Federal Formula Grant Program Elements:
California Implications
February 1999 Update

This report offers a general review of primary data elements used to determine federal formula grant allocations by state.

Formula Factors
Some federal programs distribute funding according to simple census figures for all or certain persons, while other formulas employ more complex factors.  Following is a brief discussion of some of the most common factors employed when distributing federal funding via formula and how the factors operate, specifically with respect to California.
Population -- As the crudest benchmark for examining alternate formula allocations and federal funds distributions generally, California's population currently represents approximately 12.1% of the U.S. population.  A few formulas distribute funds based purely on overall state population, such as the Social Services Block Grant (SSBG), though most are somewhat more complex.
Poverty -- Poverty rates and numbers of persons living in poverty are used to calculate distributions for a number of federal programs. In 1996-97, 16.8% of Californians were below the poverty line -- well above the national rate of 13.7% -- giving California the 10th highest poverty rate among states.  In 1996, California housed 5.5 million or 15% of the nation's 36.5 million persons in poverty.  California's above-average poverty rate in the 1990s is a pronounced shift from the state's below-average rates during the 1980s, and experts predict that while the state may settle closer to the national average, poverty rates will exceed those of other states for some time to come.
Because poverty is calculated as a particular level, some formulas are designed to calculate eligible populations precisely at the official poverty level, or they may use a specified percentage of that level (say 125% or 200% of poverty).  According the 1990 Census, California's share of persons living at each of these percentage levels is similar to its share of persons below the actual poverty line.
Child Poverty  -- The number of children in poverty is an important factor for distributing funding under the $7 billion Title I federal education grant, the largest federal education grant program and the fourth largest formula grant of any kind.  California is now home to 1.36 million poor children, 14.65 percent of the nation's total. Yet last year California schools received just 11.4 percent of funds from Title I, which is theory focused on poor children.  The Title I shortfall is attributable to a number of factors, one of which is the continued use of outdated poverty data.  While national and state-level poverty figures have been estimated every year for decades, sub-state poverty figures were until recently are only updated decennially (every 10 years), thereby making the figures rapidly outdated, and slowing the appropriate shift of federal dollars from slow-growth to high-growth states and localities.  In 1994, thanks in large part to the California Congressional delegation, Congress directed the Census Bureau to produce poverty data at least every two years. The Bureau prepared the first set of figures in late 1996 and a second set in January 1999.  The Secretaries of Commerce and Education approved the first set of updated data as accurate and required that they be used to allocate Title I funds, and the technically-proven methodology is likely to pass scientific muster for future allocations.
Unfortunately, in November 1997, a 100% "special hold harmless" provision was inserted stating that no school district in 1998 could receive less than it received in the prior year, effectively preventing school districts in California and other growth states from receiving the further gains to which they are entitled.  Rather than having funds follow poor children, the hold harmless kept funding levels static, regardless of where needs were greatest or which areas had high concentrations of target eligible children.  That "special hold harmless" continues to be applied, meaning that California receives its fair share only of extra Title I spending, rather than of all spending.
Per Capita Income -- Some formulas use a measure of "fiscal capacity," or the ability of a state or locality to raise revenues internally through state or local taxes, in an attempt to adjust funding toward poorer states away from richer ones.  Per capita income is commonly used as a measure -- an inadequate one at that, as will be explained below.  For example, a state's federal matching level for Medicaid is based on that state's per capita income compared to the national average.  While California's relative wealth has declined somewhat during the last several years, California still has the 13th highest per capita income among states in 1997 (down from 8th in 1990 and 3rd in 1980).
Use of per capita income figures in determining the Federal Medicaid Assistance Percentage (FMAP) to reimburse states for Medicaid spending disadvantages California, as the formula reimburses poorer states at higher rates than richer ones.  Per capita income usage also reduces California's share of vocational education program funding.
Per capita income is an imperfect formula factor at best.  According to the General Accounting Office, PCI was first used in the 1950s as an indicator of a state's ability to finance programs as well as of a state's poverty level, assuming that low-income states would have higher poverty rates.  Since that time, a formal poverty definition has been created, and better measures of fiscal capacity now exist.  It is important to note that California has a high per capita income, but also a high poverty rate.  Thus, formulas originally drafted to help poor people by assuming they reside in low-income states actually shortchange California's large poor population and drain the treasuries state and local governments which attempt to backfill for the shortfall.
An alternative fiscal capacity factor would be to use a state's taxable resources. A 1990 GAO study (using 1989 data) determined that California's per capita taxable resources were about 10% above the national average -- so use of a fiscal capacity factor would produce results roughly similar to use of per capita income.
Fiscal Effort -- Some programs incorporate in their formulas a factor to represent a state's or locality's sacrifice made or effort exerted to support the program's goals.  For example, a factor might reward a state for high per-eligible revenues, thereby creating an incentive for a state to raise taxes to pay for the federal goal in question.  A typical factor might be a ratio of the state's revenue in a certain category to that state's per capita income.
Cost Factors -- An alternative to an income factors (which tend to help lower-income states) would be to recognize the higher cost of providing services in one state versus another.  (See also the discussion of cost of living factors below.)  The problem is that some purported cost factors do not accurately reflect differentials in costs.
One such example can be found in the Title I education program, discussed above, which is the fourth largest federal formula grant.  While technically neither an effort factor nor a cost factor, the "state-per-pupil-expenditure" factor was drafted to be a rough proxy for both.  The use of this factor works strongly against California in funding distribution.  California has one of the highest average class sizes among states, and thus has a very low per-pupil expenditure, thereby suppressing Title I funding.  During the 103rd Congress' revision of Title I, California advocates suggested use of a more accurate proxy for the cost of providing education services -- average state teacher salaries.  California ranks 9th among states in average salaries for teachers.
Cost of Living -- While the technique has not been used, relative income figures could actually benefit California if a formula were to compensate for the higher cost of living in one state or area versus another. S. 165, introduced by Senators from high-cost states in the Northeast, would require that funding allocations using sub-state poverty data be adjusted "to account for differences in the cost of living in the areas."  California's share of funding would likely rise were the bill to be enacted and implemented. However, cost of living / consumer price index figures are not presently collected on a state-by-state basis by the Bureau of Labor Statistics.  BLS produces a CPI figure for the U.S. and for 29 major metropolitan areas.  The CPI for the three California metro areas listed are above the national city average, thanks in large part to our high housing prices, and thus a state-level CPI, should one be produced, would likely show an above average CPI for the state.
Employment and Unemployment -- The Department of Labor calculates unemployment rates monthly.  Unemployment rates can fluctuate significantly from month to month.  For example, California's unemployment rate fell from 7.7% in March 1996 to 7.5% in April 1996 and 7.2% in May 1996.  These figures contrast with national rates of 5.6% in March, 5.4% in April and 5.6% in May of that year.  Until May of 1996, California's rate had exceeded the national rate by at least 2 points nearly every month for three straight years.  Two and a half years later, by late 1998, these fluctuations and the state-national discrepancy had declined substantially.  From October to December of 1998, California's rate was relatively stable at 5.9%, while the national rate averaged 4.4%.  The unemployment rate is used to calculate grants under Workforce Investment Act of 1998 (formerly the Job Training Partnership Act), which is based 2/3 on the number of unemployed individuals in a state and 1/3 on the number of poor persons.
Urban vs. Rural Populations -- Many federal transportation/highway and agriculture dollars are allocated according to urban versus rural populations.  California's population is much more concentrated in urban areas than the national average.  In 1996, 97% of California's residents lived in what the Census Bureau defined as a metropolitan area, compared to 80% nationwide.
Age-Range Populations -- Some programs are based on populations of certain ages (such as school-age population or residents over age 65).  California has a high proportion of school-age and younger children compared to the nation at large.  A particularly high and fast-growing concentration is in the younger age ranges, where enrollment in grades K-8 has grown 11.7% compared to only 8.2% nationwide --  among the fastest states.  In contrast, 11% of Californians in 1997 were age 65 or older, compared to a 12.7% national average.  This level ranked California 45th among the states.
Number of Immigrants -- California is home to as many as 40% of the nation's legal immigrants, according to the Census Bureau.  Any formula which accounts for immigrants strongly benefits California.  For example, California received more than half of U.S. allocations under the recently-expired State Legalization Impact Assistance Grants (SLIAG) program.  However, because immigrants tend to be concentrated in relatively few states, it may be difficult to build a broad base of support for inclusion of immigrant factors in formulas.  As a very rough proxy for some formulas, such as in education, it may be appropriate to use the Census Bureau's calculations of households in which a language other than English is spoken.  In 1990, California was home to 6.46 million (or approximately one-third) of the nation's 19.77 million foreign-born persons.
The Immigration and Naturalization Service estimates that 43% of the nation's undocumented immigrants reside in California, though precise figures are difficult to pinpoint.  The State Criminal Alien Assistance Program (SCAAP) reimburses states for the costs of incarcerating undocumented felons, on the theory that their presence in the U.S. is a federal responsibility.  California received nearly half of the $585 million appropriated last year, though less than half of the state's costs are reimbursed.
Percent of Population Receiving Benefits -- On occasion, one program's benefit levels will be tied to the number of individuals receiving or eligible for another.  Thus, it can be helpful to track the share of funds.  For example, while nationwide 4.3% of the nation's 1993 population received AFDC payments, 7.8% of Californians, or 2.5 million people, received benefits.  Thus, California accounted for 21.9% of federal welfare recipients in 1996.  For Supplemental Security Income or SSI, California's 1 million recipients account for 15.8% of the national total.  California ranks second highest in percentage of persons availing themselves of these assistance payments.  In contrast, 12.5% of Californians receive Social Security payments compared to 16% nationwide -- ranking our state 48th of 50.
Crime Rates -- Crime rates are sometimes used to distribute formula grant programs from the Department of Justice.  California's crime rates tend to exceed the national average.  In 1996, California had the fifth highest violent crime rate among the states, at 863 per 100,000 persons, compared to 634 per 100,000 nationwide.  Crime appears to be trending downward nationwide, and particularly so in California.
Transportation Factors -- The federal aid highway program and other surface transportation programs reauthorized in 1998 as the Transportation Efficiency Act for the 21st Century (TEA-21) employs an array of transportation related factors for allocating funds.  Highway funds are allocated according states' road and highway length and usage, and diesel fuel usage (in an attempt to account for freight traffic), with a small factor to help states with small populations relative to usage.  California receives just over 9% of highway funds based on these factors, whereas mass transit, based in part on urbanization of population, has recently returned as much as 14% to the state.
Other Factors -- Several factors have been introduced in a handful of laws which work against California.  Among these programs are the Low Income Home Energy Assistance Program which favors "heating days" over "cooling days" and skews funding toward colder northeastern states away from warmer southwestern states.
One notorious formula, that for the Community Development Block Grant under the Department of Housing and Urban Development allocates funds in part based on the stock of "pre-1940 housing," which naturally tends to favor older Northeastern and Midwestern states over the South, the West, and California.  However, an alternative calculation method added to the program emphasizes poverty and overcrowding, thus resulting in California receiving 16% of funds at last count.
California has the second lowest smoking rate among states (just 15.5% of Californians smoke tobacco products, compared to about 25% nationwide), and its taxpayers thus would be less impacted by proposals to boost cigarette taxes than most of the rest of the nation..
Census Data vs. Reported Counts  -- Most formula distributions are based on objective data provided by the Census Bureau or other unbiased sources.  However, some funds are distributed based in whole or in part on counts of eligible individuals reported to the federal government by the entities who will ultimately receive the funds.  Such situations can sometimes lead to charges of abuse of the system.  For example, when Congress considered reauthorizing the Individuals with Disabilities Education Act (IDEA) in 1996, the House Committee proposed to replace the existing formula, whereby states report the number of handicapped children they serve and receive funds according to that count, with a formula based simply on state-level census figures for population age 3-21.  The shift to census figures would have raised California's share of IDEA funds from 10% to 12%.  (The reauthorization process was not completed.)

Formula Grant Program Special Provisions
A number of specific factors are commonly contained in or added to federal formulas to alter the distribution.  Many work to the detriment of California.  A few examples follow.
Phase-In Periods -- Similar to hold harmless provisions (below), phase-in periods are used to delay the impacts of formula changes and new data.  Such phase-ins may appear as an averaging of several periods' data (using a three-year average of per capita income rather than the most current data to distribute Medicaid funding) or as a specified delay (implementing a new formula ½ in one year and ½ in the next).
Hold Harmless provisions -- Hold harmless provisions tend to work against change and for the status quo by ensuring that a state (or other jurisdiction's) allocation will not decline at all or by more than a specified percentage in any given year.  Historically, hold harmless provisions have been used to prop up funds for slow-growth states which should otherwise decline and prevent proper growth for fast-growing states such as California.  A hold harmless provision might state, for example, that all funding up to the current year's level shall be distributed under the old formula, and only money above that level shall be distributed under the new formula.  While the relative rate of growth of California's population versus that of other states has slowed considerably in recent years, California population change is likely to be above average for the foreseeable future.  California's population is expected to grow from 12.1% of the U.S. population in 1995, to 13.7% by 2010.  Hold harmless provisions are thus likely to continue to work against California's interests.  A detailed discussion of one particularly egregious hold harmless application is discussed under the child poverty heading above.
Small-State Minimums -- Many formulas include minimum floor levels of allocations to states, counties, territories, or other jurisdictional levels.  These naturally and rather blatantly work to shift funding away from larger states and toward smaller ones.
Growth Caps --  Limiting the amount that benefits, eligible populations, or other factors may grow in any given period work against faster-growing regions in favor of slower-growing and declining regions.  However, regions can experience growth in some factors at the same time that others are stable or declining.  The number of unemployed persons may decline as population growth accelerates, for example, or the school age population can be inversely proportional to the population over age 65.  In addition, a growth cap which limits overall growth in U.S. spending on a given program tends to be preferable for growing states such as California to a growth cap placed on each individual state's or jurisdiction's expenditures.
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