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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
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