Report to the Honorable Dianne 

Feinstein, U.S. Senate 

United States General Accounting Office 

GAO 

July 2003 MEDICAID FORMULA 

Differences in 

Funding Ability among 

States Often Are 

Widened 

GAO-03-620 
The Medicaid formula narrows the average difference in states’ funding 

ability by 20 percent but often widens the gap between individual states and 

the national average. Although the receipt of federal matching aid moves 30 

states closer to the national average, making the average difference in 

funding ability smaller, it also moves 21 states farther away from the 

average, widening the average difference. These 21 states include 3 that are 

among the states with the largest populations in poverty—California, 

Florida, and New York. After federal matching aid is added, states’ funding 

ability ranges from 26 percent below the national average for two states to 

179 percent above for another. Because of the formula’s current structure, 

in many instances, two states devoting similar proportions of their own 

resources to Medicaid can spend very different amounts per person in 

poverty. For example, in fiscal year 2000, California and Wisconsin each 

devoted about $8 for every $1,000 of their own state resources toward 

Medicaid. However, under the current formula, Wisconsin receives a 

relatively high federal matching rate despite its relatively high ability to fund 

program services, whereas California receives a low federal matching rate 

despite its relatively low ability to fund program services. With the addition 

of federal matching aid, Wisconsin is enabled to spend more than twice what 

California is able to spend per person in poverty ($7,532 versus $3,731). 

Two factors constrain the formula from further decreasing differences in 

states’ funding ability. First, PCI is not a comprehensive indicator of a 

state’s total available resources and is a poor measure of the size of and cost 

to serve a state’s people in poverty. Second, the statutory provision that 

guarantees no state will receive less than a 50 percent matching rate benefits 

many states that already have above-average resources to fund health care 

for their populations in poverty. For example, 2 of the 11 states that benefit 

the most from the 50 percent “floor” receive matching rates that are 35 and 

20 percentage points higher, respectively, than the rates they would receive 

based solely on their PCI. 

GAO received comments on a draft of this report from two external 

reviewers who have Medicaid formula expertise. They generally agreed with 

the analysis and provided technical comments, which were incorporated as 

appropriate. 

A primary goal in establishing 

Medicaid’s statutory formula, 

whereby states with lower per 

capita incomes (PCI) receive 

higher rates of federal 

reimbursement for program costs, 

was to narrow differences among 

states in their ability to fund 

Medicaid services. States’ ability to 

fund services depends on their 

financial resources in relation to 

their number of and costs to serve 

people in poverty. GAO and others 

have testified before Congress that 

the current formula does not 

address wide differences among 

states in their ability to fund their 

Medicaid programs and that the 

formula’s reliance on PCI is the 

primary cause. GAO was asked to 

determine the extent to which the 

formula narrows these differences 

and to identify factors that impede 

further narrowing of differences. 

To evaluate the extent to which the 

formula narrows differences in 

states’ funding ability, GAO used an 

alternative to PCI that more 

directly measures states’ resources, 

number of people in poverty, and 

cost of providing services to this 

population. Using this measure, 

GAO determined the effect of the 

current formula by comparing 

states’ funding ability before and 

after receiving their federal 

matching aid. If differences in 

funding ability were eliminated, the 

formula would have reduced 

differences by 100 percent. 

www.gao.gov/cgi-bin/getrpt?GAO-03-620.

To view the full product, including the scope 

and methodology, click on the link above. 

For more information, contact Kathryn G. 

Allen at (202) 512-7118. 

Highlights of GAO-03-620, a report to the 

Honorable Dianne Feinstein, United 

States Senate 

July 2003 

MEDICAID FORMULA 

Differences in Funding Ability among 

States Often Are Widened 
Page i GAO-03-620 Medicaid Formula 

Letter 1

Results in Brief 4

Background 5

Medicaid Formula Narrows Differences in Some States’ Funding 

Ability and Widens Differences in Others 6

Use of PCI and 50 Percent Floor Inhibits Formula’s Ability to 

Further Narrow Differences in States’ Funding Ability 14

Comments from External Reviewers 20

Appendix I Legislative History and Description of the Matching 

Formula 21 

Legislative History of the Medicaid Formula 21

Current Medicaid Matching Formula 22

Appendix II Methodology 25 

Measuring States’ Funding Ability 25

Measuring State Resources 30

Measuring People in Poverty and the Costs to Provide Them 

Program Services 32

Calculating States’ Ability to Fund Medicaid Services without and 

with Value of Federal Matching Aid Added 41

Comparing Proportion of States’ Resources Devoted to Medicaid 

with Their Total Spending per Person in Poverty 43

Tables 

Table 1: States Benefiting from Minimum Matching Rate 

Provisions, Fiscal Year 2002, and Their Matching Rates 

without the Minimums 19

Table 2: Medicaid Matching Rates for Fiscal Years 2002-2004 23

Table 3: States’ Ability to Fund Program Services without and with 

the Value of Fiscal Year 2000 Federal Matching Aid Added 28

Table 4: Comparison of PCI with TTR, 3-Year Averages, 1996-98 30

Table 5: Distribution of Population in Poverty, by Age Group, 5-

Year Averages, 1995-99 33

Table 6: Weights for Age Groups to Reflect Cost Differences and 

Medicaid Program Participation 35

Table 7: Comparison of Official and Cost-Adjusted Poverty Rates, 

5-Year Averages, 1995-99 37

Table 8: Wage, Rent, and Health Care Cost Indexes, by State 40

Contents 
Page ii GAO-03-620 Medicaid Formula 

Table 9: States’ Funding Ability without and with the Value of 

Fiscal Year 2000 Federal Matching Aid Added 42

Table 10: Proportion of State Resources Devoted to Medicaid per 

$1,000 of TTR Compared with Total Medicaid Spending 

per Person in Poverty, Cost Adjusted, Fiscal Year 2000 44

Figures 

Figure 1: States’ Funding Ability Compared with the National 

Average, without and with the Value of Federal Matching 

Aid Added 8

Figure 2: Proportion of State Resources Devoted to Medicaid, 

Compared with Total (State plus Federal) Medicaid 

Spending, Fiscal Year 2000 11

Figure 3: Proportion of State Resources Devoted to Medicaid 

Compared with Program Spending per Person in Poverty, 

as a Percentage of the National Average, Selected States, 

Fiscal Year 2000 13

Figure 4: States’ per Capita TTR and PCI, 1996-98 15

Figure 5: Comparison of States’ PCIs with Their People in Poverty, 

Cost Adjusted 17
Page iii GAO-03-620 Medicaid Formula 

Abbreviations 

BEA Bureau of Economic Analysis 

BLS Bureau of Labor Statistics 

CMS Centers for Medicare & Medicaid Services 

CPS Current Population Survey 

DSH disproportionate share hospital 

EPSDT Early and Periodic Screening, Diagnostic, and Treatment 

FMAP Federal Medical Assistance Percentage 

FPL federal poverty level 

GSP Gross State Product 

HUD Department of Housing and Urban Development 

PCI per capita income 

PPS Prospective Payment System 

SIC Standard Industrial Classification 

SPI state personal income 

SSA Social Security Administration 

TTR Total Taxable Resources 

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Page 1 GAO-03-620 Medicaid Formula 

July 10, 2003 

The Honorable Dianne Feinstein 

United States Senate 

Dear Senator Feinstein: 

Created in 1965, Medicaid is the largest federal program assisting states in 

financing medical and health-related services for certain categories of the 

country’s low-income population. In fiscal year 2000,1

 Medicaid served 

about 43 million beneficiaries and had expenditures totaling about $196 

billion, $111 billion of which was financed by the federal government and 

the rest financed by the states.2

 The federal share of total Medicaid 

program costs is determined using a statutory formula that calculates the 

portion of each state’s Medicaid expenditures that the federal government 

will pay, known as the Federal Medical Assistance Percentage (FMAP), 

referred to in this report as the federal matching rate.3

 The formula 

calculates the federal matching rate for each state on the basis of its per 

capita income (PCI) in relation to national PCI. States with a low PCI 

receive a higher federal matching rate, and states with a high PCI receive a 

lower rate. The Medicaid statute also provides for a 50 percent minimum 

federal matching rate (“50 percent floor”) that reflects a federal 

commitment to fund at least half the cost of each state’s program.4

One of the goals of the formula has been to narrow differences among 

states in their ability to fund Medicaid services, which is determined by a 

state’s financial resources in relation to its low-income population. By 

providing higher matching rates to states with low PCI, it was expected 

that these states would be in a better position to provide health care 

 1

Fiscal year 2000 is the latest year for which Medicaid data on spending and the number of 

beneficiaries served were available. 

2

Medicaid programs operate in the 50 states, the District of Columbia, and five U.S. 

territories. In this report, “states” refers to the 50 states and the District of Columbia. 

3

Three other programs—the State Children’s Health Insurance Program, Adoption 

Assistance, and Foster Care—also use the Medicaid matching formula to establish federal 

matching rates. These three programs accounted for an additional $7.49 billion in federal 

funding in fiscal year 2000. 

4

42 U.S.C. § 1396d(b)(1) (2000). 

United States General Accounting Office

Washington, DC 20548 
Page 2 GAO-03-620 Medicaid Formula 

services to low-income populations. (App. I contains a legislative history 

of the formula.) 

In 1995, we and other witnesses testified before the Senate Committee on 

Finance that the current Medicaid formula did not adequately address 

wide differences among states in their ability to fund program services and 

that the formula’s reliance on PCI is the primary cause. Witnesses 

generally testified that PCI is an unreliable indicator of states’ ability to 

fund Medicaid programs.5

Because the formula has not been changed since the program’s inception 

and concerns persist regarding its performance with respect to narrowing 

differences in states’ ability to fund program services, you asked us to 

address the following questions: (1) To what extent does the Medicaid 

formula reduce differences in states’ ability to fund program services? (2) 

What factors prevent the formula from further narrowing differences in 

states’ funding ability? 

To evaluate the extent to which the formula narrows differences in states’ 

ability to fund program services, we defined a state’s ability to fund its 

Medicaid programs as the financial resources potentially subject to state 

taxation relative to its number of low-income residents, adjusted for the 

cost of providing health care to them.6

 For state resources, we used Total 

Taxable Resources (TTR), a measure of all income potentially subject to 

taxation that is either produced within a state or received by state 

residents from out-of-state sources. TTR is reported annually by the 

 5

U.S. General Accounting Office, Medicaid: Matching Formula’s Performance and 

Potential Modifications, GAO/T-HEHS-95-226 (Washington, D.C.: July 27, 1995); Jerry 

Cromwell, testimony before the Senate Committee on Finance, Improvements in the 

Federal Medicaid Matching Formula; and Robert P. Strauss, testimony before the Senate 

Committee on Finance, Revising the Medicaid Reimbursement Formula in an Era of 

Fiscal Austerity, 104th Congress, 1st sess., July 27, 1995. 

6

We measured states’ funding ability on the basis of potentially taxable resources and 

potentially eligible participants in Medicaid so that our measure of funding ability, before 

federal matching aid is taken into account, does not reflect the influence of states’ 

individual policy choices. The matching formula also affects states’ decisions about the 

amount and type of Medicaid services they provide and therefore affects the availability of 

health care to low-income individuals as well. However, we did not evaluate the formula’s 

performance in terms of equalizing access to care because of the high degree of uncertainty 

in predicting how individual states’ spending decisions are affected by changes in matching 

rates. 
Page 3 GAO-03-620 Medicaid Formula 

Department of the Treasury.7 To determine the number of low-income 

people in each state (“people in poverty”), we obtained the Bureau of the 

Census’s counts of people with incomes at or below the federal poverty 

level (FPL).8 We adjusted the counts of people in poverty to reflect (1) the 

higher cost of serving the elderly, who utilize health care services at higher 

rates than other age groups, and (2) geographic differences in the cost of 

medical personnel, facilities, and supplies used to deliver health care 

services. To adjust for age differences in people in poverty, we used data 

on Medicaid spending by age group from the Department of Health and 

Human Services’ (HHS) Centers for Medicare & Medicaid Services (CMS).9

We used 5-year averages of people in poverty for each age group for 1995 

through 1999 to increase the reliability of the state-level population counts 

because they are subject to statistical error, especially in smaller states. To 

measure geographic differences in the cost of medical personnel, facilities, 

and supplies, we used data from the Department of Labor’s Bureau of 

Labor Statistics (BLS) and from the Department of Housing and Urban 

Development (HUD). 

We compared states’ funding ability from their own resources with their 

funding ability after their resources have been augmented to include the 

value of the federal Medicaid matching aid they receive. Throughout this 

report, we refer to augmenting a state’s taxable resources this way as state 

funding ability with the “value” of federal matching aid included. If 

differences in funding ability were completely eliminated by adding the 

value of federal matching aid, the formula would have reduced differences 

in states’ funding ability by 100 percent. We did our work between June 

2001 and June 2003 in accordance with generally accepted government 

auditing standards. (App. II provides a more detailed discussion of our 

methodology.) 

 7

We used 3-year averages of TTR (for 1996 through 1998) to parallel the use of 3-year 

averages of PCI in the current formula (see app. I for a more detailed description of the 

current formula). 

8

The federal government bases Medicaid eligibility on a variety of categorical and incomerelated factors, and states may expand their programs beyond the minimum requirements. 

As a result of the flexibility given states in administering their Medicaid programs, except 

for children and pregnant women, there is no federal minimum income level below which 

individuals must be covered under Medicaid that can be used as a basis for measuring 

potentially eligible low-income individuals. 

9

We used CMS data on average per capita Medicaid spending for elderly (aged 65 and over) 

and other beneficiaries to determine how much to weight the numbers of people in poverty 

who are elderly to reflect the higher cost to provide them services. 
Page 4 GAO-03-620 Medicaid Formula 

The current Medicaid formula narrows the average differences in states’ 

funding ability by 20 percent, but it often widens the gap between 

individual states and the national average. Although the formula moves 30 

states closer to the national average funding ability after they receive their 

federal matching aid, making the average differences in funding ability 

smaller, it moves 21 states farther away, including 3 states that have 30 

percent of the nation’s population in poverty—California, Florida, and 

New York. After the value of federal matching aid is added, states’ funding 

ability ranges from 26 percent below the national average for two states to 

179 percent above the national average for another. Because of the 

formula’s current structure, in many instances two states devoting roughly 

the same proportion of their resources to Medicaid are able to spend very 

different amounts per person in poverty. For example, in fiscal year 2000, 

Wisconsin and California devoted the same proportion of their states’ own 

resources to fund their Medicaid programs (about $8 per $1,000 of TTR). 

Yet, after receiving federal matching aid, Wisconsin’s funding ability was 

almost 50 percent above the national average and California’s was 26 

percent below the national average. Because the current Medicaid 

matching formula does not reflect the fact that Wisconsin has fewer 

people in poverty and lower costs to provide health care services to its 

population in poverty than California, Wisconsin’s federal matching aid 

enables it to spend more than twice what California could spend per 

person in poverty—$7,532 compared with $3,731. 

Two factors prevent the Medicaid formula from further narrowing 

differences in states’ funding abilities. First, the formula uses PCI to 

calculate the federal matching rate, but it is a poor proxy measure for the 

components of funding ability—states’ resources and the size of and costs 

to serve their populations potentially eligible for Medicaid services. 

Second, the 50 percent minimum federal matching rate disproportionately 

benefits states that already have above-average resources to fund health 

care for their populations in poverty. The 50 percent “floor” thus prevents 

further narrowing of funding abilities by giving some states federal 

matching rates significantly higher than they would otherwise receive 

without the floor. 

We received comments on a draft of this report from two external 

reviewers with Medicaid formula expertise. They generally agreed with 

our analysis and provided technical comments, which we incorporated as 

appropriate. 

Results in Brief 
Page 5 GAO-03-620 Medicaid Formula 

Medicaid eligibility is determined by several factors, including an 

individual’s or a family’s income in relation to the FPL, age, and eligibility 

for certain other federal program benefits. For example, federal law 

requires state programs to cover pregnant women and children under age 

6 if their family income is at or below 133 percent of the FPL, children 

under age 19 in families with incomes at or below the FPL, and individuals 

who receive Supplemental Security Income because they have disabling 

conditions.10 For most covered populations, state Medicaid programs are 

required to offer certain benefits, such as physician services, inpatient and 

outpatient hospital services, and nursing facility and home health services. 

State Medicaid programs must provide Early and Periodic Screening, 

Diagnostic, and Treatment (EPSDT) services for most children,11 intended 

as comprehensive, periodic evaluations of children’s health and 

developmental history, that include vision, hearing, and dental screening. 

States’ Medicaid programs can differ dramatically because states may 

expand their programs beyond the minimum requirements to cover, for 

example, individuals whose incomes exceed federally mandated eligibility 

thresholds and optional services, such as prosthetic devices and 

prescription drugs. For example, a state may extend Medicaid eligibility to 

certain population groups, such as pregnant women who have family 

incomes above 133 percent of the FPL, or make optional services such as 

prescription drugs available to its entire covered population. 

Since the Medicaid program began, total program costs have been 

apportioned between states and the federal government using a formula 

that provides more generous federal matching aid to states with lower 

PCI.12 The use of PCI in federal grant formulas dates to 1946, when it was 

 10In the majority of states, individuals who receive SSI are automatically eligible for 

Medicaid. Eleven states have more restrictive Medicaid eligibility standards through 

section 1902(f) of the Social Security Act. These 11 states are often referred to as “209(b) 

states” because the origin of this authority was section 209(b) of the Social Security 

Amendments of 1972. Pub. L. No. 92-603, 86 Stat. 1329, 1381 (codified as amended at 42 

U.S.C. § 1396a(f) (2000)). 

11EPSDT services are optional for the medically needy population, a category of individuals 

who generally have too much income to qualify for Medicaid but have “spent down” their 

income by incurring medical care expenses. See 42 U.S.C. § 1396(a)(10)(C) (2000). 

12Matching rates are calculated using the following formula: 

2

U.S.PCI

State PCI FederalMatchingRate 1.00 0.45 













 = −

Background 
Page 6 GAO-03-620 Medicaid Formula 

chosen as a proxy for a state’s ability to fund public services. Consistent 

with the purpose described in the formula’s legislative history, PCI is used 

as a proxy for both state resources and the low-income population. As a 

state’s PCI increases, relative to the national average, the formula provides 

for a decreasing federal matching rate, meaning the federal government 

shares a smaller portion of a state’s costs. By statute, the federal matching 

rate may range from 50 percent to 83 percent.13 The formula’s multiplier, 

currently 0.45, represents the state’s share of its total Medicaid costs for a 

state with PCI equal to the national average, and the federal government 

thus pays a 55 percent share of total costs. 

The Medicaid formula reduces by 20 percent the differences among states 

in their ability to fund program services, compared with the national 

average funding ability. While the formula narrows differences for 30 

states, making the average difference in funding ability smaller, it moves 

21 states farther away from the national average, making the average 

difference wider. These 21 states include 3 that are among those with the 

largest populations in poverty—California, Florida, and New York. 

Because of the formula’s current structure, in many instances, two states 

devoting the same proportion of their own resources toward funding 

Medicaid services are unable, after receiving federal matching aid, to 

spend the same amounts per person in poverty, adjusted for cost 

differences related to age and geographic location. 

Because state resources, numbers of people in poverty, and the cost of 

serving this population vary widely across the states, there also are wide 

differences in states’ ability to fund health care services. Considering these 

indicators of state funding ability, Alaska has the highest funding ability—

exceeding the national average by 119 percent—and Mississippi has the 

lowest funding ability—46 percent below the national average, as 

measured using states’ TTR and the number of people in poverty, adjusting 

the poverty count for age and geographic cost differences (see fig. 1). 

Nationwide, the average difference between a state’s funding ability and 

 13In fiscal year 2003, Mississippi had the highest federal matching rate of any state—76.6 

percent. 

Medicaid Formula 

Narrows Differences 

in Some States’ 

Funding Ability and 

Widens Differences in 

Others 

Formula Reduces Overall 

Differences in States’ 

Funding Ability by 20 

Percent 
Page 7 GAO-03-620 Medicaid Formula 

that of the average state is 22.7 percent.14 Nineteen states have funding 

ability 25 percent or more above the national average, and 10 states have 

funding ability 25 percent or more below the national average. 

After the value of federal matching aid is added to states’ own resources, 

the average difference in states’ funding ability drops from 22.7 percent to 

18.1 percent. This represents a 20 percent reduction of aggregate 

differences in states’ funding ability.15 After the receipt of federal matching 

aid, differences in states’ funding abilities ranged from 26 percent below 

the national average for California and New York to 179 percent above for 

Alaska. 

 14The average difference in states’ funding ability is calculated by comparing each state’s 

funding ability with the average funding ability of all states and calculating the average 

difference (both positive and negative), weighting each state by its number of people in 

poverty. 

15In an absolute sense, the federal matching rate enhances the funding ability of all states. 

By comparing each state’s funding ability with the average funding ability for all states, our 

measure of funding ability is a relative, rather than an absolute, measure of differences in 

funding ability. As a consequence, while states with low funding ability receiving a 

relatively low federal match are helped in an absolute sense, in a relative sense they move 

farther below a new, higher national average funding ability, resulting in relatively larger 

differences in states’ funding ability. 
Page 8 GAO-03-620 Medicaid Formula 

Figure 1: States’ Funding Ability Compared with the National Average, without and with the Value of Federal Matching Aid 

Added 
Page 9 GAO-03-620 Medicaid Formula 

Note: GAO analysis of data from HHS, HUD, and the Departments of Commerce, Labor, and the 

Treasury. 

The aggregate 20 percent reduction of differences in states’ funding ability 

under the formula masks the effect of the formula on individual states. For 

example, as shown in figure 1, consistent with the formula’s goals, the onequarter of states with the lowest funding ability before the match move 

closer to the average state’s funding ability after the value of the federal 

match is added.16 In total, 30 states move closer to the national average 

after adding the federal match. However, as the right panel of figure 1 

shows, adding the value of federal matching aid often has inconsistent 

effects. For example, including the value of federal matching aid moves 

Alaska’s and Utah’s funding ability farther above, rather than closer to, the 

national average funding ability. This happens because PCI does not 

adequately reflect that these two states have fewer people in poverty than 

the national average. In addition, Utah has lower-than-average costs to 

provide health care services. The current formula actually moves 21 states 

farther above or below the average: 

• Four of the 21 states—California, Florida, Hawaii, and New York—have 

below-average funding ability before federal matching aid is added and 

move farther below the average after federal matching aid is added. These 

4 states have approximately 31 percent of the nation’s people in poverty. 

For example, California’s funding ability drops from 15 percent below the 

average to 26 percent below the average and New York’s funding ability 

drops from 12 percent below the average to 26 percent below the average. 

These two states thus rank last in terms of state funding ability after the 

value of federal matching aid is added. 

• Thirteen states that have above-average funding ability before adding the 

value of federal matching aid move farther above the average after it is 

added.17 For example, Utah’s funding ability is 73 percent above the 

national average before the federal match is added but increases to 155 

percent above the national average after the match. 

• Of the 4 remaining states, 3—Idaho, Maine, and North Dakota—have 

below-average funding ability before the match is added and above-

 16In decreasing order of funding ability before adding the value of the federal match, these 

states are Tennessee, Kentucky, Oklahoma, Montana, Arizona, South Carolina, Louisiana, 

District of Columbia, Alabama, Arkansas, West Virginia, New Mexico, and Mississippi. 

17The states, listed from highest to lowest funding ability, are Alaska, Utah, Wisconsin, 

Indiana, Wyoming, Iowa, Kansas, Missouri, Nebraska, Vermont, Ohio, Oregon, and South 

Dakota. 

Funding Ability of 21 

States Moves Farther from 

Average State’s Funding 

Ability after Federal Match 

Is Added 
Page 10 GAO-03-620 Medicaid Formula 

average funding ability after the match is added. For the fourth state—

Rhode Island—the reverse is true: Rhode Island has above-average 

funding ability before the match and below-average funding ability after 

the match is added. 

States commit widely varying proportions of their own financial resources 

to fund Medicaid benefits. For example, in fiscal year 2000, New York 

devoted $18.16 per $1,000 of its TTR toward its Medicaid program,18

roughly 5 times the proportion of resources that Utah devoted ($3.74 per 

$1,000) (see left panel of fig. 2). States’ Medicaid cost-adjusted spending 

per person in poverty varies as well. For example, Alaska’s combined 

federal and state spending was over $10,000 per person in poverty, while 

Nevada’s spending was approximately $2,500 per person in poverty (see 

right panel of fig. 2). 

 18The TTR amount used in these calculations is a 3-year average, 1996-98. 

Many States Devoting the 

Same Proportion of Their 

Own Resources to 

Medicaid Cannot Spend 

Comparable Amounts per 

Person 
Page 11 GAO-03-620 Medicaid Formula 

Figure 2: Proportion of State Resources Devoted to Medicaid, Compared with Total (State plus Federal) Medicaid Spending, 

Fiscal Year 2000 
Page 12 GAO-03-620 Medicaid Formula 

Note: GAO analysis of data from HHS, HUD, and the Departments of Commerce, Labor, and the 

Treasury. 

a

Medicaid spending per person is total spending (state and federal) per person in poverty after 

adjusting for cost differences related to age and geographic location. 

Because the federal matching formula does not fully eliminate differences 

in states’ funding ability, states devoting similar proportions of their own 

resources to Medicaid cannot spend the same amounts per person in 

poverty, cost adjusted, with federal matching aid factored in. In addition, 

because the formula further increases the already high funding ability of 

some states and decreases the low funding ability of others, these 

spending differences can be quite large. For example, in fiscal year 2000, 

both California and Wisconsin devoted roughly the same proportion of 

their own resources to fund program benefits—about $8 per $1,000 of 

taxable resources—which was close to the national average ($8.37) 

proportion of resources states devoted to Medicaid that year. However, 

the current formula moved California’s below-average funding ability 

farther below the national average and increased Wisconsin’s aboveaverage funding ability farther above. This occurred because Wisconsin 

receives a high federal match despite its relatively high funding ability, 

whereas California receives a low federal match despite its relatively low 

funding ability. Once federal matching aid was factored in, with their 

nearly identical funding effort, Wisconsin is enabled to spend more than 

twice what California could spend per person in poverty—$7,532 

compared with $3,731. Similarly, Florida and Iowa each devoted $6.48 per 

$1,000 in state resources toward their Medicaid programs. After adding the 

federal match, Iowa could spend $6,729 per person in poverty, cost 

adjusted, while Florida could spend just $3,160 per person. (See fig. 3.) 
Page 13 GAO-03-620 Medicaid Formula 

Figure 3: Proportion of State Resources Devoted to Medicaid Compared with 

Program Spending per Person in Poverty, as a Percentage of the National Average, 

Selected States, Fiscal Year 2000 

Notes: Spending per person in poverty includes cost adjustments for differences in age and 

geographic location. GAO analysis of data from HHS, HUD, and the Departments of Commerce, 

Labor, and the Treasury. 
Page 14 GAO-03-620 Medicaid Formula 

Two factors prevent the Medicaid formula from further reducing 

differences in states’ funding ability. First, PCI—the single measure used 

to establish federal matching rates—is not a comprehensive measure of 

state resources and is a poor proxy for the size of and cost to serve a 

state’s population in poverty. Second, special statutory provisions, 

including the minimum 50 percent federal matching rate, give several 

states with already high funding ability a higher federal matching rate than 

they would receive without these provisions. 

PCI is an inadequate measure of states’ funding ability because it is an 

incomplete measure of states’ resources, it is a poor proxy for the size of a 

state’s population in poverty, and it does not take into account differences 

in the cost of providing health care services to people in poverty. As an 

indicator of state resources, PCI measures income received by state 

residents, such as wages, rents, and interest income, but it does not 

include other sources of income potentially subject to state taxation, such 

as corporate income produced within the state but not received by state 

residents. For example, PCI especially understates the taxable resources 

in energy-exporting states, such as Alaska and Wyoming, and in states that 

house numerous corporate headquarters, such as Delaware. 

By comparison, because TTR comprises the income included in PCI as 

well as income from other sources, such as corporate income and capital 

gains, states’ TTR exceeds PCI by about 32 percent nationwide.19 As shown 

in figure 4, which compares states’ TTR with PCI, states whose resources 

are particularly poorly represented by PCI include the District of 

Columbia, Delaware, Alaska, and Wyoming. 

 19For a discussion of TTR, see Department of the Treasury, Office of Economic Policy, 

Treasury Methodology for Estimating Total Taxable Resources, TTR (Washington, D.C.: 

Oct. 1, 1998; revised November 2002). http://www.treas.gov/offices/economicpolicy/resources/index.html?IMAGE.X=28\&IMAGE.Y=9 (See “Summary of Current 

Methodology for Estimating TTR”) (downloaded June 4, 2003). 

Use of PCI and 50 

Percent Floor Inhibits 

Formula’s Ability to 

Further Narrow 

Differences in States’ 

Funding Ability 

PCI Is Not a 

Comprehensive Measure 

of States’ Resources and Is 

a Poor Proxy for the Size 

of and Cost to Provide 

Services to Their People in 

Poverty 
Page 15 GAO-03-620 Medicaid Formula 

Figure 4: States’ per Capita TTR and PCI, 1996-98 

Notes: TTR comprises the income included in PCI as well as income from other sources, such as 

corporate income and capital gains. GAO analysis of data from the Departments of Commerce and 

the Treasury. 

0 10,000 20,000 30,000 40,000 50,000 60,000

Mississippi

West Virginia

Montana

New Mexico

Arkansas

Idaho

Utah

Oklahoma

Alabama

Kentucky

Louisiana

South Carolina

North Dakota

Maine

South Dakota

Arizona

Tennessee

Vermont

Wyoming

Iowa

Indiana

North Carolina

Texas

Missouri

Kansas

Georgia

Oregon

Nebraska

Wisconsin

Ohio

Michigan

Florida

Pennsylvania

Hawaii

Rhode Island

California

Virginia

Washington

Alaska

Minnesota

New Hampshire

Delaware

Colorado

Nevada

Illinois

Maryland

New York

Massachusetts

New Jersey

Connecticut

District of Columbia

Dollars

TTR

PCI

Sources: Departments of Commerce and the Treasury.
Page 16 GAO-03-620 Medicaid Formula 

Using PCI to measure the size of a state’s low-income population assumes 

that the lower a state’s PCI, the greater its population in poverty. However, 

two states with similar PCIs may differ widely in their percentages of 

people in poverty. In addition, PCI is not a good proxy for the differences 

in the cost of providing health care services that are related to the ages of 

the population served and the geographic area in which services are 

provided. Persons who are elderly typically use health care services at 

higher rates than adults and children and therefore cost more to serve. 

Two states with low PCIs may have very different proportions of elderly 

persons potentially eligible for Medicaid. In addition, costs to provide 

health care services vary widely depending on geographic location 

because wages and other costs of office space vary regionally. For 

example, the District of Columbia and Connecticut have similar PCIs, but 

the share of the District’s population in poverty is more than twice 

Connecticut’s. Health care costs also are 10 percent higher in the District 

than in Connecticut. (Fig. 5 compares state rankings by PCI and by people 

in poverty, adjusted for cost differences related to age and geographic 

location.) 
Page 17 GAO-03-620 Medicaid Formula 

Figure 5: Comparison of States’ PCIs with Their People in Poverty, Cost Adjusted 

Note: GAO analysis of data from HHS, HUD, and the Departments of Commerce, Labor, and the 

Treasury. 
Page 18 GAO-03-620 Medicaid Formula 

a

People in poverty refers to people with incomes at or below the FPL, adjusted for cost differences 

related to age and geographic location. 

Because of the 50 percent floor, 11 states received higher federal matching 

rates in fiscal year 2002 than they would have if their rates had been based 

only on their PCI. Two others—Alaska and the District of Columbia—

received special federal matching rates set in statutes that gave them 

higher matching rates than they would have received solely on the basis of 

PCI.20 (See table 1.) 

 20Alaska’s current higher matching rate was authorized by the Medicare, Medicaid, and 

SCHIP Benefits Improvement and Protection Act of 2000 to address inadequacies in the 

national calculation and establish more equitable matching rates for the state. Pub. L. No. 

106-554, App. F, § 706, 114 Stat. 2763, 2763A-577. The District of Columbia’s higher 

matching rate was authorized by the Balanced Budget Act of 1997 at the time 

comprehensive policy changes realigning the financial relationship between the District 

and federal government also were enacted. Pub. L. No. 105-33, § 4725 and tit. XI, 111 Stat. 

251, 518 and 712. 

Minimum Federal Match 

Generally Helps States 

That Already Have High 

Funding Ability 
Page 19 GAO-03-620 Medicaid Formula 

Table 1: States Benefiting from Minimum Matching Rate Provisions, Fiscal Year 

2002, and Their Matching Rates without the Minimums 

 Numbers in percent 

State 

Funding ability 

without federal 

match (as a 

percentage of 

national 

average) 

Minimum 

federal 

matching 

rate 

Federal 

matching rate 

without 

minimum 

match

Percentage 

point 

difference 

Alaska 219 57.38 53.01 -4.37 

New Hampshire 179 50.00 47.36 -2.64 

Connecticut 176 50.00 14.99 -35.01 

Colorado 165 50.00 46.22 -3.78 

Delaware 162 50.00 48.13 -1.87 

New Jersey 160 50.00 29.60 -20.40 

Maryland 143 50.00 42.32 -7.68 

Minnesota 143 50.00 48.03 -1.97 

Illinois 131 50.00 46.09 -3.91 

Massachusetts 131 50.00 32.27 -17.73 

Nevada 126 50.00 46.62 -3.38 

New York 88 50.00 37.14 -12.86 

District of Columbia 71 70.00 12.99 -57.01 

Source: HHS. 

Notes: States are listed in decreasing order of funding ability. GAO analysis of data from HHS. 

Eleven of these 13 states (all except the District of Columbia and New 

York) had above-average funding ability in fiscal year 2002. Their receipt 

of a higher federal matching rate than they would have received without 

statutory minimums increases the overall differences in funding ability 

among the states. Connecticut and New Jersey benefit the most from the 

statutory minimums, receiving—as a result of the 50 percent floor—

matching rates that are 35 and 20 percentage points higher, respectively, 

than the rates they would have received based solely on their PCI. 

Receiving a higher matching rate than what the formula provides on the 

basis of PCI enables these states to spend more on program benefits per 

person in poverty than states with less funding ability that devote a higher 

percentage of their resources to funding program benefits. 

The statutory minimums benefit the District of Columbia and New York by 

providing them a higher matching rate than they would otherwise have. 

Because these two states have below-average funding ability, the minimum 

matching provisions have the effect of moving them closer to the funding 

ability of the average state and thus help to reduce overall differences in 
Page 20 GAO-03-620 Medicaid Formula 

funding ability among the states. For example, New York’s funding ability 

without the value of federal matching aid added is 12 percent below the 

average funding ability; with the value of federal matching aid added, its 

funding ability is farther from the average funding ability—26 percent 

below the average. Without the floor, New York’s matching rate would be 

37 percent, rather than 50 percent. Therefore, the 50 percent minimum 

brings New York’s funding ability closer to the average funding ability than 

it would be with the matching rate it would receive without the minimum. 

We received comments on our draft report from two external reviewers 

who have Medicaid formula expertise. The reviewers generally agreed 

with our analysis and provided technical comments, which we 

incorporated as appropriate. 

As agreed with your office, unless you publicly announce its contents 

earlier, we plan no further distribution of this report until 30 days after its 

issue date. At that time, we will send copies of this report to appropriate 

congressional committees and will make copies available to others on 

request. In addition, the report will be available at no charge on the GAO 

Web site at http://www.gao.gov. 

If you or your staff have any questions about this report, please call me at 

(202) 512-7118 or Jerry Fastrup at (202) 512-7211. Major contributors to 

this report include Richard Horte, Robert Dinkelmeyer, Michael Williams, 

Elizabeth T. Morrison, and Michael Rose. 

Sincerely yours, 

Kathryn G. Allen 

Director, Health Care—Medicaid 

 and Private Health Insurance Issues 

Comments from 

External Reviewers 
Appendix I: Legislative History and 

Description of the Matching Formula 

Page 21 GAO-03-620 Medicaid Formula 

This appendix summarizes the legislative history that led to the use of per 

capita income (PCI) in the Medicaid matching formula and describes how 

matching rates are calculated. 

The current formula is an outgrowth of variable rate matching formulas 

first discussed by Congress in the late 1940s. Senate reports accompanying 

the Social Security Act Amendments of 1946 first articulated, in the case of 

public assistance, the rationale for a variable rate matching formula based 

on state PCI: 

Federal grants-in-aid for public assistance are intended to help in aiding the aged and blind 

persons and dependent children in all parts of the country and to some extent to equalize 

the financial burden throughout the Nation. . . . The present 50 percent basis of Federal 

participation does not recognize differences in the ability of States to finance public 

assistance, nor does it recognize the greater incidence of poverty in States with low 

economic resources. To assist their needy people, the low income States must make 

greater tax effort than States with larger resources where relatively fewer persons are in 

need.1

The Social Security Amendments of 1958 established a PCI-based variable 

rate matching formula, with certain maximums, for public assistance and 

reimbursement of medical providers. Under this formula, federal matching 

rates ranged from a minimum of 50 percent for high-income states to a 

maximum of 65 percent for low-income states.2

 The Social Security 

Amendments of 1960 increased the maximum matching rate from 65 

percent to 80 percent.3

 1

S. Rep. No. 79-1862, at 15 (1946), reprinted in 1946 U.S.C.C.A.N. 1510, 1525. In conference, 

a variable rate was adopted, but not one based on state PCI. S. Conf. Rep. No. 79-2724, at 8 

(1946), reprinted in 1946 U.S.C.A.N.N. 1552, 1555. 

2

Pub. L. No. 85-840, § 505, 72 Stat. 1013, 1050. Before this, payments to medical providers 

were reimbursed up to a certain maximum dollar amount at a uniform rate of 50 percent 

for all states. S. Rep. No. 85-2388, at 39 (1958), reprinted in 1958 U.S.C.C.A.N. 4212, 4259. 

3

Pub. L. No. 86-778, sec. 601(f), § 6(c), 74 Stat. 924, 991. 

Appendix I: Legislative History and 

Description of the Matching Formula 

Legislative History of 

the Medicaid Formula 
Appendix I: Legislative History and 

Description of the Matching Formula 

Page 22 GAO-03-620 Medicaid Formula 

When Medicaid was created in 1965, it (1) was structured as an openended entitlement for eligible low-income individuals without limits on the 

maximum dollar amount subject to reimbursement, as in predecessor 

programs;4 (2) increased the federal government’s total nationwide share 

financed from 50 to 55 percent; and (3) raised the maximum federal 

matching rate from 80 to 83 percent.5

 The statutory matching formula, 

known as the Federal Medical Assistance Percentage (FMAP), used for 

calculating matching rates is 

2

U.S.PCI

State PCI FMAP 1.00 0.45 













 = −

The current matching formula is calibrated with a 0.45 “multiplier.” The 

value of the multiplier determines the percentage of a state’s Medicaid 

spending for which the state is responsible. For example, using the 0.45 

multiplier, a state with a PCI equal to the U.S. average would receive a 

federal matching rate of 55 percent (1 - 0.45 = 0.55). A smaller multiplier 

of 0.40 would raise the federal matching rate for all states and would raise 

the matching rate for a state with the national average PCI from 55 percent 

to 60 percent, whereas a higher multiplier of 50 percent would reduce the 

federal matching rate for a state with average PCI from 55 percent to 50 

percent. 

Relative PCI is intended to represent states’ funding ability, which is a 

combination of states’ resources and states’ people in poverty.6

 Consistent 

with this intent, squaring PCI has the effect of making PCI appear in the 

formula twice, thus reflecting both state resources and people in poverty. 

Squaring PCI magnifies the difference between the state’s and the national 

average PCI. For example, if a state’s PCI is 90 percent of the national 

average, the squared value of its relative PCI would be 81 percent (0.9 x 0.9 

= 0.81), resulting in a federal matching rate of 64 percent (that is, 1.00 -

0.45 x 0.81 = 0.64), rather than the 60 percent rate the state would receive 

if relative income was not squared (that is, 1.00 - 0.45 x 0.9 = 0.60). If PCI 

 4

Social Security Amendments of 1965, Pub. L. No. 89-97, sec. 121, § 1905(b), 79 Stat. 286, 

344. 

5

See U.S. General Accounting Office, Changing Medicaid Formula Can Improve 

Distribution of Funds to States, GAO/GGD-83-27 (Washington, D.C.: Mar. 9, 1983) for a 

more complete description of the legislative history of the Medicaid formula. 

6

A state’s relative PCI is its PCI when expressed as a percentage of the U.S. average PCI. 

Current Medicaid 

Matching Formula 
Appendix I: Legislative History and 

Description of the Matching Formula 

Page 23 GAO-03-620 Medicaid Formula 

were a good proxy for people in poverty, squaring would be appropriate 

since squaring would reflect the effect on states’ funding ability of both 

resources and people in poverty. However, to the extent that PCI does not 

accurately reflect state resources and people in poverty, squaring 

magnifies this inaccuracy. 

The Department of Health and Human Services (HHS) is responsible for 

calculating matching rates under the formula. HHS is required to calculate 

matching rates 1 year before the fiscal year in which they are effective, 

using a 3-year average of the most recently available PCI data reported by 

the Department of Commerce. Thus, fiscal year 2003 matching rates were 

calculated at the beginning of fiscal year 2002 using a 3-year average of 

PCI for 1998 through 2000. Publicly announcing matching rates a year in 

advance of their use allows states time to make program changes in 

response to changes in the rate at which the federal government will 

reimburse eligible program costs. However, the combination of a 1-year 

lag between the computation of state matching rates and their 

implementation, coupled with the fact that a 3-year average of PCI is used, 

also means that the distribution of states’ matching rates reflects 

economic conditions that existed several years earlier. Federal matching 

rates for fiscal years 2002 through 2004 are shown in table 2. 

Table 2: Medicaid Matching Rates for Fiscal Years 2002-2004 

 Fiscal year 

State 2002 2003 2004 

Alabama 70.45 70.60 70.75 

Alaska 57.38 58.27 58.39 

Arizona 64.98 67.25 67.26 

Arkansas 72.64 74.28 74.67 

California 51.40 50.00 50.00 

Colorado 50.00 50.00 50.00 

Connecticut 50.00 50.00 50.00 

Delaware 50.00 50.00 50.00 

District of Columbia 70.00 70.00 70.00 

Florida 56.43 58.83 58.93 

Georgia 59.00 59.60 59.58 

Hawaii 56.34 58.77 58.90 

Idaho 71.02 70.96 70.46 

Illinois 50.00 50.00 50.00 

Indiana 62.04 61.97 62.32 

Iowa 62.86 63.50 63.93 

Kansas 60.20 60.15 60.82 

Kentucky 69.94 69.89 70.09 
Appendix I: Legislative History and 

Description of the Matching Formula 

Page 24 GAO-03-620 Medicaid Formula 

 Fiscal year 

State 2002 2003 2004 

Louisiana 70.30 71.28 71.63 

Maine 66.58 66.22 66.01 

Maryland 50.00 50.00 50.00 

Massachusetts 50.00 50.00 50.00 

Michigan 56.36 55.42 55.89 

Minnesota 50.00 50.00 50.00 

Mississippi 76.09 76.62 77.08 

Missouri 61.06 61.23 61.47 

Montana 72.83 72.96 72.85 

Nebraska 59.55 59.52 59.89 

Nevada 50.00 52.39 54.93 

New Hampshire 50.00 50.00 50.00 

New Jersey 50.00 50.00 50.00 

New Mexico 73.04 74.56 74.85 

New York 50.00 50.00 50.00 

North Carolina 61.46 62.56 62.85 

North Dakota 69.87 68.36 68.31 

Ohio 58.78 58.83 59.23 

Oklahoma 70.43 70.56 70.24 

Oregon 59.20 60.16 60.81 

Pennsylvania 54.65 54.69 54.76 

Rhode Island 52.45 55.40 56.03 

South Carolina 69.34 69.81 69.86 

South Dakota 65.93 65.29 65.67 

Tennessee 63.64 64.59 64.40 

Texas 60.17 59.99 60.22 

Utah 70.00 71.24 71.72 

Vermont 63.06 62.41 61.34 

Virginia 51.45 50.53 50.00 

Washington 50.37 50.00 50.00 

West Virginia 75.27 75.04 75.19 

Wisconsin 58.57 58.43 58.41 

Wyoming 61.97 61.32 59.77 

Source: HHS. 

Note: GAO compiled data from HHS. 
Appendix II: Methodology 

Page 25 GAO-03-620 Medicaid Formula 

This appendix describes our methodology for measuring the extent to 

which the current Medicaid matching formula reduces differences in 

states’ funding abilities and the data, and their sources, we used to 

measure the elements of states’ funding ability. While we considered 

alternative indicators of state resources, people in poverty, and the cost of 

health care, and we chose those indicators we believed were most 

appropriate, we did not perform an exhaustive comparative analysis of 

other potential indicators, nor did we attempt to develop new indicators. 

We defined a state’s ability to fund Medicaid services as the economic 

resources a state is potentially able to tax to fund its Medicaid program 

relative to the number of persons with incomes below the federal poverty 

level (FPL), adjusted for the cost of providing health care to them. 

Specifically, we took into account differences in the utilization of health 

care services by children, adults, and the elderly, and we developed an 

index for the differences in the cost of health care personnel and the cost 

of medical facilities and supplies used to provide the services. 

We calculated state funding ability according to the following formula: 

















∗ =





















state state

state

P c

Y

Own Resources

AbilityFrom

State Funding

state

where 

Y = State resources potentially subject to state taxation 

P = People with incomes below the FPL, adjusted for differences in 

service utilization by children, adults, and the elderly 

c = Index of the cost of factors in the provision of health care services 

(e.g., health care personnel, medical facilities, and supplies). 

Appendix II: Methodology 

Measuring States’ 

Funding Ability 

Funding Ability from State 

Resources 
Appendix II: Methodology 

Page 26 GAO-03-620 Medicaid Formula 

We explain later in this appendix how we adjusted the counts of people in 

poverty for differences in service utilization and in the cost of personnel, 

facilities, and supplies. 

Federal matching aid, in effect, adds to a state’s ability to fund program 

costs from its own resources. For example, when federal matching aid 

pays for half the cost of a state’s program, it effectively doubles that state’s 

ability to fund program services. The higher the federal matching rate, the 

more federal matching aid contributes to a state’s ability to fund Medicaid 

services. In general, a state’s funding ability after the value of its federal 

matching aid is added can be determined using the following formula: 

















∗ 















− = 















state state

state

state state P c

Y

1 FMAP

1

with FederalMatching Aid

Medicaid FundingAbility

where 

FMAP = State’s federal matching rate 

Y = State resources potentially subject to state taxation 

P = People with incomes below the FPL, adjusted for differences in 

service utilization by children, adults, and the elderly 

c = Index of the cost of factors in the provision of health care services 

(e.g., health care personnel, medical facilities, and supplies). 

The first term after the equals sign represents the multiple by which a 

state’s matching rate increases the state’s funding ability. For example, if a 

state receives a federal match of 75 percent, its funding ability is increased 

by a factor of 4 [(1/(1 - 0.75) = 4]. 

To measure the effect of the current formula in reducing differences in 

states’ funding ability, we compared differences between each state’s 

funding ability before and after the value of federal matching aid is added 

and calculated the percentage reduction in these differences. In 

performing these calculations, we measured each state’s funding ability 

relative to the average funding ability of all states. The resulting indexes of 

states’ funding abilities provide a means of comparing relative differences 

State Funding Ability with 

the Value of Federal 

Matching Aid Added 

Calculating the Reduction 

of Differences in States’ 

Funding Ability 
Appendix II: Methodology 

Page 27 GAO-03-620 Medicaid Formula 

in states’ ability to fund their Medicaid programs. We used the weighted 

absolute mean deviation as a quantitative measure of differences in states’ 

funding ability. This statistic is a measure of average differences in states’ 

funding ability. It is calculated by taking the absolute value of each state’s 

index of relative funding ability and computing the arithmetic average of 

these differences, using the following formula: 

∑

∑

=

=

⋅ −

= 51

1

s

51

s 1

s s

w

w X X

 Mean Absolute Deviation 

AVG

s

where 

Xs

 = A state’s funding ability index 

XAVG = Weighted average of all states’ funding ability indexes 

ws

 = A state’s weighting factor (people in poverty). 

In calculating the mean absolute deviation, we took into account 

differences in the potential size of state programs by using the number of 

people living in poverty in each state. 

We chose the mean absolute deviation rather than the more commonly 

used weighted standard deviation because the latter, by squaring 

differences between each state’s funding ability and the national average 

funding ability, gives much greater weight to states at the extreme ends of 

the distribution of states’ funding abilities, resulting in a measure that is 

more sensitive to extreme values and thus less likely to reflect the norm. 

We calculated the mean absolute deviation in states’ funding ability both 

without and with the value of federal matching aid added. Calculating the 

percentage change in the two mean absolute deviations measures the 

extent to which the current formula reduces differences in states’ funding 

ability. For example, if the current formula completely eliminated 

differences in states’ funding ability, total funding ability of all states 

would equal the average of all states, and the mean absolute deviation 

would be zero, representing a 100 percent reduction in differences in 

states’ funding ability (the maximum possible). Alternatively, if the 

formula had no effect in reducing differences in states’ funding ability, the 
Appendix II: Methodology 

Page 28 GAO-03-620 Medicaid Formula 

mean absolute deviation in states’ funding ability with the value of federal 

matching aid taken into account would be the same as the mean absolute 

deviation in states’ funding ability from their own resources. In this case, 

there would be no change in the mean absolute deviation, meaning that 

the matching formula had no effect in reducing relative differences in 

states’ funding ability. 

Table 3 shows each state’s index of Medicaid funding ability without and 

with the value of its federal matching aid. 

Table 3: States’ Ability to Fund Program Services without and with the Value of 

Fiscal Year 2000 Federal Matching Aid Added 

State Medicaid funding ability 

(percentage of national average) 

State 

(1)

Without federal 

matching aida

(2)

With FY 2000 federal 

matching aid

Alabama 65 89

Alaska 219 279

Arizona 73 98

Arkansas 61 94

California 85 74

Colorado 165 138

Connecticut 176 147

Delaware 162 136

District of Columbia 71 102

Florida 81 78

Georgia 96 101

Hawaii 98 84

Idaho 94 131

Illinois 131 110

Indiana 148 162

Iowa 147 166

Kansas 126 132

Kentucky 79 112

Louisiana 72 101

Maine 95 117

Maryland 143 120

Massachusetts 131 110

Michigan 111 103

Minnesota 143 123

Mississippi 54 97

Missouri 123 130

Montana 73 119
Appendix II: Methodology 

Page 29 GAO-03-620 Medicaid Formula 

State Medicaid funding ability 

(percentage of national average) 

State 

(1)

Without federal 

matching aida

(2)

With FY 2000 federal 

matching aid

Nebraska 122 131

Nevada 126 106

New Hampshire 179 150

New Jersey 160 134

New Mexico 55 88

New York 88 74

North Carolina 94 105

North Dakota 92 132

Ohio 111 112

Oklahoma 76 112

Oregon 111 117

Pennsylvania 108 98

Rhode Island 101 92

South Carolina 73 102

South Dakota 105 152

Tennessee 80 91

Texas 86 93

Utah 173 255

Vermont 121 134

Virginia 125 108

Washington 141 123

West Virginia 56 92

Wisconsin 150 153

Wyoming 147 174

Sources: HHS and the Departments of Commerce, Labor, and the Treasury. 

Note: GAO calculations are based on data from HHS and the Departments of Commerce, Labor, and 

the Treasury. 

a

Funding ability without federal matching aid was calculated using an average of state taxable 

resources for 1996 through 1998. 

The mean absolute deviation of states’ funding ability before taking into 

account the value of federal matching aid (column 1 of table 3) yielded an 

average difference in states’ relative funding ability of 22.7 percent. The 

mean absolute deviation in states’ funding ability after taking into account 

the value of federal matching aid (column 2 of table 3) yielded an average 

difference of 18.1 percent. This difference represents a 20 percent overall 

reduction in differences in states’ funding ability as a result of adding 

federal matching aid. 
Appendix II: Methodology 

Page 30 GAO-03-620 Medicaid Formula 

As the indicator of state resources in the formula, PCI includes income 

received by state residents (“personal income”), such as wages, rents, and 

interest income, but excludes other important taxable income. For 

example, PCI excludes corporate income not received as income by state 

residents, such as undistributed corporate profits and dividends received 

by people who reside out-of-state. An ideal resources measure would 

count all income that states are able to tax. Even certain types of income 

that states exempt from taxation or tax at preferential rates should be 

counted as potentially taxable income because these enhance taxpayers’ 

ability to pay all taxes levied in the state. 

We used Total Taxable Resources (TTR), as reported by the Department of 

the Treasury, to measure state resources because it comprises the income 

included in PCI as well as income from other sources, such as corporate 

income and capital gains, and thus it is a more comprehensive indicator of 

income than PCI alone.1

 TTR includes personal income received by state 

residents as well as income produced within a state but received by 

individuals who reside out-of-state (which is considered a portion of the 

Gross State Product (GSP)). As indicated in table 4, nationwide, the TTR 

measure of income is 32 percent larger than PCI. 

Table 4: Comparison of PCI with TTR, 3-Year Averages, 1996-98 

State PCI TTR per capita Percentage difference

Alabama $21,194 $26,884 27

Alaska 27,001 42,755 58

Arizona 22,842 29,947 31

Arkansas 20,310 26,324 30

California 26,867 35,057 30

Colorado 28,014 36,340 30

Connecticut 35,507 48,047 35

Delaware 27,872 47,020 69

District of Columbia 36,067 51,503 43

Florida 25,756 32,267 25

Georgia 24,756 33,364 35

Hawaii 26,209 35,220 34

Idaho 21,035 27,399 30

 1

Another possible measure of a state’s resources is the Representative Tax System 

developed by the Advisory Commission on Intergovernmental Relations. We did not use 

this measure in our analysis because data on this measure are not available on an annual 

basis. 

Measuring State 

Resources 
Appendix II: Methodology 

Page 31 GAO-03-620 Medicaid Formula 

State PCI TTR per capita Percentage difference

Illinois 28,442 37,421 32

Indiana 23,902 31,493 32

Iowa 23,785 32,282 36

Kansas 24,388 32,456 33

Kentucky 21,241 28,774 35

Louisiana 21,272 31,520 48

Maine 22,376 28,205 26

Maryland 29,305 38,019 30

Massachusetts 31,448 41,141 31

Michigan 25,608 31,558 23

Minnesota 27,773 35,996 30

Mississippi 18,981 24,480 29

Missouri 24,251 32,314 33

Montana 20,291 25,436 25

Nebraska 24,832 33,481 35

Nevada 28,383 38,887 37

New Hampshire 27,776 39,760 43

New Jersey 32,492 44,438 37

New Mexico 20,296 29,533 46

New York 30,661 41,470 35

North Carolina 24,194 32,076 33

North Dakota 21,577 29,298 36

Ohio 24,897 32,450 30

Oklahoma 21,152 26,412 25

Oregon 24,817 34,477 39

Pennsylvania 26,096 33,239 27

Rhode Island 26,589 35,002 32

South Carolina 21,444 27,809 30

South Dakota 22,603 31,700 40

Tennessee 23,450 30,323 29

Texas 24,201 32,931 36

Utah 21,135 29,010 37

Vermont 23,487 30,344 29

Virginia 26,869 36,788 37

Washington 26,912 35,271 31

West Virginia 19,400 25,379 31

Wisconsin 24,863 32,456 31

Wyoming 23,615 41,920 78

United States $25,949 $34,299 32

Source: Departments of Commerce and the Treasury. 

Notes: Data reflect 3-year averages of TTR and PCI. GAO analysis of data from the Departments of 

Commerce and the Treasury. 
Appendix II: Methodology 

Page 32 GAO-03-620 Medicaid Formula 

While TTR is a more comprehensive measure of state resources than PCI, 

recent definitional changes to GSP and state personal income (SPI) data 

made by the Bureau of Economic Analysis (BEA) may have implications 

for the methodology used by the Department of the Treasury to calculate 

TTR. For example, BEA has changed its treatment of the value of services 

provided by government-owned fixed assets that are now included in GSP 

and benefit payments of government employee pension plans, which are 

now excluded from SPI. Since the Treasury initially developed the TTR 

methodology, it has not reported why definitional changes made by BEA 

should or should not be reflected in TTR. In the case of the changes to 

government pension plans, the Treasury has reported it is currently 

studying whether they necessitate any modifications to the TTR 

methodology. 

To measure people in poverty, we adjusted the Bureau of the Census’s 

estimates of people in households with incomes at or below the FPL for 

(1) differences in the cost of providing health care services to children, 

adults, and the elderly (to account for the higher health care costs for the 

elderly) and (2) geographic differences in the cost of providing health care 

services (such as wages and salaries of health care professionals and the 

rental cost of medical facilities).2

We obtained estimated counts of people living in poverty from the Bureau 

of the Census’s Current Population Survey (CPS). Because the CPS sample 

sizes for individual states are especially small when disaggregated by age 

cohorts, they are subject to greater statistical error than a sample 

representing all age groups. To improve the accuracy of these estimates, 

we averaged poverty counts over the 5-year period 1995 through 1999. We 

used the FPL as a basis for making cross-state comparisons of the number 

of people in poverty. (See table 5.) 

 2

We have excluded disproportionate share hospital (DSH) payments from this analysis. 

These hospitals receive additional Medicaid reimbursement because they serve a 

disproportionate number of Medicaid and other low-income patients. We have excluded 

these payments from our analysis because the federal government uses a different 

distribution formula from the regular Medicaid program. 

Measuring People in 

Poverty and the Costs 

to Provide Them 

Program Services 

Measuring the Number of 

People in Poverty 
Appendix II: Methodology 

Page 33 GAO-03-620 Medicaid Formula 

Table 5: Distribution of Population in Poverty, by Age Group, 5-Year Averages, 

1995-99 

 Percentage who are 

State 

Official 

poverty 

count Childrena

 Adultsb Elderlyc

Alabama 684,401 44 44 11

Alaska 52,434 47 50 3

Arizona 773,651 49 44 7

Arkansas 418,593 43 44 14

California 5,213,675 48 46 6

Colorado 356,379 42 52 6

Connecticut 307,435 46 44 10

Delaware 73,643 47 43 11

District of Columbia 111,071 43 46 12

Florida 2,040,854 41 47 12

Georgia 1,024,452 47 44 9

Hawaii 138,433 42 49 9

Idaho 166,135 49 44 7

Illinois 1,335,576 49 42 9

Indiana 485,926 39 50 10

Iowa 273,851 44 47 9

Kansas 275,646 45 44 12

Kentucky 568,739 41 48 10

Louisiana 811,417 47 44 10

Maine 132,323 39 47 14

Maryland 437,917 42 44 14

Massachusetts 653,754 43 46 11

Michigan 1,064,367 47 43 10

Minnesota 437,201 46 43 11

Mississippi 518,149 45 44 11

Missouri 554,936 42 46 11

Montana 143,838 46 47 7

Nebraska 176,270 42 44 13

Nevada 181,524 46 45 9

New Hampshire 91,519 42 45 12

New Jersey 680,727 39 47 13

New Mexico 411,507 51 42 8

New York 2,945,784 45 45 10

North Carolina 931,440 42 46 12

North Dakota 81,831 44 44 12

Ohio 1,308,010 46 45 9

Oklahoma 486,474 42 47 11

Oregon 410,697 45 49 7
Appendix II: Methodology 

Page 34 GAO-03-620 Medicaid Formula 

 Percentage who are 

State 

Official 

poverty 

count Childrena

 Adultsb Elderlyc

Pennsylvania 1,322,801 42 47 12

Rhode Island 107,019 40 43 17

South Carolina 539,744 46 42 12

South Dakota 86,713 45 42 13

Tennessee 784,910 43 47 10

Texas 3,149,475 48 44 9

Utah 163,467 51 44 5

Vermont 61,026 42 49 9

Virginia 686,279 39 48 13

Washington 584,612 43 50 7

West Virginia 299,257 36 50 14

Wisconsin 448,444 46 45 10

Wyoming 57,957 45 45 9

United States 35,052,282 45 45 10

Source: Department of Commerce. 

Note: Percentages may not add to 100 across age groups because of rounding. 

a

Population under age 21 with income at or below the FPL. 

b

Population aged 21 to 64 with income at or below the FPL. 

c

Population aged 65 and over with income at or below the FPL. 

Official poverty counts are not a good proxy for the low-income 

population because they do not take into account the higher cost of 

serving elderly individuals. For example, elderly individuals represented 

27 percent of Medicaid beneficiaries in fiscal year 2000, the latest year for 

which data are available. However, because they are more intensive users 

of the health care system and utilize more expensive long-term care 

services, elderly persons accounted for 66 percent of all Medicaid 

spending that year. 

To account for differences in costs to serve each group, we weighted the 

numbers of children, adults, and the elderly. We calculated Medicaid 

spending per beneficiary for each age group nationwide, then compared 

spending per beneficiary for each age group with average spending per 

beneficiary for all age groups. We used a 5-year average of Medicaid 

spending per beneficiary derived from data reported by the Centers for 

Medicare & Medicaid Services (CMS) for fiscal years 1995 through 1999. 

The results suggest that, nationwide, elderly beneficiaries utilize health 

Adjusting Poverty Counts 

for Differences in Costs to 

Serve Children, Adults, and 

the Elderly 
Appendix II: Methodology 

Page 35 GAO-03-620 Medicaid Formula 

care services at about two-and-one-half times the rate of the average 

Medicaid beneficiary, and children utilize services at less than half the rate 

of the average beneficiary. (See the cost weight index column in table 6.) 

Table 6: Weights for Age Groups to Reflect Cost Differences and Medicaid Program 

Participation 

Age group 

Average 

annual 

spending per 

beneficiary

Cost weight 

(index)a

Average 

participation 

rate (index)b

Adjusted 

cost 

weightc

Elderly (aged 65 or 

older) $9,005 2.5 1.4 3.5

Adults (aged 21-64) $4,729 1.3 0.7 1.0

Children (under age 21) $1,483 0.4 1.2 0.5

All groups $3,532 1.0 1.0 1.0

Sources: Department of Commerce and HHS. 

Note: GAO analysis of data from the Department of Commerce for 1995 through 1999 and data from 

HHS for 1994 through 1998. 

a

Index is spending per recipient for each age group divided by average spending per recipient for all 

age groups. 

b

Index is the percentage of people in each age group receiving Medicaid benefits, expressed as a 

ratio to the average of all groups. 

c

Calculated by multiplying the cost weight index by the participation rate index. 

To adjust for differences in program participation across age groups, we 

compared the number of Medicaid beneficiaries by age group with the 

number of people in poverty. We compared these counts with the national 

average participation rates for all Medicaid beneficiaries. We calculated 

the adjusted cost weight by multiplying the cost weight index by the 

average participation rate index. We calculated a weighted count of people 

in poverty for each state by applying the adjusted cost weights in the last 

column of table 6 to poverty counts by age group, according to the 

following formula: 





















+





















+





























=





















Age 21

PovertyUnder

Number in

0.5

Aged 21 to 64

Poverty

Number in

1.0

Age 65

Over

Poverty

Number in

3.5

Count

Poverty

Weighted

In table 7, the columns representing official poverty rates report the 

percentage of people in poverty based on the official government poverty 
Appendix II: Methodology 

Page 36 GAO-03-620 Medicaid Formula 

statistics reported by the Bureau of the Census. The age-weighted columns 

are the percentages of people in poverty after weighting children, adults, 

and the elderly. Comparing the percentages in the official poverty rate 

columns with the percentages after age-weighting illustrates the effect of 

differences in utilization rates by age cohort. For example, Florida’s 

official poverty rate is revised upward from 14.0 percent to 15.3 percent 

when weighted for age differences. Similarly, the District of Columbia’s 

poverty rate increases from about 21.1 percent to about 22.7 percent after 

weighting.3

 3

The age and health care use cost-adjusted poverty rates in table 7 will be discussed in the 

next section, in which we describe the cost adjustments made for differences in medical 

care costs. 
Appendix II: Methodology 

Page 37 GAO-03-620 Medicaid Formula 

Table 7: Comparison of Official and Cost-Adjusted Poverty Rates, 5-Year Averages, 1995-99 

 Official poverty rate Age-weighted poverty rate 

 Age and health care use 

cost-adjusted poverty rate 

State 

Percentage of 

people in poverty

Percentage 

of U.S. 

poverty rate 

Percentage in 

poverty 

Percentage 

of U.S. 

poverty rate 

Percentage 

in poverty

Percentage 

of U.S. 

poverty rate

Alabama 15.9 122 16.9 128 16.0 121

Alaska 8.2 63 6.9 52 7.2 54

Arizona 16.5 126 15.2 115 15.7 119

Arkansas 16.3 125 18.3 138 16.4 124

California 15.9 122 14.2 108 15.7 118

Colorado 9.0 69 8.4 63 8.5 64

Connecticut 9.3 71 9.4 71 10.4 78

Delaware 9.9 75 10.2 77 11.1 84

District of Columbia 21.1 162 22.7 172 27.7 209

Florida 14.0 108 15.3 116 15.6 118

Georgia 13.6 104 13.6 103 13.4 102

Hawaii 11.6 89 11.9 90 13.7 104

Idaho 13.6 104 12.6 95 11.3 85

Illinois 11.1 85 11.0 83 11.0 83

Indiana 8.4 64 8.9 68 8.3 63

Iowa 9.6 74 9.7 73 8.5 64

Kansas 10.7 82 11.4 86 10.1 76

Kentucky 14.7 112 15.4 117 14.2 107

Louisiana 19.0 145 19.2 145 17.1 130

Maine 10.7 82 12.5 94 11.6 87

Maryland 8.6 66 9.9 75 10.3 78

Massachusetts 10.7 82 11.3 86 12.1 92

Michigan 10.8 83 10.9 83 10.9 82

Minnesota 9.2 71 9.8 74 9.7 73

Mississippi 18.9 145 19.6 149 17.5 132

Missouri 10.4 80 11.2 85 10.3 78

Montana 16.0 123 15.0 114 13.1 99

Nebraska 10.6 81 11.8 90 10.4 79

Nevada 10.5 80 10.4 79 11.9 90

New Hampshire 7.7 59 8.5 64 8.5 64

New Jersey 8.5 65 9.6 73 10.8 82

New Mexico 22.6 173 21.2 161 19.8 150

New York 16.1 123 16.5 125 17.9 136

North Carolina 12.8 98 13.9 105 13.6 103

North Dakota 13.0 99 14.1 106 12.4 94

Ohio 11.6 89 11.7 88 11.2 85

Oklahoma 14.8 114 15.7 119 13.5 102

Oregon 12.5 95 11.8 89 11.9 90

Pennsylvania 11.1 85 12.0 91 11.9 90
Appendix II: Methodology 

Page 38 GAO-03-620 Medicaid Formula 

 Official poverty rate Age-weighted poverty rate 

 Age and health care use 

cost-adjusted poverty rate 

State 

Percentage of 

people in poverty

Percentage 

of U.S. 

poverty rate 

Percentage in 

poverty 

Percentage 

of U.S. 

poverty rate 

Percentage 

in poverty

Percentage 

of U.S. 

poverty rate

Rhode Island 11.2 86 13.6 103 13.6 103

South Carolina 14.3 109 15.1 114 14.9 113

South Dakota 12.3 94 13.5 102 12.0 90

Tennessee 14.2 109 14.5 110 14.2 107

Texas 16.1 124 15.8 119 14.8 112

Utah 7.9 61 7.0 53 6.5 49

Vermont 10.3 79 10.6 80 9.6 73

Virginia 10.4 79 11.8 89 11.6 88

Washington 10.4 79 10.0 75 9.7 73

West Virginia 17.0 131 20.1 152 18.0 136

Wisconsin 8.6 66 8.7 66 8.3 62

Wyoming 12.0 92 12.1 91 10.8 82

United States 13.1 100 13.2 100 13.2 100

Sources: HHS, and the Departments of Commerce, Housing and Urban Development (HUD), and Labor. 

Note: GAO analysis of data from HHS, HUD, and the Departments of Commerce and Labor. 

The cost of providing health care services is affected by three factors: (1) 

the cost of the personnel who provide the services (wages, for example), 

(2) the rental cost of facilities in which the services are provided, and (3) 

the cost of medical equipment and supplies. 

We used the average wage per worker in the health industry (Standard 

Industrial Classification (SIC) code 8000), produced by the Bureau of 

Labor Statistics (BLS), to measure the cost of personnel for 1996 through 

1998. The BLS cost data cover personnel in a wide variety of settings, 

including offices, clinics, hospitals, and medical and dental laboratories, as 

well as health care providers who work for home health agencies. 

To measure the cost of facilities through which services are delivered, we 

used apartment rents as reported by the Department of Housing and 

Urban Development (HUD) because data on commercial office space 

rental rates in the health sector of the economy were not available. 

Apartment rental rates were an appropriate alternative because the same 

factors that affect the cost of office space (for example, population density 

and income) affect housing rental rates, and apartment rental rates are 

likely to more closely mimic office space costs than would owneroccupied housing units. In addition, data are available for apartment 

Adjusting Poverty Counts 

for Differences in the Cost 

of Providing Health Care 

Services 
Appendix II: Methodology 

Page 39 GAO-03-620 Medicaid Formula 

rentals by the size of the unit, which allowed us to take size differences 

into account. 

Data on the geographic differences in the cost of medical equipment and 

supplies were not readily available. Because medical equipment and 

supplies generally are purchased in national markets, we assumed that the 

costs of these items do not vary across states. 

We calculated an index of health industry wage rates and apartment rents 

(our proxy for the rental cost of medical facilities). For medical supplies, 

we used a cost index of 1.0 for all states to reflect the assumption that 

these costs do not vary across states. We then combined the three factors 

into an overall index of the cost of health care services by state, weighting 

each factor on the basis of its respective proportion of the total cost of 

health care services. Personnel costs represent the greatest share of health 

care costs, as much as 75 percent of total costs, according to one study.4

We constructed our cost index conservatively by reducing the personnel 

cost weight to 60 percent. We applied a cost weight of 30 percent for 

medical equipment and supplies and other miscellaneous costs that are 

assumed to be the same across states. The remaining 10 percent is the cost 

weight for rent. Using these cost weights is likely to understate cross-state 

cost differences. 

Nineteen states had health care costs estimated to be at least 10 percent 

above or below the national average. The states with costs 10 percent or 

more above the national average were California, Connecticut, the District 

of Columbia, Hawaii, Nevada, and New Jersey. States with lower costs 

tended to be southern or midwestern states. (See table 8.) 

 4

Gregory Pope, Adjusting the Alcohol, Drug Abuse, and Mental Health Services Block 

Grant for Allocations for Poverty Population and Cost of Service (Needham, Mass.: Health 

Economics Research, Inc., Mar. 30, 1990). 
Appendix II: Methodology 

Page 40 GAO-03-620 Medicaid Formula 

Table 8: Wage, Rent, and Health Care Cost Indexes, by State 

 Percentage of national average 

State 

Wage index

(3-year averages, 

1996-98)

Rent index

(FY 2000)

Health care cost 

index 

Alabama 96 70 95 

Alaska 104 124 105 

Arizona 106 98 103 

Arkansas 88 67 89 

California 112 127 110 

Colorado 101 107 101 

Connecticut 113 125 110 

Delaware 114 104 109 

District of Columbia 131 133 122 

Florida 103 100 102 

Georgia 100 91 99 

Hawaii 119 139 115 

Idaho 87 75 90 

Illinois 100 104 100 

Indiana 92 82 93 

Iowa 83 74 87 

Kansas 85 77 89 

Kentucky 92 69 92 

Louisiana 87 72 89 

Maine 90 88 93 

Maryland 105 113 104 

Massachusetts 106 131 107 

Michigan 101 93 100 

Minnesota 99 93 99 

Mississippi 87 66 89 

Missouri 91 74 92 

Montana 82 77 87 

Nebraska 84 77 88 

Nevada 122 110 114 

New Hampshire 99 112 100 

New Jersey 114 134 112 

New Mexico 92 81 93 

New York 109 132 109 

North Carolina 99 84 98 

North Dakota 85 71 88 

Ohio 96 85 96 

Oklahoma 83 69 86 

Oregon 101 99 101 

Pennsylvania 99 94 99 
Appendix II: Methodology 

Page 41 GAO-03-620 Medicaid Formula 

 Percentage of national average 

State 

Wage index

(3-year averages, 

1996-98)

Rent index

(FY 2000)

Health care cost 

index 

Rhode Island 99 108 100 

South Carolina 101 79 99 

South Dakota 85 77 89 

Tennessee 100 76 98 

Texas 92 90 94 

Utah 90 95 93 

Vermont 85 97 91 

Virginia 98 98 99 

Washington 94 106 97 

West Virginia 88 66 90 

Wisconsin 95 85 95 

Wyoming 87 76 90 

United States 100 100 100 

Sources: HHS, HUD, and the Department of Labor. 

Notes: States in bold have health care costs estimated to be 10 percent or more above or below the 

national average. GAO analysis of data from HHS, HUD, and the Department of Labor. 

We compared states’ ability to fund Medicaid services without and with 

the value of federal matching aid added. Column 1 of table 9 shows states’ 

funding ability: states’ TTR per person in poverty adjusted for differences 

in the cost of providing them health care services. Column 2 shows states’ 

effective fiscal year 2000 federal matching rates used in the analysis5

 and 

column 3 shows the resulting “multipliers” (i.e., 1/(1 - FMAP)) that reflect 

the effect of federal matching on states’ funding ability. Funding ability 

with federal aid is shown in column 4. 

 5

To calculate effective matching rates we divided each state’s federal matching aid by its 

total Medicaid spending, net of DSH and certain other costs. 

Calculating States’ 

Ability to Fund 

Medicaid Services 

without and with 

Value of Federal 

Matching Aid Added 
Appendix II: Methodology 

Page 42 GAO-03-620 Medicaid Formula 

Table 9: States’ Funding Ability without and with the Value of Fiscal Year 2000 Federal Matching Aid Added 

State 

(1)

Funding ability from 

state resources 

(dollars per person in 

poverty)a

(2) 

Effective FY 2000 

FMAP (percentage) 

(3) 

FMAP multiplier 

(4)

Funding ability with 

federal matching aid

(col. 1 x col. 3)

Alabama $169,683 69.64 3.29 $558,840

Alaska 570,409 67.26 3.05 1,742,447

Arizona 189,505 69.19 3.25 615,081

Arkansas 158,718 73.11 3.72 590,165

California 222,437 52.06 2.09 463,963

Colorado 429,969 50.08 2.00 861,380

Connecticut 459,835 50.02 2.00 920,046

Delaware 422,823 50.20 2.01 848,991

District of Columbia 184,951 70.93 3.44 636,309

Florida 211,705 56.60 2.30 487,803

Georgia 251,548 60.01 2.50 628,961

Hawaii 256,566 51.03 2.04 523,891

Idaho 244,092 70.29 3.37 821,587

Illinois 341,369 50.15 2.01 684,770

Indiana 386,661 61.84 2.62 1,013,136

Iowa 382,676 63.14 2.71 1,038,320

Kansas 328,243 60.09 2.51 822,538

Kentucky 205,683 70.62 3.40 700,085

Louisiana 187,290 70.37 3.38 632,139

Maine 246,614 66.31 2.97 732,052

Maryland 374,141 50.18 2.01 750,931

Massachusetts 342,550 50.13 2.01 686,922

Michigan 289,686 55.17 2.23 646,136

Minnesota 372,580 51.69 2.07 771,185

Mississippi 140,227 76.89 4.33 606,653

Missouri 320,009 60.58 2.54 811,740

Montana 190,431 74.49 3.92 746,413

Nebraska 319,214 61.00 2.56 818,427

Nevada 327,582 50.45 2.02 661,158

New Hampshire 467,893 50.08 2.00 937,274

New Jersey 417,976 50.07 2.00 837,128

New Mexico 142,227 74.19 3.87 551,081

New York 229,337 50.11 2.00 459,721

North Carolina 244,355 62.61 2.67 653,542

North Dakota 238,866 70.97 3.45 822,897

Ohio 289,509 58.72 2.42 701,375

Oklahoma 198,643 71.63 3.53 700,263

Oregon 288,765 60.42 2.53 729,556

Pennsylvania 281,796 53.84 2.17 610,540
Appendix II: Methodology 

Page 43 GAO-03-620 Medicaid Formula 

State 

(1)

Funding ability from 

state resources 

(dollars per person in 

poverty)a

(2) 

Effective FY 2000 

FMAP (percentage) 

(3) 

FMAP multiplier 

(4)

Funding ability with 

federal matching aid

(col. 1 x col. 3)

Rhode Island 264,602 53.77 2.16 572,326

South Carolina 189,300 70.18 3.35 634,851

South Dakota 274,528 71.07 3.46 948,856

Tennessee 209,859 63.19 2.72 570,142

Texas 224,158 61.54 2.60 582,883

Utah 452,178 71.65 3.53 1,595,085

Vermont 315,610 62.39 2.66 839,259

Virginia 325,551 51.90 2.08 676,811

Washington 367,374 52.08 2.09 766,584

West Virginia 145,611 74.80 3.97 577,734

Wisconsin 392,390 58.88 2.43 954,178

Wyoming 383,724 64.63 2.83 1,084,827

United States $260,851 56.83 2.32 $624,935

Sources: HHS and the Department of the Treasury. 

Notes: Calculations were done with unrounded numbers, not the rounded numbers shown in the 

table. GAO analysis of data from HHS and the Department of the Treasury. 

a

Funding ability without federal matching aid was calculated using an average of TTR for 1996 

through 1998. 

The data used to show the relationship between a state’s effort to fund 

Medicaid benefits from its own financial resources and its total Medicaid 

spending per person in poverty, shown in figure 2, are displayed in table 

10. 

Comparing 

Proportion of States’ 

Resources Devoted to 

Medicaid with Their 

Total Spending per 

Person in Poverty 
Appendix II: Methodology 

Page 44 GAO-03-620 Medicaid Formula 

Table 10: Proportion of State Resources Devoted to Medicaid per $1,000 of TTR 

Compared with Total Medicaid Spending per Person in Poverty, Cost Adjusted, 

Fiscal Year 2000 

State 

State financial resources 

per $1,000 of TTR 

Total Medicaid spending 

per person in poverty

Alabama $6.08 $3,397 

Alaska 5.84 10,178 

Arizona 4.64 2,851 

Arkansas 6.35 3,747 

California 8.04 3,731 

Colorado 6.26 5,391 

Connecticut 8.99 8,274 

Delaware 7.35 6,242 

District of Columbia 8.51 5,417 

Florida 6.48 3,160 

Georgia 6.15 3,869 

Hawaii 7.51 3,935 

Idaho 5.07 4,166 

Illinois 7.79 5,332 

Indiana 6.07 6,153 

Iowa 6.48 6,729 

Kansas 6.23 5,127 

Kentucky 7.40 5,179 

Louisiana 5.59 3,533 

Maine 10.93 7,999 

Maryland 7.38 5,544 

Massachusetts 11.43 7,849 

Michigan 9.12 5,895 

Minnesota 9.20 7,094 

Mississippi 6.19 3,757 

Missouri 7.82 6,345 

Montana 5.13 3,826 

Nebraska 7.26 5,941 

Nevada 3.83 2,533 

New Hampshire 7.32 6,864 

New Jersey 7.00 5,857 

New Mexico 6.12 3,370 

New York 18.16 8,347 

North Carolina 7.77 5,075 

North Dakota 6.64 5,467 

Ohio 7.77 5,449 

Oklahoma 5.12 3,586 

Oregon 7.26 5,299 

Pennsylvania 11.29 6,891 
Appendix II: Methodology 

Page 45 GAO-03-620 Medicaid Formula 

State 

State financial resources 

per $1,000 of TTR 

Total Medicaid spending 

per person in poverty

Rhode Island 14.27 8,170 

South Carolina 6.40 4,061 

South Dakota 4.92 4,671 

Tennessee 11.04 6,296 

Texas 5.58 3,252 

Utah 3.74 5,964 

Vermont 10.32 8,661 

Virginia 5.10 3,455 

Washington 8.71 6,679 

West Virginia 7.22 4,170 

Wisconsin 7.89 7,532 

Wyoming 3.85 4,171 

United States $8.37 $5,056 

Sources: HHS and the Departments of Commerce, Housing and Urban Development, and the Treasury. 

Note: GAO analysis of data from HHS and the Departments of Commerce, Housing and Urban 

Development, and the Treasury. 

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