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.” 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). 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.) 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. 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. Wyo. Mich. R.I. Conn. Nebr. Pa. N.J. Ill. Ind. Del. Colo. Kans. Mo. W.Va. Va. Md. Ky. D.C. N.C. Okla. Tenn. N.Mex. Ark. S.C. Miss. Ala. Ga. Tex. La. Fla. 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. 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. 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. 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). 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. 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.

Summary: 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. 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.