Why Average Income Isn’t A Good Way to Distribute Federal Medicaid Funds to States
Instead of equalizing Medicaid resources across the country, the current funding formula often exacerbates disparities
Medicaid, the largest health insurer in the U.S., is financed jointly by the federal government and the states. Overall, of the $728 billion in total Medicaid spending in 2021, states paid 31 percent and the federal government paid 69 percent. Each state’s share is primarily determined by the Federal Medical Assistance Percentage (FMAP), based on a formula devised alongside the Medicaid program in 1965. Things haven’t gone according to plan.
The FMAP formula, shown in Figure 1, is based on a single measure: average personal income. The fundamental effect of the formula is to transfer more responsibility for financing Medicaid to the federal government in states with lower average personal incomes relative to the national average. Conversely, states with higher average personal incomes are required to contribute more of their own budgets to support their Medicaid program.
Figure 1: The FMAP Formula
The FMAP formula was an attempt to account for the fact that states vary widely in their ability to meet the health care needs of their most vulnerable residents with state funds. By indexing federal assistance for Medicaid to a measure of economic prosperity (albeit crude), Congress intended to establish a basic health care safety net throughout the nation. In practice, the FMAP formula often thwarts this objective, widening differences in states’ abilities to fund Medicaid services.
That’s because a state’s average income is only loosely related to the health needs or size of its low-income population and its ability to fund its own social assistance programs.
Personal income, as defined by the Bureau of Economic Analysis, the federal agency that provides the data used to calculate FMAPs, includes wages, rents and interest income received by a state’s residents, but it ignores other sources of income potentially subject to state taxation, such as corporate income and capital gains produced within the state but not received by state residents. As a result, the FMAP formula understates the resources of energy-exporting states like Alaska and Wyoming. A better measure to capture state fiscal capacity would be total taxable resources (TTR), which provides a fuller accounting of what states could feasibly spend on Medicaid.
Average income also tracks poorly with the level of need of a state’s population. For example, Nevada and Maine report nearly identical average incomes and, consequently, receive almost identical FMAPs. Yet by many other measures, Nevada ought to receive more federal Medicaid assistance than Maine: Nevada’s poverty rate is 25% higher than Maine’s, its diabetes prevalence is 10% higher than Maine’s, and its proportion of adults at the bottom of the health scale is 13% higher than Maine’s.
Other examples abound of states receiving the same level of federal aid despite large differences on other relevant dimensions. Florida receives the same FMAP as Wisconsin, despite having (adjusted for population) 22% more poverty, 42% more diabetes, and 25% more adults at the bottom of the health scale.
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The point isn’t that the rate of poverty or diabetes prevalence are better measures for distributing Medicaid funding. Every measure has strengths and weaknesses, capturing some useful state characteristics and leaving some out. But in combining them, it’s possible to more accurately define state needs and allocate Medicaid funding more effectively.
Other programs recognize this — in fact, The FMAP formula is virtually unique in its reliance on a single input variable. Instead of relying on a single measure, the Community Development Block Grant (CDBG) program identifies high-need communities based on a weighted average of several inputs, including population, people in poverty, overcrowded living units, and the age of housing stock. Similarly, DOE grants to states to help cover services for special needs students are based on multiple criteria, including the number of children in the state and the proportion of children in poverty.
Congress should adopt a similar, multivariate approach in calculating the FMAP.