Congress appropriates federal assistance grant funds to executive branch agencies that then use funding formulas to distribute federal assistance to states or local entities. These funding formulas are typically established through statute and expressed as one or more equations containing one or more variables. Executive branch agencies also use formulas to determine the amount of federal matching grants for jointly funded federal assistance programs where the amount of the federal match varies among the states based upon the formula calculation. For example, Medicaid’s Federal Matching Assistance Percentage (FMAP) is determined through a statutory formula based on each state’s per capita income relative to U.S. per capita income. Various statutory or administrative provisions can also modify the amount that would otherwise be determined under the formula. These provisions may be included to avoid disruptions that could be caused by year-to-year changes in funding, to cover fixed costs of a program, or for other reasons. Congress can use formula grants to target funds to achieve federal assistance program objectives by including specific variables in the formulas that relate to the programs’ objectives. For example, for a program intended to serve a specific segment of the population, the formula may contain variables that measure or identify the subset of the population. Therefore, the formula for a program designed to provide services for children in low income areas may contain variables that identify the total number of children living in poverty in a certain area. Historically, many formulas have relied at least in part on decennial census and related data as a source of these variables. The decennial census collects, among other things, information on whether a residence is owned or rented, as well as respondents’ sex, age, and race. To update decennial population counts, the Bureau’s Population Estimates Program produces population estimates for each year following the last published decennial census, as well as for past decennials, using administrative records such as birth and death certificates and federal tax returns. Census-related data stem from the decennial census and the Bureau’s population estimates and include (1) surveys with statistical samples designed to represent the entire population using data from the decennial census or its annual updates, and (2) statistics derived from decennial census data, its annual updates, or census-related surveys. Two of the census-related surveys produced by the Bureau include the American Community Survey (ACS) and the Current Population Survey (CPS). The ACS is an annual survey of about 3 million housing units that collects information about people and housing, including information previously collected during the decennial census. The CPS is a monthly survey of about 50,000 households conducted by the Census Bureau for the Bureau of Labor Statistics and provides data on the labor force characteristics of the U.S. population. Supplemental questions also produce estimates on a variety of topics including school enrollment, income, previous work experience, health, employee benefits, and work schedules. Federal agencies use census data, annual updates, and surveys based on these data to produce other statistics used in federal assistance grant formulas. For example, the Bureau of Economic Analysis produces per capita income data—a derivative of decennial census data—by dividing personal income by population obtained from census population estimates. Per capita income is used to calculate Medicaid’s FMAP. Another derivative is Fair Market Rent (FMR) that the Department of Housing and Urban Development calculates and uses to determine payment standard amounts for the Section 8 Housing Choice Voucher Program. The FMR for a particular area is based on decennial census data or other surveys such as the ACS for the years between censuses. Our analysis showed that each of the 10 largest federal assistance programs in fiscal year 2008 and 2009 relied at least in part on decennial census and related data to determine funding. For fiscal year 2008, this totaled about $334.9 billion, representing about 73 percent of total federal assistance. We considered funding based on decennial census and related data if any part of the funding formula or eligibility requirements relied on these data sources. Table 1 shows the fiscal year 2008 obligations for the 10 largest federal assistance programs in that year. For fiscal year 2009, the estimated obligations of the 10 largest federal assistance programs totaled about $478.3 billion, representing about 84 percent of total federal assistance. This amount included about $122.7 billion funded by the Recovery Act and about $355.6 billion funded by other means. The 10 largest federal assistance programs in fiscal year 2009 included a new program added by the Recovery Act—the State Fiscal Stabilization Fund. Table 2 shows the fiscal year 2009 estimated obligations for the 10 largest federal assistance programs and how much the Recovery Act increased that amount. Decennial census and related data play an important role in funding for the largest federal assistance programs. However, changes in population do not necessarily result in an increase or decrease in funding. Based on our prior work and related research on formula grants, we identified some of the factors that could affect the role of population grant formulas. We found that factors related to the formula equation(s) and those that modify the amount that a state or local entity would otherwise receive under the formula could affect the role of population in grant funding formulas. Further, the extent to which one particular factor can affect the role of population in grant funding varied across programs. Although at least one factor that could affect the role of population in grant funding formulas was present in each program in our review, the number and combination of factors varied across programs. To illustrate how these factors can be used in formula grant funding, we selected examples from the federal assistance programs in our review. The examples presented below are illustrative and do not necessarily indicate the relative importance of a factor compared to the other factors present. All of the programs in our review included one or more grants with formulas containing variables other than total population. Obviously, absent other factors, funding based on these formulas will be affected less by changes in population than those that rely solely on total population. The State Fiscal Stabilization Fund formula is based on total population and a subset of total population—states’ shares of individuals aged 5 to 24 relative to total population. The Federal Transit Program grants for urbanized areas with populations of 200,000 are based on total population and variables related to the level of transit service provided. TANF supplemental grants are awarded based on a formula with multiple variables. According to the Department of Health and Human Services’s Administration of Children and Families (ACF), which administers the program, supplemental grants are awarded to states with exceptionally high population growth in the early 1990s, historic welfare grants per poor person lower than 35 percent of the national average, or a combination of above average population growth and below average historic welfare grants per poor person. Medicaid’s FMAP is based on a 3-year average of a state’s per capita income relative to U.S. per capita income with per capita income defined as personal income divided by total population. The FMAP is affected by both changes in population and personal income. Because changes in population and personal income are not correlated, the affect of a population change may be diminished or increased by a change in personal income. Finally, because per capita is squared—that is, multiplied by itself—in the formula, the affect of a population change may be greater than if per capita income were not squared. In addition to the number of variables, the number of equations can also affect the role of population in grant funding formulas. Under CDBG, metropolitan counties and cites are eligible for the greater of the amounts calculated under two different equations. The variables in the first equation are population, extent of poverty, and extent of overcrowded housing. The variables in the second equation are population growth lag, extent of poverty, and age of housing. The use of the dual equation structure and the variables other than population in each equation reduce the effect of population changes on grant funding. Some formulas also have base amounts that are set at the amount of funding in a specified prior year and the remainder for funding is calculated according to a formula. For programs with set base amounts, only a portion of the funding might be affected by a change in population. Because appropriation amounts can change from year to year, the base amount portion of the grant will represent less of the total grant amount if appropriations increase, making total grant funding affected more by a change in population. When appropriations decrease, the share of the overall funding subject to the formula is lower, lessening the effect of a change in population on total funding. Some programs we reviewed contained such base amounts in their funding formula. Under IDEA Part B, generally each state first receives the same amount it received for fiscal year 1999 for the program for children aged 3 through 21, and, for the program for children aged 3 through 5, the amount the state received in fiscal year 1997. For the remainder of the state’s funding in a given year, (1) 85 percent is based on the state’s share of the 3 through 21 year old population for the school-aged program, and the 3 through 5 year old population for the preschool program and (2) 15 percent is based on the state’s share of those children living in poverty. In another example, the Head Start program guarantees the same base amount as in the prior year. The remainder of the funding is allocated to cost of living increases and Indian and migrant and seasonal Head Start programs depending upon the amount remaining. According to ACF, which administers Head Start, when the increase in appropriation is large enough to allow for expansion of Head Start, those funds are calculated based on the relative share of children aged 3 and 4 living in poverty in each state. Some factors modify the amount that a state would otherwise receive under the funding formula and could affect the role of population in grant funding formulas. The factors include the following: (1) hold harmless provisions and caps; (2) small state minimums; and (3) funding floors and ceilings.