  reallocations are based on the same census statistical population estimates  as the Medicaid estimated reallocations, most of the estimated increases in  state allocations would have tended to congregate in the southeastern,  southwestern, and northwestern regions of the country, as they did in our  Medicaid simulation. The estimated decreases would have been grouped in  the northcentral region and several states of the northeastern region of the  country. The northeastern region would also have experienced both  increases and decreases in funding.
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Figure 4 shows how much (as a percentage) and where SSBG funding  would have shifted as a result of using statistical population estimates for  recalculating formula grant funding by state. By recalculating SSBG state  allocations using the statistical population estimates for states based on  2003 Census population numbers, we estimate that 27 states would have  experienced an increase from more than 0 to less than 1 percent; the  District of Columbia would have increased by more than 2 percent; 2 states’  allocations would have decreased by more than one percent; and 21 states’  allocations would have decreased by more than 0 to less than 1 percent.
section_title: Statistical Population Estimates from the 2000 Census Would Have Shifted a Smaller Percentage of Funding Compared to Those from the 1990 Census
paragraphs: For the Medicaid program, recalculating state allocations using statistical  population estimates based on the 2000 Census would have changed the  funding for 39 states in fiscal year 2004.  In particular, 22 states would have  increased their allocations by $208.5 million, 17 states would have  decreased them by $368.0 million, and 11 states and the District of  Columbia would have had no change.  By contrast, recalculating state  allocations using statistical population estimates based on the 1990 Census,  the number of changing states would have remained the same but the  amounts shifting among the states would have changed in fiscal year 1997.   Table 2 presents the comparative information from the two analyses.  The  allocations for the gaining states would have decreased by almost 50  percent, from $402.4 million for the 1990 Census to $208.5 million for the  2000 Census, while the allocations for the losing states would have  increased by 7 percent, from $344.6 million to $368.0 million.  While total  allocations under the Medicaid program increased by over 75 percent from  fiscal year 1997 to fiscal year 2004, the relative or percentage change in  state funding would have decreased in our simulation of recalculations of  state allocations using statistical population estimates.
We have a similar finding for the SSBG program.  Our recalculation of state  allocations would have resulted in a smaller change in allocations when we  compare the results of our recalculation using statistical population  estimates based on the 2000 Census to the results based on the 1990  Census.  The change in funding would have been reduced by half using the  statistical population estimates based on the 2000 Census.  Total SSBG  state allocations decreased by 26 percent between fiscal year 1998 and  fiscal year 2005, and the percentage shift in funding would also have been  reduced, from 0.37 percent to 0.25, using the statistical population  estimates based on the 2000 Census.
In summary, using the statistical population estimates based on the 2000  Census to recalculate Medicaid and SSBG allocations would have resulted  in a smaller shift in program funding than using the statistical population  estimates based on the 1990 Census.  This is because the difference  between the actual and estimated population counts was smaller for the  2000 Census compared to the 1990 Census. As mentioned earlier, the  recalculated allocations are the result of simulations using statistical  population estimates and were done for the purpose of illustrating the  sensitivity of these two formula grant programs to alternative population  estimates.
As agreed with your offices, unless you publicly announce the contents of  this report earlier, we plan no further distribution until 30 days from its  issuance date. At that time we will send copies of the report to other  interested congressional committees, the Secretary of Commerce, the  Secretary of Health and Human Services, the Director of the U.S. Census  Bureau, and the Director of the Office of Management and Budget. We will  make copies available to others upon request. This report will also be  available at no charge on GAO’s Web site at http://www.gao.gov.
If you or your staff have any questions concerning this report, please  contact me on (202) 512-6806 or by email at farrellb@gao.gov. GAO staff  who made major contributions to this report are listed in appendix VI.
Contact points for our Offices of Congressional Relations and Public  Affairs may be found on the last page of this report.
section_title: Scope and Methodology
paragraphs: As agreed with your offices, we identified (1) the top 20 formula grant  programs based on the amount of funds targeted by any means, and (2)  how much money would have been allocated using census data for certain  formula grant programs, and the prospective impact of using estimated  population counts from the 1990 and 2000 Censuses to recalculate state  allocations for these grant programs. We use the term “allocation” to  include Department of Health and Human Services (HHS) reimbursement  to states of Medicaid expenditures subject to the Federal Medical  Assistance Percentage (FMAP) formula and Social Services Block Grant  (SSBG) state allotments.  We use the term “statistical population estimates”  to refer to the results of the coverage measurement programs that the  Census Bureau (Bureau) conducted following the 1990 and 2000 Censuses.
To identify the top 20 formula grant programs based on the amount of  funds targeted by any means, we used fiscal year 2004 grants expenditure  and obligations data from the Bureau’s Consolidated Federal Funds Report  (CFFR), the most recent data available at the time of our review.  While we  recently reported on inaccuracies in the CFFR, we determined that the  CFFR is adequate for purposes of identifying the top 20 federal formula  grant programs because it shows the overall magnitude of these programs.  Because the CFFR lists direct expenditures or obligations, the amount  shown for Medicaid in table 1 is different from the Medicaid allocations  shown in the rest of the report, where we use state expenditure data  subject to the FMAP formula, which exclude administrative costs.  Administrative costs for which Medicaid reimburses states include nine  broad tasks: (1) inform potentially eligible individuals and enroll those who  are eligible, (2) determine what benefits it will cover in what settings, (3)  determine how much it will pay for the benefits it covers and from whom to  buy those services, (4) set standards for providers and managed care plans  from which it will buy covered benefits and contract with those who meet  the standards, (5) process and make payments to service providers, (6)  monitor the quality of services to beneficiaries, (7) ensure that state and  federal health care funds are not spent improperly or fraudulently, (8) have  a process for resolving grievances, and (9) collect and report information  for effective administration and program accountability.
To determine how much money was allocated using census population  counts for Medicaid and SSBG, we obtained population and income data  from the Department of Commerce (Commerce).  Additionally, we  obtained Medicaid expenditures, SSBG allocations, and certain other  information from HHS.  Table 3 displays the census population counts for  1990 and 2000 and their statistical estimates. We obtained state per capita  income—the ratio of personal income to population—for 2000, 2001, and  2002 from Commerce and replicated the actual FMAP for 2005 using fiscal  year 2004 state expenditure data. For the SSBG state allocation formula, we  obtained state population estimates for 2003 and replicated the SSBG  allocations for 2005. The official 1990 Census population counts and  statistical population estimates from the 1990 coverage measurement  program known as the Post-Enumeration Survey (PES) come from our  earlier report.
To analyze the prospective impact of estimated population counts on the  money allocated to the states through these two grant programs, we  recalculated the state allocations using statistical estimates of the  population that were developed for the 1990 and 2000 Censuses in lieu of  the actual census numbers.  We used the population estimates, which are  based on the 2000 Census counts, and then adjusted these population  estimates by the difference between the 2000 official population counts and  the statistical estimates of the population (A.C.E.).  Our procedure to  simulate the formula allocations using adjusted counts was to (a) obtain  the population estimates used to calculate the Medicaid FMAP and SSBG  allocations, (b) subtract the A.C.E. population estimates from the official  2000 Census population counts, and (c) add the difference from (b) to the  population estimates from (a). We included the 50 states and the District of  Columbia in our calculations, but did not include the territories: American  Samoa, Guam, the Northern Mariana Islands, Puerto Rico, and the Virgin  Islands, because their allocations use formulas that are different from  those used by the 50 states we analyzed.
To verify our approach, we spoke with Department of Commerce and  Department of Health and Human Services officials who administer these  grant programs about the procedures they use to calculate the formula  funding amounts.  Importantly, our analyses of Medicaid and SSBG are  simulations and were conducted only to illustrate the sensitivity of these  two grant programs to alternative population estimates. Both the Census  Bureau and GAO deem the 1990 and 2000 statistical population estimates  as unreliable and they should not be used for any purposes that legally  require data from the decennial census.
Medicaid is an entitlement program. The federal share of total Medicaid  program costs is determined using the FMAP, a statutory formula that  calculates the portion of each state’s Medicaid expenditures that the  federal government will pay. Our Medicaid simulation uses the fiscal year  2005 FMAP, which applies 2001 through 2002 personal income and  population data, and fiscal year 2004 expenditure data. The formula  calculates the federal matching rate for each state on the basis of its per  capita income (PCI) in relation to national PCI. States with a low PCI  receive a higher federal matching rate, and states with a high PCI receive a  lower rate. If applying the formula renders a state’s reimbursement less  than 50 percent of its allowable expenditures, the state is still entitled to be  reimbursed for a minimum of 50 percent—or “floor”—of what it spent.  Conversely, a state cannot be reimbursed for more than 83 percent of  allowable expenditures—the “ceiling.” Thus, if one used the A.C.E.  statistical estimates to recalculate state Medicaid allocations, states’  reimbursements for allowable expenditures would not be less than 50  percent, the “floor,” or more than the “ceiling.” Our calculations do not  include administrative costs, because they are not subject to the FMAP  formula. The Medicaid data we used in our calculations include the Indian  Health and the Family Planning programs, which are not subject to the  allocation formula. Agency officials told us that the expenditures for these  two programs are so small in relation to the total Medicaid expenditures  that they do not materially affect the calculations of state allocations  subject to the FMAP formula.
The SSBG federal grant is for a fixed amount determined in an annual  appropriation, and its formula is set up so that an increase in funding to any  state is offset by a decrease to others. To estimate the prospective impact  of using statistical population estimates to recalculate allocations for  SSBG, we used 2003 population data adjusted by the difference between  the 2000 Census and the A.C.E. estimates and fiscal year 2005 allocations to  the states for our analysis—the data HHS used in its fiscal year 2005 grant  allocations to the states. Unlike Medicaid, SSBG includes administrative  costs in its population-based formula to calculate state allocations.
section_title: Medicaid
paragraphs: Program Objectives: To provide financial assistance to states for  payment of medical care on behalf of cash assistance recipients, children,  pregnant women, and the aged who meet income and resource  requirements and other categorically eligible groups.
Federal Agency: Department of Health and Human Services (HHS),  Centers for Medicare & Medicaid Services.
Fiscal Year 2004 Obligations: $183.2 billion. (Federal allocations  excluding administrative costs: $159.7 billion.)
Formula Calculation: Eligible medical expenses are reimbursed based on  the per capita income of the state. The federal reimbursement rate, known  as the Federal Medical Assistance Percentage (FMAP), ranges from a  minimum of 50 percent to a maximum of 83 percent. Most administrative  expenses are reimbursed at a flat rate of 50 percent but may be as high as  100 percent as is the case with immigration status verification.
Formula Constraints: No state may receive a matching percentage below  50 percent or in excess of 83 percent.
FMAP = Federal Medical Assistance Percentage.
PCI = Per capita personal income.
PI = Personal income.
Pop = State population.
Pop: Department of Commerce, Bureau of Economic Analysis, and Census  Bureau.
Amount Shifted: $368 million, or a 0.23 percent overall loss of the total  $159.7 billion allocated among the states as a result of the simulation.
Comments: Allotment amounts were calculated for fiscal year 2004, the  latest year for which data were available. Total federal allotment includes  some amounts for Family Planning and Indian Health Services that are not  subject to the FMAP. We use the term “allocation” to include HHS  reimbursement to states of Medicaid expenditures subject to the federal  FMAP formula (net of administrative costs).
section_title: Social Services Block Grant
paragraphs: Program Objectives: To enable states to provide social services directed  toward the following goals: (1) reducing dependency; (2) promoting self- sufficiency; (3) preventing neglect, abuse, or exploitation of children and  adults; (4) preventing or reducing inappropriate institutional care; and (5)  securing admission or referral for institutional care when other forms of  care are not appropriate.
Federal Agency: Department of Health and Human Services,  Administration for Children and Families.
Fiscal Year 2004 Obligations: $1.7 billion.
Formula Calculation: State funding is allocated in proportion to each  state’s share of the national population.
Formula Constraints: None.
Amt = Funds available for allocation to states.
Pop = A state’s population count.
Amt: Department of Health and Human Services, Administration for  Children and Families.
Pop: Department of Commerce, Census Bureau.
Amount Shifted: $4.2 million, or 0.25 percent of the total $1.7 billion  allocated. The Social Services Block Grant (SSBG) federal grant is for a  fixed amount determined in an annual appropriation; an increase in  funding to any state is offset by a decrease in others.
Comment: We use the term “allocation” to include SSBG state allotments.  SSBG state allotments are based on each state’s population in proportion to  the total U.S. population.
section_title: GAO Contact and Acknowledgments
subsections: section_title: GAO Contact
section_title: Acknowledgments
paragraphs: In addition to the individual named above, Robert Goldenkoff, Assistant  Director, as well as Faisal Amin, Robert Dinkelmeyer, Carlos Diz, Gregory  Dybalski, Amy Friedlander, and Sonya Phillips made key contributions to  this report.