## Medicaid Empire: Why New York Spends so much on Health Care for the Poor and Near Poor and How the System Can Be Reformed

No. 284
Monday, March 20, 2006
by John C. Goodman, Michael Bond, Devon M. Herrick, Joe Barnett, and Pamela Villarreal

## Appendix I: The Federal Medicaid Matching Formula

A formula called FMAP (Federal Medicaid Assistance Percentage or the “federal match”) is used to determine the percentage the federal government contributes to individual state programs. The FMAP formula is not unique to Medicaid. It was established in 1946 and used to fund hospital construction under the Hill-Burton Act. FMAP was later used to determine benefi ts under Social Security’s Medical Assistance to the Aged program in 1958. At that time, the federal matching rate was narrower, ranging from a “floor” of 50 percent to a “ceiling” of 65 percent.1 In 1960, amendments to the Social Security Act raised the matching-rate ceiling to 80 percent. Once Medicaid was established in 1965, the formula was again revised, with a new maximum rate of 83 percent. The term “matching” is misleading, however. We would normally think of matching in terms of the government paying anywhere from 50 cents to 83 cents (depending on a state’s matching rate) for every dollar the state spends. However, that is not the case. Consider New York, with a matching rate of 65 percent. Given one dollar of Medicaid expenditures, New York pays 35 cents of that dollar, while the federal government pays the other half. Therefore, the federal government does not actually contribute 65 cents for each New York dollar of Medicaid; rather it contributes \$1.86 for every dollar that New York spends. Similarly, if a state has a matching rate of 83 percent, the federal government contributes about \$4.88 for every dollar the state spends on Medicaid.

The current formula is2

The first term on the right-hand side of the equation, 0.45, is called the multiplier. The second term is the ratio of a state’s per capita income (state PCI) to the overall United States per capita income (U.S. PCI), and is known as relative per capita income. This term is intended to represent a state’s resources as well as its general poverty rate. When the ratio of the state’s PCI to the U.S. PCI is multiplied by .45 and subtracted from one, the resulting value determines the federal government’s matching rate for that state. For simplicity, suppose a state's PCI is the same as the U.S. PCI. The 0.45 means that the federal matching rate for that state would 55 percent.3 Notice, however, that the per capita ratio term is squared. This is done to magnify the differences among states in terms of resources and people in poverty. Additionally, the federal matching rate has a “floor” - it does not fall below 50 percent. (But recall that the federal government actually pays 65 percent of the cost, due to the enhanced match.) For example, suppose a state’s PCI ratio is 1.10, meaning their PCI is 10 percent higher than the U.S. average. Technically, their matching rate should be about 45 percent, but due to the fl oor, they receive 50 percent.4 On the other hand, a state with a PCI ratio of .95 (indicating only 95 percent of the U.S. average) receives a matching rate of 59 percent.

In determining a state’s PCI, the U.S. Department of Health and Human Services (HHS) uses the state’s average PCI over three years, beginning with the most recently available annual data, which is usually the rate in the fi scal year before the matching rate is effective.5

Critics of the formula have several arguments against the FMAP. First, the formula was ostensibly designed to narrow disparities among wealthy and poorer states by giving poor states a higher federal matching rate. But the 50 percent “floor” gives high-income states such as New York money that they may not need. It therefore widens the gap between rich and poor states, something that the formula was intended to remedy.

Moreover, critics argue that the PCI measurement has its own problems. First, using a threeyear- average to determine a state’s PCI is outdated since the most recent year used is the end of the fi scal year before the year that benefi ts are allotted, as well as the two years prior; therefore, the PCI does not refl ect a state’s current economic conditions. Second, they note that PCI is a poor measure of a state’s poverty population. It does not completely measure a state’s resources, nor does it indicate what percentage of the population is poverty-level. As a result, policymakers have debated using other measures, such as a state’s taxable total resources (TTR) to determine a state’s ability to fund Medicaid.6

1. Kathryn G. Allen; Memorandum to Senator Daniel Patrick Moynihan, "Medicaid Formula: Effects of Proposed Formula on Federal Shares of State Spending." U.S. Government Accountability Office, GAO/HEHS-99-29R, February 19, 1999; pages 1 – 30.
2. "Medicaid Formula: Differences in Funding Ability among States Often Are Widened," U.S. Government Accountability Offi ce, Report No. GAO-03-620, August 11, 2003.
3. For a more detailed description of how the Medicaid federal match is calculated see "Medicaid Formula: Differences in Funding Ability among States Often Are Widened," U.S. Government Accountability Offi ce, Report No. GAO-03-620, August 11, 2003, Appendix I: Legislative History and Description of the Matching Formula.
4. States also received an enhancement of the matching rate, which is 30 percent of the difference between 100 and the calculated matching rate or the floor rate.
5. "Medicaid Formula: Differences in Funding Ability Among States Often Are Widened."
6. For a description and analysis of the TTR, see "Medicaid Formula Proposal (pdf)," U.S. Government Accountability Office, Health, Education and Human Services Division, Report No. GAO/HEHS-99-29R.