EXECUTIVE OFFICE OF THE PRESIDENT

COUNCIL OF ECONOMIC ADVISERS

THE EFFECTS OF STATE FISCAL RELIEF

September 10, 2009
1

I. INTRODUCTION

One important component of American Recovery and Reinvestment Act (ARRA) is state 

fiscal relief. Through August 28, $38.4 billion had gone to states in the form of fiscal relief, with 

most of that total ($28.1 billion) coming through a higher Federal share of Medicaid spending. 

As Table 1 shows, state fiscal relief constituted a crucial portion of the early part of the stimulus 

– nearly two-thirds of the spending and a quarter of total ARRA stimulus (that is outlays plus tax 

cuts) through the second quarter of 2009 came in the form of state fiscal relief.1

February - Junea Julyb August

c

Spending provisionsd 43.0 16.5 15.7

State fiscal relief

e 28.2 6.2 4.0

Tax provisionsf 56.8 10.3 9.2

Total 99.8 26.8 24.8

Notes: a. Data from recovery.gov are through June 26.

b. Data from recovery.gov are for June 27 through July 31.

c. Data from recovery.gov are for July 31 through August 28.

e. Grants to States for Medicaid; State Fiscal Stabilization Fund.

f. Estimated effects of tax provisions; Economic Recovery Payments; Compensation and Pensions.

d. All recovery.gov spending excluding: Economic Recovery Payments made through the Social

Security Administration and Railroad Retirement Board; and Compensation and Pensions made

through Veteran Affairs.

Sources: Recovery.gov; Updated simulations from the Department of the Treasury (Office of Tax

Analysis); CEA calculations.

Table 1. Total ARRA Spending and Tax Relief by Category

Billions of Dollars

 

State budget relief was especially important because states, which normally must end the 

year with a balanced budget,

2 experienced budget gaps of up to 20 percent of their general funds 

at some point during the 2009 fiscal year.

3

 

1 See U.S. Recovery Accountability and Transparency Board (2009).

2 See National Governors Association and National Association of State Budget Officers (2008) for a discussion of 

the exact balanced budget requirements.

3 See National Conference of State Legislatures (2009a).

 In response to these gaps, states were already raising 

taxes and reducing spending by the time the ARRA was passed. These actions not only placed 

further burdens on families already suffering from the recession and cut important services, but 

also directly contributed to the worsening of the downturn. The aid to states appears to have 
2

helped prevent large tax increases and cuts to government social programs and services that 

otherwise would have taken place. 

All states have received substantial support. The ARRA was designed to provide greater 

support for states hit harder by the recession. For example, it further increased the Federal 

component of Medicaid spending in states that have experienced especially large increases in 

unemployment. Moreover, because Medicaid is a means-tested program, an increase in 

Medicaid funding naturally provides more funds to states where more workers are unemployed.4

 

 

And indeed, fiscal relief per capita has on average been greater in states that had higher 

unemployment rates at the time the Act was passed.

Since there is ample evidence that increases in government spending and reductions in 

taxes help slow economic downturns, there is every reason to think that the state fiscal relief has 

been one force helping to move the economy from recession to recovery. But, we have little 

direct evidence that specifically concerns the economic effects of state fiscal relief. For example, 

there has been little research concerning the macroeconomic effects of the 1972 State and Local 

Fiscal Assistance Act or the $20 billion state fiscal relief package in 2003. In this report, we 

therefore look at the effects of state fiscal relief in more detail.

Simply asking whether states that have received more ARRA funds have generally 

performed better has an obvious problem: on average, states that were “sicker” may have 

received more “medicine.” For example, the ARRA further increased the Federal component of 

Medicaid spending in states that have experienced especially large increases in unemployment. 

Moreover, because Medicaid is a means-tested program, during recessions states that lose the 

largest number of jobs tend to see a relative increase in the number of their residents eligible for 

Medicaid. These states would therefore tend to receive more funds from the Federal

government. Thus, a finding that states that had received more ARRA funding had greater 

economic problems would not be evidence that fiscal relief causes economic problems; it would 

just be evidence that the relief was well targeted.

4 A possible effect operating in the opposite direction is that states with larger economic declines could decrease 

Medicaid generosity to balance their budgets. To ensure that this did not occur, the ARRA specifically mandated 

that eligibility standards not be tightened, so distressed states could not alter their eligibility rules and still receive 

ARRA funding.
3

This report describes how it is possible to mitigate this problem by focusing on a part of 

the Medicaid relief to states which resulted from decisions prior to the recession. We then 

describe the institutional details of the Federal Medicaid funding. Finally, we present results for 

the relationship between employment changes and state fiscal relief and suggest that 

government-related employment and spending may explain part of this relationship.

II. IDENTIFYING THE RELATIONSHIP BETWEEN FISCAL RELIEF AND EMPLOYMENT CHANGES

To get evidence about the effects of the fiscal relief, we focus on a particular part of the 

relief: the increase in Federal Medicaid spending which resulted from typical state Medicaid 

expenditures before the recession. Even in normal times, Medicaid expenditures per capita vary 

substantially across states. The ARRA increased by 6.2 percentage points the Federal share of 

states’ Medicaid expenses. As a result, states that spent more on Medicaid per resident before 

the recession received more recovery dollars per capita from this portion of the package. 

We can estimate the fiscal relief to states from this portion of the program by multiplying 

0.062 times Medicaid spending per person in the state in fiscal year 2007. Since this component, 

which we refer to as “estimated non-cyclical ARRA Medicaid payouts,” was determined before 

the recession, it is plausibly less related to the recession’s effects on jobs than overall state fiscal 

relief. Indeed, although we cannot be sure if other factors are responsible for the relationship

between this measure and employment changes, we will present evidence below to suggest that 

this correlation is not driven by some important underlying differences between states that 

received more money and states that received less. 

Because there are substantial cross-state differences in the amount of money spent on 

Medicaid per resident, some states received more dollars per capita from this portion of the 

stimulus package than others. Figure 1 shows the variation in estimated non-cyclical ARRA 

Medicaid payout across states. This difference allows us to compare the change in employment 

in states that received relatively large amounts of fiscal relief with those that received somewhat 

less. By using this “treatment-and-control group” research design, we attempt to isolate the 

effect of state fiscal relief from other factors that may have influenced net employment growth.
4

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40

60

80

100

120

140

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AK

AL

AR

AZ

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CO

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DC

DE

FL

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HI

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ID

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IN

KSKY

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MI

MN

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NCND

NE

NH

NJ

NM

NVNY

OH

OK

OR

PA

RI

SCSD

TN

TX

UT

VA

VT

WA

WI

WVWY

Figure 1. Estimated Non-cyclical ARRA Medicaid Payouts

Dollars per capita

Source: Centers for Medicare and Medicaid Services. Data Compendium. 2008.

Note: Each bar represents 0.062 multiplied by total per capita Medicaid expenditures in 2007. 

There is a very strong relationship between actual ARRA Medicaid payouts through July 

3 and estimated non-cyclical ARRA Medicaid payouts, as shown in Figure 2.5

 Note that in 

Figure 2, as in all scatter plots, the size of a circle is proportional to a state’s population. The 

difference between the two values partly reflects the fact that a state’s actual payouts depend 

directly on a state’s current employment situation.6

 

 The estimated payouts, in contrast, are 

calculated with variables determined prior to the beginning of the recession. 

5 We focus on spending data from July because the latest employment data available for our analysis is also from 

July. 

6 See Section III for more details. Differences between a state’s actual and estimated ARRA Medicaid payouts also 

reflect changes in Medicaid spending between 2007 and the present.
5

0

50

100

150

0 50 100 150

Estimated non-cyclical ARRA Medicaid payouts, per capita ($)

Sources: Centers for Medicare and Medicaid Services. Data Compendium; Recovery.gov.

Note: Estimated non-Cyclical ARRA Medicaid payouts are 0.062 * (Medicaid spending in FY 2007).

Size of circle proportional to 2008 state population.

The regression line is (actual payouts) = 14.6 + 0.9 * (estimated payouts).

The coefficient on estimated payouts is significant at the 99% confidence level. The R-squared is 0.79.

Actual ARRA Medicaid payouts, per capita ($)

Figure 2. Estimated and Actual ARRA Medicaid Payouts

Although the estimated non-cyclical ARRA Medicaid payouts are clearly more 

exogenous than actual ARRA Medicaid payouts, there are important differences between states 

that were high Medicaid spending and states that were low Medicaid spending states. For 

example, Figure 3 shows the strong regional component to the estimated non-cyclical ARRA 

Medicaid payouts. However, it also shows that there is also variation within regions and that 

states that might seem relatively similar have different estimated non-cyclical ARRA Medicaid 

payouts. For example, New York has a higher value than New Jersey or California, states 

somewhat similar to New York. We will show that the correlation is robust to accounting for 

many important observable differences between high and low spending states. Even so, we 

cannot rule out the possibility that there is some other confounding variable driving the 

correlation. 
6

Estimated ARRA Medicaid payouts

($ per capita)

Figure 3. Estimated Non-cyclical ARRA Medicaid Payouts by State

Source: Centers for Medicare and Medicaid Services. Data Compendium. 2008.

Note: The data represent 0.062 multiplied by total per capita Medicaid expenditures in 2007.

III. INSTITUTIONAL DETAILS OF MEDICAID GRANTS

Before turning to our main findings, we describe some of the institutional details of the 

Medicaid grants and argue why differences in grants that result from a state’s 2007 Medicaid 

spending are less related to a state’s economic performance than is the total size of a state’s fiscal 

relief. 

Medicaid is a government program that provides health insurance for persons and 

families with incomes below a certain threshold or who meet other requirements. Both the 

eligibility requirements and the insurance coverage vary across states. By statute, the Federal 

government reimburses states for between 50 and 83 percent of their Medicaid expenditures, as 

determined by the Federal Medical Assistance Percentages (FMAP).7

 

 Each state’s FMAP is 

recalculated each fiscal year based on the state’s per capita income relative to the national 

average, with poorer states receiving higher reimbursement rates. Thus, states that have lower 

average incomes, more recipients of Medicaid per capita, or more generous benefits will receive 

larger per capita matching funds from the Federal government. 

7 See Assistant Secretary for Planning and Evaluation (2007) for details of the FY 2009 FMAP determination. 
7

ARRA made three changes to the FMAP calculation.8 First, the baseline FMAP, based 

on states’ income relative to other states, may not decrease for FY 2009-FY 2011:Q1. Second, 

for October 2008 through December 2010, the FMAP is increased by 6.2 percentage points 

above the baseline for every state.9

 The additional match is applied retroactively from passage in 

mid-February back to October 2008, making part of the transfer purely lump-sum. Finally, states 

receive a further increase in their quarterly FMAP between October 2008 and December 2010 

based on the change in the state’s unemployment rate relative to its lowest three-month average 

unemployment rate since January 2006. To qualify for the ARRA changes, states must maintain 

“eligibility standards, methodologies, [and] procedures” of their Medicaid programs not more 

restrictive than existed on July 1, 2008.10

States gained access to ARRA Medicaid funds early in 2009 and were able to use them 

for a variety of purposes. On February 25, the ARRA-enhanced Medicaid funds were made 

available to states for the first two quarters of fiscal year 2009.

 Program benefits may, however, change.

11 States can draw down these 

funds the same way that they receive regular Medicaid matching funds, as they submit receipts. 

Importantly, the changes to FMAP made by ARRA were intended to boost the level of 

discretionary funds available to states, and not simply to relieve Medicaid burdens. Because an 

increase in FMAP reduces required payments by states, the additional funds are to a large degree 

fungible. Aside from mandating that states must maintain Medicaid eligibility standards and that 

“any amounts attributable (directly or indirectly)” to the increase in a state’s FMAP may not be 

“deposited or credited into any reserve or rainy day fund of the State,” ARRA does not contain 

language substantially limiting how the funds are used.

12

The increase in the FMAP was in the earliest versions of the bill from mid-January and 

remained through passage on February 13, suggesting that the most appropriate period to begin 

analysis is January if state governments’ revenue expectations were affected by Congress’s 

activities. A draft version of the House bill released on January 15, 2009 allocated $87 billion to

 8 See U.S. Congress (2009). Section 5001. 

9 Under ARRA the 0.83 cap on the FMAP is also removed.

10 See U.S. Congress (2009). Section 5001.

11 See Department of Health and Human Services. Centers for Medicare and Medicaid Services (2009b).

12 See U.S. Congress (2009). Section 5001.
8

increase the FMAP by 4.8 percentage points, a feature highlighted in the House Appropriations 

Committee press release accompanying the draft.

13 Indeed, the original House and Senate 

versions, passed on January 28 and February 10, respectively, had this component of aid to 

states, with an increase of 4.9 percentage points in the House version and 7.6 percentage points 

in the Senate version.14

Here we present evidence that states that received higher estimated ARRA Medicaid 

payouts experienced a larger net growth in their employment to population ratio. Figure 4 

documents this correlation. The horizontal axis plots the estimated amount of money (per capita) 

that a state received, excluding transfers related to a state’s economic performance. The vertical 

axis shows the change in the percent of the state’s population that was employed from January 

2009 to July 2009.

 The use of an FMAP increase to provide aid to states only six years 

earlier further increased the plausibility that such a provision would make it into the final bill in 

this case. Because the details of the FMAP expansion were already apparent in January, our 

primary analysis focuses on changes in employment from January to July 2009 (the most recent 

month for which we have employment data by state), although our results are generally not 

sensitive to considering other time horizons.

IV. SUGGESTIVE CORRELATIONS

15 Because the outcome variable is measured more precisely for states with 

larger populations, the best-fit line weights states by their population size, although the results 

are somewhat larger and still statistically significant if we do not weight.16

 

 In Figure 4, the size 

of the circle represents the size of a state’s population. 

13 Obey (2009).

14 See U.S. House (2009) for the House version and U.S. Senate (2009) for the Senate version. 

15 The data come from the Bureau of Labor Statistics Current Employment Statistics, an establishment-based survey 

which asks firms to report the number of employees on payroll during the pay period that includes the 12th day of the 

reference month. Note that, since this data is an establishment survey, an individual can actually be counted more 

than once, so “per capita employment” would be a more accurate term. 

16 When we do not weight, the coefficient on estimated payouts is 0.0106, and the result is significant at the 99% 

level. We also obtained a direct measure of the standard error of the state-level employment from the BLS. When 

we use this measure to construct weights, the results are very similar to the population weighted results. Here, the 

coefficient on estimated payouts is 0.0076. The result is significant at the 99% confidence level.
9

 

-3

-2

-1

0

1

0 50 100 150

Estimated non-cyclical ARRA Medicaid payouts, per capita ($)

Sources: Centers for Medicare and Medicaid Services. Data Compendium; Bureau of Labor

Statistics; CEA calculations.

Note: Size of circle proportional to 2008 state population.

The regression line is (change in employment) = -1.3 + 0.0076 * (estimated payouts).

The coefficient on estimated payouts is significant at the 99% confidence level.

The R-squared is 0.29.

Percent of state population, January - July

Figure 4. Change in Nonfarm Employment

The clear message from the figure is that states that received more of this type of relief 

experienced better labor market outcomes than states that received less. The magnitude of this 

relationship is large: the figure implies that receiving $120 per capita instead of $60 per capita is 

related to a state the size of Michigan gaining about 45,600 jobs.17

Although our use of Medicaid payouts based upon past Medicaid expenditures reduces 

the concern that correlation does not imply causation, we caution that interpreting this evidence 

as indicating causality remains problematic. However, this relationship does not appear to be

driven by some important underlying differences between states that received more money and 

states that received less. First, in the six months before the details of ARRA became clear, states 

that later received more relief lost essentially the same number of jobs per capita as states that 

 

17 We calculate this number as follows. We multiply the difference between $60 per capita and $120 per capita by 

the value from the regression line in the scatter plot (0.0076), divided by 100 so that employment changes are also in 

per capita terms. We then multiply this number by the size of Michigan’s population, approximately 10 million, to 

arrive at 45,600. As stressed above, these results are correlations and should not be interpreted as causal 

relationship. 
10

later received less; it is not the case that high Medicaid spending states were hit less hard by the 

recession in the half year before ARRA was passed.18

Second, using multivariate regression analysis to account for differences between states 

such as geographic location, industry composition, and population density changes does not 

affect the basic correlation.

 

19 For example, Figure 5 shows the correlation between estimated 

ARRA Medicaid payouts and change in employment from January to July, 2009 after we take 

into account differences between the nine census regions. The figure shows a similar positive 

correlation between a state’s being a high Medicaid spender and its change in employment 

between January and July even after taking into account a state’s region. 

 

-3

-2

-1

0

1

-50 0 50 100

Estimated ARRA Medicaid payouts, per capita, relative to regional average

Sources: Centers for Medicare and Medicaid Services. Data Compendium; Bureau of Labor Statistics.

Note: Size of circle proportional to 2008 state population.

The regression coefficient on estimated payouts is 0.0078 and is significant at the 99% confidence level.

Percent of state population

Figure 5. Change in Nonfarm Employment: Region Effects

18 Specifically, when we repeated the correlations presented above using per capita employment change from June 

2008 – December 2008, we find that the correlation is small in magnitude and not statistically different from 0. 

When we add control variables described below, the results are similar.

19 The variables we considered are the nine census regions, lagged change in employment, industry composition, 

population density, share of workers covered by a union, total state population, and the size of the housing bubble in 

the state. We experimented with using every combination of these control variables and found that the correlation 

was always positive. We also included a measure of the number of jobs that a state would have been expected to 

lose based on its 2007 industry composition, and continued to find a strong positive relationship.
11

Finally, we note that differences in 2007 per capita Medicaid spending are driven by (1) 

more residents per capita being Medicaid beneficiaries or (2) the average Medicaid beneficiary 

having more spending devoted to her. These two sources of variation are empirically distinct 

and mildly negatively correlated across states: states that have more beneficiaries tend to spend 

somewhat less per beneficiary. We find that there is a positive correlation between both (1) and 

(2) and a state’s growth in employment. Because these two reasons why states were high 

Medicaid spenders yield similar conclusions, it is less likely that the correlation is driven by 

underlying differences between high and low Medicaid spending states. Other robustness checks 

include ensuring that the correlation is robust to dropping any single state from the analysis and 

is not dependent on the specific time window chosen.20

Time series evidence of state and local government receipts and expenditures suggests 

that Federal grants-in-aid may have helped avoid further cuts in government expenditure. Figure 

6 shows the time series of expenditures, receipts, and receipts minus Federal grants-in-aid (all 

transfers from the Federal government to state and local governments, including Medicaid, 

transfers for welfare payments and social services).

 

V. IMPORTANCE OF STATE RELIEF FOR GOVERNMENT EMPLOYMENT AND BUDGETS

The above analysis shows that there is a strong and positive relationship between state 

fiscal relief and relative net job creation. Yet, for fiscal relief to affect economic outcomes, it has 

to affect state budgetary decisions. Here, we discuss the impact that fiscal relief had on state 

budgets, and how that may have led to the observed employment outcomes. 

21

 

 The final quarter in 2008 and the first 

quarter in 2009 were the first quarters since 1952 where nominal consumption expenditure for 

state and local governments declined. While total receipts minus Federal grants-in-aid continued 

to fall for the first two quarters of 2009, the growth rate of total receipts was positive during 

these two quarters. This difference between the behavior of the two series reflects the important 

20 There is a significant positive correlation when we consider the following time periods for our employment 

change: January to June 2009, February to July 2009, January to April 2009, and April to July 2009.

21 See U.S. Department of Commerce. Bureau of Economic Analysis (2009b), Table 3.24U contains a complete list 

of the components of Federal grants-in-aid.
12

role of Federal transfers (including the Medicaid component in ARRA) in helping to alleviate the 

state fiscal crisis during the recession.

-6%

-4%

-2%

0%

2%

4%

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Consumption Expenditures

Receipts less Federal grants-in-aid

Receipts

Figure 6. State and Local Government Growth Rates

Quarter-on-quarter growth rate 

Source:U.S. Department of Commerce. Bureau of Economic Analysis.

2008Q4

2009Q2

Next, we show that the size of the state fiscal relief was substantial but generally less than 

states’ budget gaps. The state fiscal relief component of ARRA is comprised of both the higher 

Federal share of Medicaid spending and the State Fiscal Stabilization Fund from the Department 

of Education. Figure 7 compares the size of total funds from these programs that had been 

transferred to each state through July 3 with the state’s maximum reported fiscal 2009 budget 

gap.22 While these transfers were sizeable in magnitude, in 35 states they are smaller than the 

reported budget gap. This means that states could have used the funds to increase their rainy day 

funds only if they reduced expenditures or increased taxes in the same fiscal year. Given that 

states underwent deep expenditure cuts in 2009 (42 states cutting their fiscal year 2009 budgets 

by $31.6 billion through June 2009), it seems unlikely that this would have occurred.23

 

22 We use data from July 3 because most states end their fiscal year at the end of June. Data on the state budget gaps 

is from the National Conference of State Legislatures (2009b). 

23 Budget cut data from National Governors Association and National Association of State Budget Officers (2009). 

 
13

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2,000

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AK

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MTNCND

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NM

NVNY

OH

OK

OR

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SCSD

TN

TX

UT

VA

VT

WA

WI

WVWY

ARRA State Transfers (Medicaid and State 

Fiscal Stabilization Fund)

Estimated FY 2009 Budget Gap

Figure 7. Budget Gaps and ARRA Transfers to States

Sources: National Conference of State Legislatures (2009b); recovery.gov; CEA calculations.

Millions of $

CA ARRA Transfers: 5,706

CA Budget Gap: 19,639

We can also examine directly the relationship between ARRA Medicaid transfers and 

relative increases in a state’s total balances, a comprehensive measure of state savings which 

contains both the rainy day fund and the state’s ending balance. Figure 8 plots the estimated 

non-cyclical ARRA Medicaid payouts against changes in states’ total balances, in per capita 

terms.24 If states were saving a substantial fraction of their fiscal relief, we would expect to see a 

positive correlation between the total amount that the Federal government transferred to a state 

and the change in its total balances. Instead, the best-fit line is slightly downward-sloping, the 

opposite of what one would expect if larger transfers resulted in total balance build-up.25 When 

we use multiple regression techniques to account for some of the differences between high and 

low Medicaid spending states, we see a similar negative correlation.26

 

 Although one must be 

24 For this analysis, we exclude Alaska because the change in its total balances was more than ten times larger than 

any other state on a per capita basis. When we include Alaska, we have a similar negative correlation. Data for this 

analysis comes from National Governors Association and National Association of State Budget Officers (2009).

25 The correlation is similar if we restrict attention to states’ rainy day funds rather than their total balances. Data are 

the most recent estimates published in National Governors Association and National Association of State Budget 

Officers (2009). Because these data are estimates, they may not reflect final totals. Our results are similar if we 

exclude states that do not have fiscal years that end in June (New York, Texas, Alabama, and Michigan). 

26 As before, the variables considered are the nine census regions, lagged change in employment, industry 

composition, population density, share of workers covered by a union, total state population, and the size of the 

housing boom in the state. 
14

cautious in interpreting this correlation, these results provide some suggestive evidence that 

states do not appear to be saving the money that they received. 

-400

-300

-200

-100

0

100

0 50 100 150

Estimated non-cyclical ARRA Medicaid payouts, per capita ($)

Sources: Centers for Medicare and Medicaid Services. Data Compendium; National Association

of State Budget Officers; CEA calculations.

Note: Excludes Alaska. Total balances include balances at the end of the fiscal year and

balances in budget stabilization funds. Size of circle proportional to 2008 state population.

The regression line is (change in balances) = -53.1 - 0.3 * (estimated payouts).

The coefficient on estimated payouts is not significant. The R-squared is 0.01.

Change in total balances, per capita ($)

Figure 8. Total Budget Reserve Balances

Many state governors have given examples of how they have used the fiscal aid to avoid 

expenditure reductions. For example, Governor Jan Brewer of Arizona noted her commitment to 

use “Arizona’s portion of Federal funds to help avoid massive cuts to [its] higher education 

system.”27 Governor Martin O’Malley of Maryland told of “looking down the barrel of those 

hard budget decisions” and being “forced to articulate a budget that proposed devastating cuts.”28 

Those sentiments were echoed by Governor Deval Patrick of Massachusetts. He described how 

the fiscal relief would help “Massachusetts sustain critical safety net programs and services 

while avoiding laying off thousands of teachers, public safety workers, human service providers 

and other government employees.”29

Employment data confirm this narrative evidence. As states reduced budget cuts, we 

would expect to see fewer layoffs in the areas of public safety, education, health care and other 

 

27 See Brewer (2009).

28 See O’Malley (2009).

29 See Patrick (2009).
15

sectors where state governments provide a large amount of financial support. Figure 9 

demonstrates a positive relationship between the estimated ARRA payments and the growth in 

employment in these sectors. We do not see a similar correlation in the period before ARRA 

was passed. Results are similar when we take into account observable differences between 

states, although as before we cannot be sure that other differences between states are not driving 

the result.30 Comparing Figures 9 and 4 indicates that about one-quarter to one-half of the 

relationship between estimated ARRA Medicaid payments and total employment results from 

jobs created or saved in government-related sectors. 

-0.4

-0.2

0.0

0.2

0.4

0 50 100 150

Estimated non-cyclical ARRA Medicaid payouts, per capita ($)

Sources: Centers for Medicare and Medicaid Services. Data Compendium; Bureau of Labor

Statistics; CEA calculations.

Note: Excludes Louisiana and Wyoming due to data availability. Size of circle proportional to

2008 state population.

The regression line is (change in employment) = -0.2 + 0.003 * (estimated payouts).

The coefficient on estimated payouts is significant at the 99% confidence level.

The R-squared is 0.20.

Percent of state population: state, local, health and education employees, January - July

Figure 9. Change in Government Employment

Thus, several pieces of evidence support the idea that state fiscal relief helped create jobs 

through preventing cuts to services and avoiding tax increases. First, logic suggests that states 

are unlikely to build up their total balances while cutting programs. Second, statistical evidence 

suggests that states that received larger estimated ARRA Medicaid payouts did not build up their 

 

30 The variables we considered are the same as above: the nine census regions, lagged change in employment, 

industry composition, population density, share of workers covered by a union, total state population, and the size of 

the housing boom in the state. We also find a similar positive and significant correlation when we restrict attention 

to just government workers. When we do not weight by a state’s population, we find a similar positive relationship 

between estimate ARRA Medicaid payouts and growth in employment in public safety, education, health care and 

other sectors where state governments provide a large amount of financial support. The result, however, is 

somewhat smaller in magnitude and is not statistically significant.
16

rainy day funds. Third, anecdotal evidence suggests that states did save jobs using ARRA state 

fiscal relief. Finally, there is a strong relationship between greater estimated ARRA Medicaid 

payments and growth in jobs related to government. 

VI. CONCLUSION

State fiscal relief has been an important component of Recovery Act spending. This 

money went out the door quickly and played a critical role for the states, which are required to 

operate with a balanced budget. The CEA analysis clearly shows that states that received more 

fiscal aid experienced better employment outcomes in the first six months of ARRA 

implementation. Furthermore, this analysis suggests that states did not hoard recovery dollars in 

rainy day funds and that the best available evidence indicates that more recovery dollars resulted 

in better outcomes for crucial state programs. 

There are several caveats to our analysis. First, we only have six months of data on 

which we can conduct our analysis. As more data become available and the existing data are

revised, the jobs portrait may become clearer. Second, the analysis omits cross-state spillovers, 

which would lead to missing some of the relationship between fiscal relief in one state and 

increased jobs in the rest of the country, as well as other factors. Finally, although the 

correlations are robust to accounting for many important differences between states, there may 

be other important differences between states that spend large amounts on Medicaid that would 

affect the results. 
17

DATA APPENDIX

Primary Outcome Variable. Our main outcome variable is the change in a state’s seasonally 

adjusted employment from January 2009 to July 2009, divided by its 2008 population. The data 

come from the Bureau of Labor Statistics (BLS) Current Employment Statistics (CES), an 

establishment-based survey which asks firms to report the number of employees on payroll 

during the pay period that includes the 12th day of the reference month. We also focus on 

employment in certain industries (government, health, or education). These data also come from 

the CES and are seasonally adjusted.

Rainy Day Fund Information. Data for a state’s rainy day funds are taken from the June 2009 

National Governors Association and National Association of State Budget Officers “The Fiscal 

Survey of States.” 

ARRA Spending Data. We use data from the US government’s official website, recovery.gov, 

through July 3, 2009. 

2007 Medicaid Spending Data. We use data from Centers for Medicare and Medicaid Services 

Data Compendium 2008 Edition table VII.1 for data on total 2007 spending. For data on the 

number of Medicaid beneficiaries in each state, we use the Medicaid Statistical Information 

System State Summary Datamart.

Control variables. 

Region effects: we use the 9 census regions 

Lagged employment change: The lagged employment is a state’s seasonally adjusted 

change in employment level from June to December (the 6 months before the period of 

interest).31

GDP per capita: A measure of a state’s 2006 per capita GDP. Data is from the Bureau of 

Economic Analysis.

House price appreciation: We use the percent change in the state’s housing price index 

as measured by the Federal Housing Finance Agency House Price Index from 1999Q4 to 

2004Q4 as a way of controlling for the size of a state’s housing boom. 

32

Employment manufacturing share: A measure of the state’s concentration in 

manufacturing from 2005-2007.

 

33

 

31 By December there was already public discussion of a stimulus package involving aid to states. If states began to 

respond to expected stimulus funds before January 12th, then including lagged employment change through January 

would bias our coefficient of interest downward. For this reason we use the June to December period as the preARRA trend in all of our regressions.

32 U.S. Department of Commerce. Bureau of Economic Analysis (2009a).

33 U.S. Department of Commerce. Bureau of the Census (2009a) and U.S. Department of Commerce. Bureau of the 

Census (2009b). 
18

State 2008 population and population density: Data is from the U.S. Census. 

Union share: Share of workers affiliated with a union in 2007.34

 

34 See U.S. Department of Labor (2009b). 
19

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