EXECUTIVE OFFICE OF THE PRESIDENT

COUNCIL OF ECONOMIC ADVISERS

THE ECONOMIC IMPACT OF THE 

AMERICAN RECOVERY AND REINVESTMENT ACT OF 2009 

FIRST QUARTERLY REPORT

SEPTEMBER 10, 2009
THE ECONOMIC IMPACT OF THE AMERICAN RECOVERY AND REINVESTMENT ACT OF 2009 

FIRST QUARTERLY REPORT

EXECUTIVE SUMMARY

As part of the unprecedented accountability and transparency provisions included in the 

American Recovery and Reinvestment Act of 2009 (ARRA), the Council of Economic Advisers 

was charged with providing to Congress quarterly reports on the effects of the Recovery Act on 

overall economic activity, and on employment in particular. In this first report, we provide an 

assessment of the effects of the Act in its first six months. 

Evaluating the impact of countercyclical macroeconomic policy is inherently difficult 

because we do not observe what would have happened to the economy in the absence of policy. 

And the sooner the evaluation is done after passage, the less data one has about key economic 

indicators. Any estimates of the impact of the ARRA at this early stage must therefore be 

regarded as preliminary and understood to be subject to considerable uncertainty. In this regard, 

it is important to note that there has not yet been any direct reporting by recipients of ARRA 

funds on job retention and creation. Such direct reporting data will be evaluated and 

incorporated in future reports. 

Because of the inherent difficulties in the analysis, we approach the task of estimating the 

impact of the Recovery Act from a number of different directions. Our multi-faceted analysis 

suggests that the ARRA has had a substantial positive impact on the growth of real gross 

domestic product (GDP) and on employment in the second and third quarters of 2009. That 

various approaches yield similar estimates increases the confidence one can have in the results. 

Among the key finding of the study are: 

 As of the end of August, $151.4 billion of the original $787 billion has been outlaid or 

has gone to American taxpayers and businesses in the form of tax reductions. An 

additional $128.2 billion has been obligated, which means that the money is available to 

recipients once they make expenditures. The areas where stimulus has been largest in the 

first six months are individual tax cuts, state fiscal relief, and aid to those most directly 

hurt by the recession. That recovery funds have gone out rapidly certainly increases the 

probability that the Act has been effective in its first six months. 

 Following implementation of the ARRA, the trajectory of the economy changed 

materially toward moderating output decline and job loss. The decomposition of the 

GDP and employment change by components or sector suggests that the ARRA has 

played a key role in this change of trajectory. 

 Estimates of the impact of the ARRA made by comparing actual economic performance 

to the predictions of a plausible, statistical baseline suggest that the Recovery Act added 

roughly 2.3 percentage points to real GDP growth in the second quarter and is likely to 

add even more to growth in the third quarter. 
 This analysis indicates that the ARRA and other policy actions caused employment in 

August to be slightly more than 1 million jobs higher than it otherwise would have been. 

We estimate that the Act has had particularly strong effects in manufacturing, 

construction, retail trade, and temporary employment services. The employment effects 

are distributed across states, with larger effects in states more severely impacted by the 

recession. 

 In addition to the estimates based on statistical projection, we provide estimates of the 

effects of the ARRA from standard economic models. Both our multiplier analysis and 

estimates from a wide range of private and public sector forecasters confirm the estimates 

from the statistical projection analysis. There is broad agreement that the ARRA has 

added between 2 and 3 percentage points to baseline real GDP growth in the second 

quarter of 2009 and around 3 percentage points in the third quarter. There is also broad 

agreement that it has likely added between 600,000 and 1.1 million to employment 

(again, relative to what would have happened without stimulus) as of the third quarter. 

 Fiscal stimulus appears to be effective in mitigating the worldwide recession. Nearly 

every industrialized country and many emerging economies responded to the severe 

financial crisis and recession by enacting fiscal stimulus. However, countries differed 

greatly in the size of their fiscal actions. We find that countries that adopted larger fiscal 

stimulus packages have outperformed expectations relative to those adopting smaller 

packages. 

 State fiscal relief was one of the ways in which the Recovery Act was able to provide 

support for the economy most quickly, and it played a critical role in helping states facing 

large budget shortfalls because of the recession. Our analysis indicates that state fiscal 

relief increased employment at the state level relative to what would have happened 

without stimulus. Thus, this analysis both provides evidence of how one particular type 

of fiscal stimulus impacts the economy and corroborates the more fundamental finding 

that fiscal stimulus in general is an effective countercyclical tool. 
CONTENTS

 PAGE

I. INTRODUCTION 1 

II. THE PROGRESS OF SPENDING AND TAX REDUCTIONS UNDER THE ACT

 

 4 

 

III. EVIDENCE OF EFFECTS FROM THE BEHAVIOR OF GDP AND EMPLOYMENT 7 

IV. ESTIMATES OF EFFECTS FROM ECONOMIC MODELS 23

V. EVIDENCE OF EFFECTS FROM THE EXPERIENCE OF MANY COUNTRIES 27

VI. THE IMPACT OF STATE FISCAL RELIEF 33

VII. CONCLUSION 39

REFERENCES 41

I. INTRODUCTION

The American economy slipped into recession in December 2007. What began as a 

relatively moderate downturn changed dramatically following the severe disruptions in U.S. and 

world financial markets in the fall of 2008. By November, employment was declining at a rate 

of more than half a million jobs per month, and credit markets were stretched almost to the 

breaking point. As the economy entered 2009, the decline accelerated further, with job loss in 

January reaching almost three-quarters of a million. There were genuine fears that the United 

States and world economy were on the verge of a depression. 

Less than a month after his inauguration, President Obama signed into law the American 

Recovery and Reinvestment Act of 2009 (ARRA). This act, together with a number of 

emergency measures taken by the Treasury and the Federal Reserve to stabilize financial 

markets, was designed to rescue an economy in freefall and provide a lift to aggregate demand at 

a time when the economy needed it desperately. The Recovery Act provided $787 billion of 

fiscal stimulus, concentrated in 2009 and 2010. At roughly 51⁄2 percent of GDP (2 percent in 

2009, 21⁄2 percent in 2010, and about 1 percent in 2011 and beyond), the action was the boldest 

countercyclical fiscal action in American history.1

As part of the unprecedented accountability and transparency provisions included in the 

Act, the Council of Economic Advisers (CEA) was charged with providing to Congress quarterly 

reports on the effects of the Recovery Act on overall economic activity, and on employment in 

particular. In this first report, we provide an assessment of the effects of the Act in its first six 

months of operation. 

It is well understood among experts that policy evaluation is difficult. Estimating the 

impact of countercyclical macroeconomic policy is particularly difficult because we do not 

observe what would have happened to the economy in the absence of policy. As the prominent 

economic forecaster Mark Zandi has put it, “It is important to note that estimating the economic 

impacts of the fiscal stimulus is not an accounting exercise .... It is not feasible to identify and 

count each job that results from the stimulus.”2

 Furthermore, the sooner the evaluation is done 

after passage, the less data one has about key economic indicators. For these reasons, any 

estimates of the impact of the ARRA at this early stage must be regarded as preliminary and 

understood to be subject to substantial uncertainty. 

                                                           

1

 The $787 billion figure is from Congressional Budget Office (2009a). Adding their estimate of the stimulus in 

fiscal year 2009 and one-quarter of the estimate for fiscal 2010 yields $285 billion in calendar year 2009, or about 2 

percent of GDP. A similar procedure yields $333 billion in 2010, or about 21⁄2 percent of GDP, and $169 billion in 

2011 and beyond, or about 1 percent of annual GDP. 

2

 Zandi (2009). 
2 

Because of the inherent difficulties in the analysis, we approach the task of estimating the 

impact of the Recovery Act from a number of different directions. We use evidence from the 

overall path of the economy, economic models, and cross-country and cross-state comparisons. 

The goal is to provide a wide range of cross-checks and alternative estimates. That various 

approaches yield similar estimates increases the confidence one can have in the results. 

Our multi-faceted analysis suggests that the ARRA has had a substantial positive impact 

on real GDP growth and on employment in the second and third quarters of 2009. The ARRA is 

estimated both by the CEA and a wide range of private analysts to have added 2 to 3 percentage 

points to real GDP growth (at an annual rate) in the second quarter of 2009, and potentially an 

even larger amount to growth in the third quarter. Consistent with this, a range of estimation 

procedures indicates that employment in the second quarter was 300,000 to 500,000 greater than 

it otherwise would have been because of the Recovery Act. By August, two-thirds of the way 

through the third quarter, employment is estimated to be between 600,000 and 1.1 million higher 

than it otherwise would have been. 

Of course, current economic indicators show that the U.S. economy is still in recession: 

real GDP fell at a 1 percent annual rate in the second quarter and the most recent employment 

report showed that employment declined by 216,000 in August. CEA and others’ estimates of 

the effect of the Recovery Act imply that these declines in output and employment would have 

been significantly worse in the absence of fiscal stimulus. 

As discussed above, the report marshals a wide range of evidence to support these 

conclusions. We begin with a summary of the spending and tax reductions that have occurred 

under the ARRA over its first six months. We find that as of the end of August, $151.4 billion of 

the original $787 billion has been outlaid or has gone to American taxpayers and businesses in 

the form of tax reductions. An additional $128.2 billion has been obligated, which means that 

the money is available to recipients once they make expenditures. That recovery funds have 

gone out rapidly certainly increases the probability that the Act has been effective in its first six 

months. 

We then examine the behavior of GDP and employment in detail. We find that the 

trajectory of the economy has changed: job loss and output declines have moderated 

substantially. We also find that the decomposition of GDP and employment by components or 

sector suggest that the ARRA has played a key role in the change of trajectory. We supplement 

this analysis with an examination of the behavior of GDP and employment relative to a plausible, 

statistically-determined baseline. We find that actual and expected behavior is substantially 

better in the second two quarters of 2009 than would have been predicted based on the past 

behavior of the two series. This analysis provides strong suggestive evidence that the range of 

policy actions taken early in the year, including the ARRA, has had a substantial impact on 
3

economic conditions. 

In the course of this analysis, we use a variety of straightforward statistical procedures to 

allocate the estimates of job creation and retention to particular sectors and states. This analysis 

provides a first pass at the important issue of the industrial and geographic impact of the 

Recovery Act. We estimate that the Act has had particularly strong effects in manufacturing, 

construction, retail trade, and temporary employment services. The employment effects are 

distributed across states, with larger effects in states more severely impacted by the recession. 

Third, we consider estimates of the impact of the ARRA from standard economic models. 

We incorporate the data on actual outlays and tax changes under the Act in the second and third 

quarters of 2009 into the multiplier analysis used by the CEA to predict the impact on GDP and 

employment. We compare our results with those of prominent private sector and public sector 

analysts. This analysis indicates that much of the change in macroeconomic behavior in the last 

six months is attributable to the ARRA. 

Fourth, we examine the U.S. experience in international perspective. Nearly every 

industrialized country and many emerging economies responded to the severe financial crisis and 

recession by enacting fiscal stimulus. However, countries differed greatly in the size of their 

fiscal actions. The United States, with a program of roughly 2 percent of GDP in 2009, was 

above average; China at 2.6 percent and Korea at 3.0 percent were substantially larger; France at 

0.6 percent and Italy at 0.1 percent were noticeably smaller. We analyze how the size of the 

stimulus in a country is correlated with the developments in mid-2009, relative to what was 

forecast back in November. We find that countries that adopted larger fiscal stimulus packages 

have outperformed expectations relative to those adopting smaller packages. Thus, the crosssection analysis provides further evidence that fiscal stimulus is leading to improved economic 

performance both in the United States and abroad. 

Fifth, and finally, we look in detail at the impact of one part of the ARRA: state fiscal 

relief. Because this was an area where funds could be disbursed quickly, fiscal support for the 

states constituted one-quarter of ARRA spendout through the end of August. CEA analysis 

indicates that this relief successfully increased employment at the state level relative to the nostimulus baseline, and that it did so by affecting state budgetary decisions. In this way, our 

analysis of state fiscal relief both provides evidence of how this particular type of fiscal stimulus 

impacts the economy, and corroborates the more fundamental finding that fiscal stimulus in 

general is an effective countercyclical tool. 

This report is the first of a series that the Council of Economic Advisers will be preparing 

on the American Recovery and Reinvestment Act of 2009. Beginning in October, recipients of 

ARRA funds will begin providing direct reports of job retention and creation. Our next quarterly 
4 

report will include an evaluation of this direct reporting employment data and consider 

techniques for incorporating these data into our estimation.3

 Each report will, like this first one, 

provide rigorous analysis of the impact of the path-breaking Recovery Act of 2009. 

II. THE PROGRESS OF SPENDING AND TAX REDUCTIONS UNDER THE ACT

The first step in evaluating the effects of the ARRA is to analyze the data on spending 

and tax reductions that have occurred under the Act. It is certainly possible that the Act could 

have effects even if no spending or tax changes had actually occurred. For example, its passage 

could have affected confidence, and expectations of a tax cut in the future could affect spending 

today. But, it is far more likely that the Act has had significant impact if funds have actually 

been spent and tax cuts have actually reached consumers. 

 The data on both spending and tax relief are available on the Recovery.gov website. The 

outlays and obligations by agency are available weekly and the tax reduction data are available 

monthly.4

 Outlays represent payments made by the government. Those funds represent 

spending that has already occurred. Obligations represent funds that have been made available 

but not necessarily outlaid, such as for a highway project where the builder must complete the 

work properly to get the final payment. One can certainly make the case the obligations can 

generate economic activity because recipients may begin spending as soon as they are certain 

funds are available. 

 Table 1 shows outlays, obligations, and tax reductions as of the ends of March, June, and 

August. Not surprisingly, as of the end of March, just six weeks after the Act was passed, only 

$11.8 billion of outlays and tax reductions had occurred, though an additional $21.9 billion of 

spending had already been obligated. By the end of June, the sum of outlays and tax reductions 

was $99.8 billion, with an additional $101.5 billion of spending obligated. As of the end of 

August, the sum of outlays and tax reductions was $151.4 billion, with another $128.2 billion 

obligated. 

                                                           

3

 Importantly, recipient reports will not encompass all ARRA spending. Specifically, the reports due to begin in 

October will provide employment impacts only for those projects and activities funded by state fiscal relief grants 

and government investment spending. The job impacts associated with the remaining recovery funds, such as funds 

going to individual tax cuts, business tax incentives, and aid to directly impacted individuals, will not be captured. 

Furthermore, recipients are only required to report on direct jobs created or retained by the entities receiving 

recovery funds (for example, the general contractor for a road project) and not additional job impacts that may be 

occurring beyond that (for example, at sub-contractors or suppliers to the general contractor). And of course, they 

will not capture jobs created by the additional spending resulting from the higher incomes of the workers hired. 

Thus, the recipient reports will not provide an easy way of finding the overall effects of the Act. 4

 The outlays and obligations data are based on weekly reports by the relevant agencies. The tax reduction estimates 

are based on the Department of the Treasury Office of Tax Analysis (OTA) tax simulation model for the effect of 

the ARRA tax provisions. The OTA will not have comprehensive data on the 2009 tax filings until June 2010. 
5

Marcha Juneb Augustc

Outlays 8.6 56.3 88.8

Obligations 30.5 157.8 217.0

Tax Reductions 3.2 43.5 62.6

Sum of Outlays and Tax Reductions 11.8 99.8 151.4

Notes: a. Data on outlays and obligations are for March 27.

b. Data on outlays and obligations are for June 26.

c. Data on outlays and obligations are for August 28.

Table 1. Outlays, Obligations, and Tax Reductions

Through the end of 

Billions of Dollars

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

Analysis) based on the Mid-Session Review.

The August numbers suggest that total outlays plus tax cuts will equal approximately $75 

billion for the third quarter of calendar 2009. If this prediction is met, between one-fifth and 

one-quarter of the total $787 billion included in the Act will have been spent by the end of the 

2009 fiscal year. This is approximately what was projected by the Congressional Budget Office 

(CBO) when the Act was passed.5

To some degree, the categorization of stimulus into outlays versus tax reductions is 

largely technical. For example, the Making Work Pay tax credit, which reduced taxes for 95 

percent of households, is treated as a tax cut, while the $250 extra payment to seniors and 

veterans is treated as an outlay. Yet, both are thought to affect economic activity by putting 

more money into the hands of consumers. For this reason, it is useful to consider a more 

functional decomposition. The decomposition is not only interesting in its own right, but is 

necessary for our later multiplier analysis of the impact of the program. 

We divide the total dollars of stimulus expended to date into six categories: individual 

tax cuts and similar payments; the tax cut associated with the adjustment of the Alternative 

Minimum Tax (AMT); business tax incentives; state fiscal relief; aid to those most directly hurt 

by the recession; and direct government investment spending. The first three are tax changes of 

some kind and were established at passage to be roughly one-third of the total package; the 

second two represent emergency measures and were again estimated to be roughly one-third of 

the total; the last encompasses a range of direct spending and covers the remaining one-third of 

the total. At passage, it was anticipated that the tax changes and emergency measures would 

occur more quickly and direct government spending would be a larger fraction of later 

expenditures. 

We divide the outlays and tax reduction data into these functional categories as follows. 

Individual tax cuts include the Making Work Pay tax credit, the child tax credit, and a number of 

                                                           

5

 Congressional Budget Office (2009a). 
6 

smaller individual tax reductions. We also include direct payments (from Recovery.gov) that 

were made in lieu of a tax cut to certain groups. These include payments of $250 distributed to 

individuals who receive Social Security and Supplemental Security Income, Railroad Retirement 

benefits, or veterans’ benefits. The business tax incentives and AMT relief are calculated 

directly by the IRS as part of their simulation process.6

We define state fiscal relief to include just the two main programs in this category: a 

substantial increase in the Federal government’s matching percentage for Medicaid spending 

(FMAP), and formula grants to state governments for education through the State Fiscal 

Stabilization Fund. Aid to those directly impacted by the recession includes the increase and 

extension of unemployment benefits, increased funds for nutritional assistance, and increases in 

the Temporary Aid to Needy Families (TANF) program. It also includes the government’s 

substantial subsidy of continuing health insurance benefits (COBRA), which is technically 

treated as a tax cut. 

Government investment outlays include everything else. The obvious components are 

spending on infrastructure, health information technology, research on renewable energy, and 

other forms of direct spending excluding transfers. Also included here are tax credits for 

particular types of private spending, such as weatherization or research and experimentation, 

since these credits are functionally similar to the direct government spending. 

Table 2 shows our breakdown of aggregate outlays and tax relief into these functional 

categories. The table shows that the bulk of the stimulus so far has been concentrated in three 

areas: individual tax cuts and similar payments, state fiscal relief, and aid to those directly hurt 

by the recession. This concentration is exactly what was intended and expected when the Act 

was passed. One key purpose of these types of stimulus was to provide immediate help to an 

economy in freefall. AMT relief and business tax incentives were always expected to be smaller 

components of the Act. And, it was anticipated that direct government investment spending 

would mainly provide support over what was expected to be an extended period of economic 

weakness. Consistent with this, obligations in the area of infrastructure and other investments, 

indicating future outlays, are substantial. 

                                                           

6

 The monthly estimates of AMT relief are from unpublished analysis by the Office of Tax Analysis of the 

Department of Treasury. 
7

Table 2. Fiscal Stimulus by Functional Category

Through the end of 

Marcha Juneb Augustc

Billions of Dollars

Individual Tax Cuts 2.3 29.3 40.0

AMT Relief 0.0 7.6 8.8

Business Tax Incentives 0.1 14.4 17.2

State Fiscal Relief 8.5 28.2 38.4

Aid to Directly Impacted Individuals 0.8 14.4 30.6

Government Investment Outlays 0.0 5.9 16.5

Totald 11.8 99.8 151.4

Sources: Recovery.gov; CEA calculations; Updated simulations from the Department of the 

Treasury (Office of Tax Analysis) based on the Mid-Session Review.

Notes: a. Data on outlays and obligations are for March 27.

b. Data on outlays and obligations are for June 26.

c. Data on outlays and obligations are for August 28.

d. Items may not add to total due to rounding.

III. EVIDENCE OF EFFECTS FROM THE BEHAVIOR OF GDP AND EMPLOYMENT

The first way that we investigate the impact of the ARRA is to consider the behavior of 

real GDP and employment. Are the changes that we have observed in these two key indicators 

over the past six months consistent with the Recovery Act having a substantial effect? 

Before looking at the data, it is important to acknowledge once again that six months is a 

short period of time for macroeconomic analysis. The only official GDP data that we have under 

the program is for the second quarter of 2009. While we now have the second estimate of this 

series, all data are subject to further revision and one observation obviously does not constitute a 

trend. For employment, we have monthly data through August 2009. These data are again 

subject to revision, and analysts are well aware that the monthly employment series has a 

substantial margin of error simply due to inherent sampling difficulties. 

A. Real GDP Growth 

Figure 1 shows the growth rate of real GDP. After falling considerably and, indeed, 

progressively more deeply in each of the three quarters before the most recent one, the fall in 

GDP moderated substantially. After declining at an annual rate of 6.4 percent in the first quarter 

of 2009, it fell at a rate of 1.0 percent in the second quarter. Figure 1 also shows the consensus 

forecast for real GDP growth in the third quarter. The August 10th Blue Chip forecast of 2.2 

percent is, if anything, on the low end of current forecasts. Macroeconomic Advisers, GoldmanSachs, and Moody’s Economy.com, three prominent members of the Blue Chip panel, are 

currently forecasting third quarter growth of more than 3 percent at an annual rate. 
8 

1.2

3.2 3.6

2.1

-0.7

1.5

-2.7

-5.4

-6.4

-1.0

2.2

-8

-6

-4

-2

0

2

4

6

07:Q1 07:Q2 07:Q3 07:Q4 08:Q1 08:Q2 08:Q3 08:Q4 09:Q1 09:Q2 09:Q3

Figure 1. Real GDP Growth

Quarterly percent change, seasonally adjusted annual rate

Blue Chip

Sources: Department of Commerce (Bureau of Economic Analysis); Blue Chip consensus forecast.

Note: 2009:Q3 datapoint reflects Blue Chip consensus forecast from August 10.

The economy is obviously still far from healthy. Real GDP is far below its previous peak 

level and millions of Americans are out of work. But economies do not switch from rapid 

decline to robust growth all at once. Given what we now know about the frightening momentum 

of economic decline in the first quarter, it would have been hard for the economy to stabilize 

much faster than it has. 

Figure 2 shows the change in the growth rate of real GDP over the last 25 years. The rise 

in GDP growth from the first quarter to the second was the largest in almost a decade, and the 

second largest in the past quarter century. And, if growth in the third quarter matches the 

consensus forecast, the turnaround in real GDP growth from the first to the third quarter of 2009 

would be the largest in the past 25 years. 
9

-12

-8

-4

0

4

8

84:Q1 86:Q1 88:Q1 90:Q1 92:Q1 94:Q1 96:Q1 98:Q1 00:Q1 02:Q1 04:Q1 06:Q1 08:Q1

Figure 2. Changes in Quarterly Real GDP Growth

Percentage points

Sources: Department of Commerce (Bureau of Economic Analysis); Blue Chip consensus forecast.

Note: 2009:Q3 datapoint reflects Blue Chip consensus forecast from August 10. NBER recessions are shown in grey.

The timing of the change in trajectory in real GDP growth is certainly suggestive of an 

important role for the ARRA. An economy in freefall in the months before the ARRA stabilized 

dramatically in the quarter after, and according to most forecasts will begin growing again two 

quarters after the stimulus began. 

The behavior of key components of GDP is consistent with the ARRA playing a causal 

role. Figure 3 shows the contributions of each of the main components of GDP to overall growth 

in the first and second quarters of this year. 

0.44

-5.29

-1.33

-2.36

-0.19 -0.33

2.64

-0.69

-1.15

-0.66

-1.39

0.44

0.82

1.60

-6

-4

-2

0

2

4

6

2009:Q1

2009:Q2

Figure 3. Contributions to Real GDP Growth

Personal

Consumption 

Expenditures

Nonresidential 

Fixed 

Investment

Other 

Fixed 

Investment

Inventory 

Investment

State and 

Local Gov't 

Spending

Federal 

Gov't 

Spending

Net 

Exports

Percentage points

Source: Department of Commerce (Bureau of Economic Analysis).

Note: Bars sum to quarterly change in GDP growth (-6.4% in Q1; -1.0% in Q2).
10 

The role of the Recovery Act is clearest in state and local spending. Sharp falls in 

revenues and balanced budget requirements have been forcing state and local governments to 

reduce spending and raise taxes. But, state and local government spending actually rose at a 

robust 3.6 percent annual rate in the second quarter of 2009, which helped keep the economy 

from sinking deeper. This followed two consecutive quarters of decline, and was the highest 

growth rate in more than five years. The $28 billion of state fiscal relief that had been 

distributed by the end of the second quarter was almost certainly a key source of this increase. 

 Another area where the role of the ARRA seems clear is in nonresidential fixed 

investment – firms’ purchases of everything from machines to software to structures. A key 

source of the more modest decline in GDP is that this type of investment, which fell at a 

devastating 39 percent annual rate in the first quarter, fell at a much more moderate 11 percent 

rate in the second quarter. One important component of the Recovery Act was investment 

incentives, such as bonus depreciation. Businesses received about $14 billion of this type of tax 

relief in the second quarter, and this may have contributed to slower investment decline. 

The behavior of durable goods orders and shipments in July suggest that the stabilization 

in the second quarter is likely to turn into genuine expansion in this key sector in the third 

quarter. Core capital goods shipments rose 0.8 percent in July.7

 This component is a direct 

input to the estimate of equipment and software investment. That orders for durable goods in 

July were roughly equal to shipments is an indicator that investment is likely to continue at a 

similar pace later in the quarter. 

                                                           

For the personal consumption component of GDP, the picture is more nuanced. 

Consumption fell sharply in the second half of last year, but has largely stabilized despite rising 

unemployment and falling GDP. The Making Work Pay tax credit and the improvements in 

confidence as a result of the Recovery Act and the Administration’s other recovery actions surely 

contributed to that stabilization.8

 At the same time, the fact that consumption fell slightly in the 

second quarter after rising slightly in the first quarter could be a sign that households are initially 

using the tax cut mainly to increase their saving and pay off debt. 

Data on real personal consumption expenditures (PCE) for June and July suggest that 

consumer spending could rise going forward.9

 Real PCE rose 0.1 percent in June and 0.2 

percent in July. The Conference Board index of consumer confidence turned sharply upward in 

August, suggesting that this pattern could continue through the rest of the third quarter.10 While 

most analysts expect consumers to remain somewhat cautious going forward and for saving rates 

to remain elevated, even a modest recovery in consumer spending would be helpful to continued 

7

 The data are from the U.S. Census Bureau of the Department of Commerce. 

8

 The University of Michigan consumer survey showed a sharp increase in approval of government economic policy 

in April. See Reuters/University of Michigan Surveys of Consumers (2009). 9

 The data are from the Bureau of Economic Analysis of the Department of Commerce. 

10 The University of Michigan index, in contrast, was essentially unchanged in August. 
11

recovery. 

B. Change in Payroll Employment 

Figure 4 shows the change in payroll employment over the recession. A key indicator of 

the severity of this recession is the fact that in the first quarter of this year, we lost nearly 

700,000 jobs per month. In the second quarter, we lost an average of 428,000 jobs per month. 

Statistics released on September 4 show that job loss was 276,000 in July and 216,000 in August, 

for a two-month average loss so far this quarter of 246,000. These job losses are obviously 

unacceptable. But the change does suggest that we are on the right trajectory. 

133

82

2

167

-113 -153

-208

-553

-691

-428

-246

-800

-400

0

400

07:Q1 07:Q2 07:Q3 07:Q4 08:Q1 08:Q2 08:Q3 08:Q4 09:Q1 09:Q2 09:Q3

Figure 4. Payroll Employment Growth

Average monthly change from end of quarter to end of quarter, thousands

Source: Department of Labor (Bureau of Labor Statistics).

Note: 2009:Q3 datapoint reflects the average change in employment in July and August.

Figure 5 shows the change in the change in employment. The movement in job loss from 

the first quarter to the second was the largest in almost 30 years. If the observation for 

September is equal to the average for July and August, which is a relatively pessimistic 

assumption, the average monthly job loss for the third quarter would be almost 200,000 less than 

in the second quarter and 450,000 less than in the first quarter. 
12 

-400

-200

0

200

400

84:Q1 86:Q1 88:Q1 90:Q1 92:Q1 94:Q1 96:Q1 98:Q1 00:Q1 02:Q1 04:Q1 06:Q1 08:Q1

Figure 5. Changes in Payroll Employment Growth

Thousands

Source: Department of Labor (Bureau of Labor Statistics).

Note: The figure shoes the change from the previous quarter in the average monthly change in employment. 2009:Q3 

datapoint reflects the change in average monthly growth in July and August from the average monthly growth in 2009:Q2. 

NBER recessions are shown in grey.

As with real GDP, the timing of the change in employment behavior is suggestive of a 

key role for the ARRA and other stabilizing measures taken in February and March. Job losses 

moderated in the quarter after Recovery Act spending and tax cuts began. They then continued 

to slow in the subsequent quarter. 

Further suggestive evidence is provided by considering the changes in the sectoral 

composition of job loss between the first, second, and third quarters of 2009. Figure 6 shows the 

contribution of the change in employment for each quarter in ten key sectors of the economy. 

-250

-200

-150

-100

-50

0

50

100

150

2009:Q1

2009:Q2

2009:Q3 (est.)

Figure 6. Contributions to Changes in Employment

Average monthly change from end of quarter to end of quarter, thousands 

Sources: Department of Labor (Bureau of Labor Statistics); CEA calculations.

Note: Observations for 2009:Q3 are based on average change in July and August. Bars sum to average monthly change in 

quarter (-691,000 in Q1; -428,000 in Q2; -246,000 in Q3).

Mining 

and 

Logging

ConstructionManufacturingWhlsl. 

Trade, 

Trans.,

& Util

Retail 

Trade

Prof. 

and 

Business 

Services

Education 

and 

Health 

Services

Federal 

Gov't

State and 

Local 

Gov't

Other 

Services
13

The largest swings in job loss from the first to the third quarters have been in 

manufacturing and in professional and business services (which includes temporary employment 

agencies). Since these are both highly cyclical industries, this is the pattern one would expect if 

the ARRA and other policy actions were moderating the cyclical decline. The pronounced 

decline in manufacturing job loss could also reflect the effect of business tax incentives on 

investment. 

Another place where there is evidence of the Act’s role is in the absence of any 

acceleration of job losses in state and local government. As described in Section VI, the 

conjunction of sharp revenue declines and balanced budget requirements created enormous 

pressures on state and local governments to cut spending and lay off workers. But, as Figure 6 

shows, overall state and local government employment has declined relatively little. The 

obvious candidate explanation is the $38 billion of state fiscal relief provided by the ARRA 

through August. Similarly, the construction industry, where job losses have moderated 

substantially despite the fact that the recession has in many ways been centered in residential real 

estate, could suggest a role for the Recovery Act spending in infrastructure and the First-Time 

Homebuyer Tax Credit. Some of the moderation of job losses in this sector presumably also 

reflects other policy actions, such as the Administration’s programs to help distressed 

homeowners and the Federal Reserve’s efforts to support the mortgage market. 

C. Estimates of Effects of Policy from a Comparison to Baseline Forecasts 

The previous analysis has used the timing and sectoral composition of changes in GDP 

and employment to suggest an important role for the ARRA. One limitation of this analysis is 

that it does not attempt to specify what would have happened in the absence of the fiscal 

stimulus and other recovery actions. It implicitly assumes that in the absence of stimulus, no 

change would have occurred. To address this issue, in this section we present a sensible 

statistical forecast of the likely path of GDP and employment in the absence of stimulus. We can 

then interpret the discrepancy between this forecast and actual developments as a measure of the 

impact of policy. 

There are many ways to construct a statistical baseline forecast. The particular method 

that we use is to estimate a vector autoregression (or VAR) using the logarithms of real GDP (in 

billions of chained 2005 dollars) and employment (in thousands, in the final month of the 

quarter) estimated over the period 1990:Q1-2007:Q4. We include four lags of each variable. 

Because the estimation ends in 2007:Q4, the coefficient estimates used in the prediction are not 

influenced by developments in the current recession. Rather, they show the usual joint short-run 

dynamics of the two series over an extended sample. We then forecast GDP and employment in 

the second and third quarters of 2009 using actual data through the first quarter of the year. Data 

through the first quarter include the monetary response to the current crisis, but not the fiscal 
14 

stimulus or other actions that took effect after the first quarter. We have experimented with a 

variety of other ways of projecting the no-stimulus path of GDP. The results of those exercises 

are generally similar to those we report below. 

Figure 7 shows the results of this forecasting exercise for real GDP. Past history predicts 

that real GDP would continue to decline at a substantial rate in the second quarter. The projected 

decline (at an annual rate) is 3.3 percent. In the third quarter, real GDP would also be projected 

to decline, but at the more modest rate of 0.5 percent. 

13,367

13,415

13,325

13,142

12,925

12,816 12,798

12,500

12,750

13,000

13,250

13,500

2008:Q1 2008:Q2 2008:Q3 2008:Q4 2009:Q1 2009:Q2 2009:Q3

Figure 7. Real GDP: Recent and Projected Levels

Billions of 2005 dollars, seasonally adjusted annual rate

Actual Projection

Sources: Department of Commerce (Bureau of Economic Analysis); CEA calculations.

Figure 8 superimposes the actual GDP outcome in 2009:Q2 and the consensus forecast 

outcome in 2009:Q3 on the projections based on past history. The figure shows that real GDP 

growth in the second quarter, which was -1.0 percent, was 2.3 percentage points higher than the 

usual time-series behavior would have led one to expect. Assuming that GDP in the third quarter 

matches the Blue Chip consensus estimate of 2.2 percent, GDP growth in 2009:Q3 will be 2.7 

percentage points higher than the statistical baseline prediction. These estimates again suggest 

that policy actions taken in the winter resulted in large positive innovations to GDP growth. 
15

12,500

12,750

13,000

13,250

13,500

2008:Q1 2008:Q2 2008:Q3 2008:Q4 2009:Q1 2009:Q2 2009:Q3

Actual

Projection

Figure 8. Real GDP: Recent and Projected Levels

Billions of 2005 dollars, seasonally adjusted annual rate

Sources: Department of Commerce (Bureau of Economic Analysis); CEA calculations; Blue Chip consensus forecast.

Note: The 2009:Q3 figure for "actual" is the Blue Chip consensus forecast from August 10.

Figure 9 shows the forecast of employment changes using this procedure. The baseline 

forecast implies further substantial job loss in the second and third quarters. Indeed, the 

projected average monthly decline in the absence of the Recovery Act is nearly 600,000 jobs in 

2009:Q2 and just over 500,000 jobs in 2009:Q3. 

-113

-153

-208

-553

-691

-597

-513

-800

-600

-400

-200

0

2008:Q1 2008:Q2 2008:Q3 2008:Q4 2009:Q1 2009:Q2 2009:Q3

Figure 9. Payroll Employment: Recent and Projected Changes

Average monthly change from end of quarter to end of quarter, thousands

Actual Projection

Sources: Department of Labor (Bureau of Labor Statistics); CEA calculations.

Figure 10 shows that the actual job loss in the second quarter came in substantially lower 

than the projection. Based on the data to date on employment in 2009:Q3, it appears that job loss 

will also be substantially smaller in the third quarter than the forecasting model predicts. 
16 

-800

-600

-400

-200

0

2008:Q1 2008:Q2 2008:Q3 2008:Q4 2009:Q1 2009:Q2 2009:Q3

Projection

Actual

Figure 10. Payroll Employment: Recent and Projected Changes

Average monthly change from end of quarter to end of quarter, thousands 

Sources: Department of Labor (Bureau of Labor Statistics); CEA calculations.

Note: 2009:Q3 datapoint for "actual" series reflects the average change in employment in July and August.

The difference between the predicted and actual changes in GDP and employment over 

the middle two quarters of 2009 can be cumulated to show the difference in the level of the two 

series as of the third quarter. Table 3 shows this calculation. For real GDP, the finding that 

growth has been 2.3 percentage points higher than predicted in 2009:Q2 and is likely to be about 

2.7 percentage points higher in 2009:Q3 implies that the level of GDP in 2009:Q3 is 

approximately 11⁄4 percent higher than a sensible statistical baseline forecast.11 

2009:Q2 2009:Q3

Actual GDP Growth -1.0% 2.2%a

Baseline Projection -3.3% -0.5%

Difference +2.3 p.p. +2.7 p.p.

Estimated Cumulative Impact of Policy on Level +1.25%

Actual Employment Change -428,000 -246,000b

Baseline Projection -597,000 -513,000

Difference +169,000 +267,000

Estimated Cumulative Impact of Policy on Level (August)c +1,040,000

Notes: a. Blue Chip, August 2009.

b. Average of July and August only.

c. Items may not add to total due to rounding.

Table 3. Estimates of the Effect of the ARRA Using CEA Statistical Projection

GDP Growth

Employment Change

Sources: Department of Commerce (Bureau of Economic Analysis); Department of Labor (Bureau of Labor Statistics); CEA 

calculations.

                                                           

11 The reason the figure is about 11⁄4 percent rather than 5 percent is that the figures for quarterly GDP growth are 

expressed at an annual rate. 
17

For employment, the average change in each of the three months of the second quarter 

was 169,000 less than the baseline forecast. This implies that the level of employment at the end 

of the quarter was 507,000 higher than the baseline forecast predicted. For each month of the 

third quarter, actual employment loss is estimated to be an average of 267,000 less than 

projected. This implies that as of August, employment relative to the projection is another 

534,000 higher than at the end of June. Therefore, the level of employment as of August is 

1,040,000 higher than the statistical baseline forecast.12

This projection methodology provides one way of estimating the impact of the ARRA on 

employment and the economy. It shows that using the past history of GDP and employment and 

actual data through the first quarter of 2009, one would have predicted that employment as of 

August would be about 1 million lower than it actually was. To ascribe much of this difference 

to the ARRA, the key policy action taken in the first quarter, is certainly plausible. However, 

other policy actions, such as the Financial Stabilization Plan, monetary policy, and the Federal 

Reserve’s program of buying agency debt and long-term U.S. government bonds, surely 

contributed to the difference. Also, any other factors not captured by the past history of GDP 

and employment, such as unusual moves in foreign demand or asset prices, would also be 

captured in the difference. 

Importantly, there is no reason to assume that the overall effect of these omitted policies 

and other factors was to contribute positively to actual GDP and employment growth. For 

example, while the various actions to improve financial conditions have surely had a positive 

impact, the continuing stringency in credit conditions is a development likely to be holding down 

actual outcomes relative to usual cyclical patterns. Thus, the forecast residuals could either 

overestimate or underestimate the impact of the ARRA. 

D. Sectoral Decomposition of the Estimated Impact on Employment 

The previous analysis provides an estimate of the impact of the ARRA on employment 

relative to the baseline. An obvious question is how those impacts are likely to have been 

distributed across industrial sectors. 

The most important effects of the Recovery Act on the economy to date have been 

through the general stimulus it has provided. For example, thus far tax cuts and support for those 

most directly hurt by the recession have been substantial, while direct government spending on 

specific projects has been relatively small. Thus, the main reason the employment effects of the 

Act so far have not been evenly distributed across sectors is that some sectors are more sensitive 

to changes in overall employment than others. 

                                                           

12 The number is the sum of 507,000 and 534,000. The numbers do not add exactly because of rounding. 
18 

The response of employment in individual sectors to changes in overall employment can 

be decomposed into two components. First, a rising overall level of employment tends to 

increase employment in each industry in proportion to its share of the overall economy. We 

refer to this as the “rising tide” effect. Second, some sectors are more sensitive to the state of the 

business cycle than are others. An example is the employment services industry, most of which 

is comprised of temporary help services: temporary employment tends to rise much faster than 

overall employment in business cycle expansions and to decline much faster in recessions. The 

additional employment due to the Recovery Act has therefore almost certainly produced relative 

expansion of such procyclical sectors, while countercyclical sectors, such as utilities, health care, 

and government, have seen their shares of total employment shrink relative to what would have 

been seen in the absence of stimulus. We refer to the resulting changes in sectoral employment 

as the “cyclicality effect.”13 

The net effect of the Recovery Act on employment in each sector through its 

expansionary effects is simply the sum of the rising tide and the cyclicality effects. The rising 

tide effect is straightforward to measure, as each sector receives a share of the estimated 1.04 

million jobs created proportional to the sector’s share of overall employment. The first column 

of Table 4 shows the employment share of each major industrial sector and of selected subsectors in August 2009.14

Estimation of the cyclicality effect is the more complex part of the decomposition. First, 

the cyclicality of each sector’s employment share must be estimated. Using quarterly data on 

employment by sector from 1990 through 2007,15 we estimate the relationship between changes 

in overall employment and changes in the sectoral employment share. The second column of 

Table 4 shows the cyclical sensitivity of each sector’s employment share. The first few entries 

indicate that a 1 percent increase in total employment tends to correspond to a 0.29 percent 

reduction in the share of employment in the mining and logging sector and 1.76 and 0.92 percent 

increases in the employment shares of the construction and manufacturing sectors, 

respectively.16 The cyclicality factors indicate that construction and information are the most 

procyclical major sectors. The professional and business services and manufacturing sectors are 

both highly cyclical as well, driven, respectively, by the employment services and durable goods 

sub-sectors. The most countercyclical sectors are education and health services, government, 

                                                           

13 Formally, let sˆ and Eˆ be the sectoral employment share and total non-farm employment, respectively, that 

would have obtained without the Recovery Act, and let s and E be the values that were actually observed in 

August 2009. Then the total impact on employment in the sector is sE  sˆEˆ  s(E  Eˆ)  (s  sˆ)Eˆ . The first 

term here is the rising tide effect and the second term is the cyclicality effect. 14 Data are from U.S. Department of Labor (2009). 

15 Data are from U.S. Department of Labor (2009). 

16 These cyclicality factors are the coefficients from regressions of the quarterly change in each sector’s share of 

total non-farm employment on a constant and the quarterly change in log employment, using data from 1990:Q1 

through 2007:Q4, divided by the sector’s employment share in August 2009. 
19

financial activities, and other services; all of these tend to see rising employment shares when the 

economy contracts and falling shares when the economy expands. 

Employment 

Share

Sector

Cyclicality

Factor Total

Share of

Total

Mining and Logging 1% -0.29 -2 6 4 0%

Construction 5% 1.76 85 48 133 13%

Manufacturing 9% 0.92 86 93 179 17%

Durable Goods 5% 1.78 101 57 158 15%

Trade, Transportation, and Utilities 19% 0.16 33 199 232 22%

Retail Trade 11% 0.16 18 117 135 13%

Information 2% 1.27 28 22 51 5%

Financial Activities (FIRE) 6% -0.51 -31 61 30 3%

Professional and Business Services 13% 0.95 124 132 256 25%

Employment Services 2% 4.55 88 19 107 10%

Education and Health Services 15% -0.86 -132 153 22 2%

Leisure and Hospitality 10% -0.21 -21 104 83 8%

Other Services 4% -0.50 -21 43 22 2%

Government 17% -0.84 -149 178 29 3%

Total Nonfarm Employment 100% ------ ------ 1,040 1,040 100%

Sources: Department of Labor (Bureau of Labor Statistics); CEA calculations.

Note: Data are from August 2009.

Table 4. Employment Effects of the Recovery Act by Sector

Effect

(Thousands of Jobs)

Cyclicality Rising Tide

The Recovery Act, by stimulating total employment, has led to increases in the 

employment shares of procyclical industries and reductions in the shares of countercyclical 

industries relative to what would have happened otherwise. The resulting cyclicality effects on 

sectoral employment are shown in the third column of Table 4.17 Construction and 

manufacturing have each gained about 85,000 jobs relative to the baseline due to cyclicality 

factors, while professional and business services has gained nearly 125,000 jobs. More than all 

of the cyclical manufacturing growth is in the durable goods sector (which gained 101,000 jobs 

through this channel)18 while the professional services growth is largely due to the employment 

services industry (88,000 jobs gained relative to the baseline). By contrast, education and health 

services and government each saw their job creation reduced by over 130,000 jobs relative to the 

baseline due to the cyclicality effect, and financial activities by 31,000 jobs. 

                                                            

17 These are calculated by multiplying the regression coefficients from the previous footnote by the change in log 

employment attributable to the Recovery Act (from the analysis in the previous section) to obtain the change in the 

sectoral employment share attributable to the cyclicality effect of the Act. That is, we estimate (s  sˆ) as 

 (ln E  ln Eˆ) , where  is the regression coefficient. The resulting change in the sectoral employment share is 

then multiplied by our estimate of the employment level that would have obtained without the act, Eˆ = 130.2 

million, to obtain the cyclicality effect on sectoral employment levels. 

18 The cyclicality effect on durable goods can be larger than that on all manufacturing because non-durable goods 

employment is (relatively) countercyclical, with declining employment shares in expansions. 
20 

The fourth column shows the rising tide effects. These are all necessarily positive, as no 

industry has a negative share of total employment. In each case, industries with negative 

cyclicality effects saw those more than offset by positive rising tide effects, leading to a net 

positive effect on total employment relative to the no-stimulus baseline. These net effects are 

shown in the fifth column, while the last column shows the distribution across sectors. All major 

industries were assisted, with the largest shares of jobs created by the Recovery Act in 

professional and business services; trade, transportation, and utilities; manufacturing; and 

construction. 

Of course, these figures are only estimates. One factor that could cause the distribution 

of job creation to differ from its normal cyclical pattern is the unusual nature of the recession. 

For example, the fact that the recession has been unusually concentrated in construction may 

mean that the fraction of jobs saved or created by fiscal stimulus in this recession that are in 

construction is different than it usually would be. 

Another factor that could cause the actual distribution to differ from our estimates is the 

specifics of the Recovery Act. Most obviously, the fact that a substantial portion of spending 

under the Act thus far has consisted of aid to the states suggests that estimates based on normal 

cyclical behavior are likely to underestimate the effects of the Act on state and local government 

employment. 

E. State Decomposition of the Estimated Impact on Employment 

Our comparison to baseline projections suggests that the ARRA and other recovery 

programs have resulted in employment as of August that is just over 1 million higher than it 

otherwise would have been. There is obviously much interest in how these employment effects 

have been distributed across states. In this section, we make an initial attempt to provide such a 

state-by-state breakdown. However, it is important to emphasize that these disaggregate 

estimates are inherently more speculative and uncertain. 

Because there is no perfect way to measure state-level effects, we pursue three 

approaches to decomposing employment impacts across states. Our first method allocates jobs 

according to states’ shares of national non-farm employment as of March 2009.19 Georgia, for 

example, had 3.0 percent of all employment in the country in March, so is allocated 3.0 percent 

of total job creation. This is akin to the “rising tide” component of job creation discussed above. 

Our second method allocates jobs according to the distribution of Recovery Act outlays, 

as reported by Recovery.gov on August 28, 2009. Georgia has received 2.8 percent of total 

outlays, so is estimated to receive 2.8 percent of total job creation. This method provides a more 

                                                           

19 U.S. Department of Labor (2009). We use seasonally adjusted estimates of total nonfarm employment. 
21

direct measure of where ARRA impacts are likely to be felt than does the “rising tide” method, 

but it has an important drawback. Only a portion of the overall Recovery Act stimulus is 

included in the Recovery.gov state-level figures. The most important stimulus not included in 

this approach are the various types of tax relief, which, as discussed earlier, comprise almost half 

of total spending plus tax cuts to date. Tax cuts are likely more evenly distributed across states 

than are outlays, so our use of outlays likely overstates the unevenness of employment effects. 

Similarly, this method assumes that all of the employment effects of spending in a state are felt 

within the state. In fact, however, there are important spillovers across states. Thus again, this 

approach is likely to exaggerate the differences among states. 

Our third method relies on the sectoral decomposition of employment effects from the 

previous subsection. We assume that any jobs saved or created in a particular industrial sector 

(for example, mining and logging) are distributed across states in the same way as are existing 

jobs in that sector.20 Georgia has only 1.4 percent of national employment in mining and 

logging, so is assumed to receive only 1.4 percent of employment effects in that industry. By 

contrast, Georgia has nearly one-quarter of national textile product mill employment, so any 

employment impacts in that industry are assigned disproportionately to Georgia. Summing 

across 42 industries, we obtain the total impact on Georgia employment.21 The procedure is 

repeated for each state to obtain the distribution across states. 

None of these three approaches does a perfect job of measuring the geographic 

distribution of employment effects, and each has advantages and disadvantages relative to the 

others. Thus, to obtain a reasonable estimate of state-level job impacts, we use a simple average 

of the three approaches. This average indicates that the ARRA has saved or created nearly 

31,000 jobs in Georgia, 3.0 percent of the national total. Estimates for all fifty states, plus the 

District of Columbia, are reported in Table 5. 

                                                           

20 Employment by state and industry is drawn from data published by the U.S. Department of Labor (2009). We use 

data from the March 2009 Current Employment Statistics to determine state employment shares and data from the 

2008 Quarterly Census of Employment and Wages to determine state-by-industry employment. Because of 

limitations in the available data, the analysis here (unlike that used for the sectoral analysis above) uses data 

beginning in 1990:Q2. 

21 For this analysis, we use a finer disaggregation of industries than was reported in Table 4. Manufacturing is 

divided into 21 sectors (for example, fabricated metal products). Trade, transportation, and utilities are divided into 

four sectors (wholesale trade, retail trade, utilities, and transportation/warehousing); financial activities into two 

(finance/insurance, and real estate/rental/leasing); professional and business services into five (professional/technical 

services, management of companies, employment services, other administrative/support services, and waste 

management/remediation); education and health into two (educational services and health care/social assistance); 

leisure and hospitality into two (arts/entertainment/recreation and accommodation/food services). For data sources 

and methods used in the sectoral decomposition, see the previous subsection. 
22 

Table 5. Estimated Impact of the ARRA on Employment by State

State Jobs Impact State Jobs Impact

Alabama

Alaska

Arizona

Arkansas

California

Colorado

Connecticut

Delaware

District of Columbia 

Florida

Georgia

Hawaii

Idaho

Illinois

Indiana

Iowa

Kansas

Kentucky

Louisiana

Maine

Maryland

Massachusetts

Michigan

Minnesota

Mississippi

Missouri

Thousands

13.5

2.2

21.4

8.6

139.7

16.1

12.9

3.0

4.9

55.4

30.8

4.2

4.6

50.4

24.4

10.9

9.1

13.1

12.7

4.8

17.4

27.4

36.0

20.1

8.3

19.2

Montana

Nebraska

Nevada

New Hampshire

New Jersey

New Mexico

New York

North Carolina

North Dakota

Ohio

Oklahoma

Oregon

Pennsylvania

Rhode Island

South Carolina

South Dakota

Tennessee

Texas

Utah

Vermont

Virginia

Washington

West Virginia

Wisconsin

Wyoming

Thousands

2.9

5.6

9.1

4.0

31.2

5.3

72.5

31.5

2.2

38.9

11.8

13.6

40.9

4.1

13.7

2.8

20.0

71.9

9.5

2.3

24.0

22.6

5.1

22.1

1.8

Source: CEA estimates based on data from the Current Employment Statistics and the Quarterly Census of 

Employment and Wages. 

Notes: Entries sum to the estimated cumulative impact of policy on level in Table 3 (1,040,000 jobs impacted). 

may not add to total due to rounding.

 Items 

Of course, simply because their populations are larger, we estimate that larger states have 

seen larger jobs impacts. Similarly, because their employment is more cyclically sensitive, 

industrial states are estimated to have had larger employment effects relative to their populations. 

Finally, both because of their industrial composition and because state fiscal relief and aid to 

those directly impacted have been larger in states hit harder by the recession, we estimate that 

states with higher unemployment rates at the time of passage have seen larger employment 

effects of the ARRA relative to their populations. 
23

IV. ESTIMATES OF EFFECTS FROM ECONOMIC MODELS

This section examines estimates of the output and employment effects of the ARRA from 

macroeconomic models of the effects of various types of fiscal stimulus. The first part of the 

section describes the Council of Economic Advisers’ estimates derived from those models. We 

then consider the estimates from a wide range of public and private forecasts and analysts. 

A. CEA Model-Based Estimates of the Effect of the ARRA 

A natural way to estimate the effects of the ARRA on employment and GDP is to use 

existing estimates of the macroeconomic effects of fiscal policy. This was one approach used by 

the CEA to estimate the likely effects of the Act based on the information available soon after 

the Act was passed.22 This methodology uses mainstream estimates of economic multipliers for 

the effects of fiscal stimulus. 

The main difference from our earlier analysis is that we can now use figures on actual 

outlays and tax relief under the Act through August, rather than prospective estimates of what the 

likely spendout would be. To use the actual spendout figures, we need to address the fact that 

our approach is designed to work with quarterly data, while at the moment there are data on 

spendout only through the end of August. We therefore assume that spendout in July and August 

represents two-thirds of spendout in 2009:Q3. The multipliers are applied to the resulting 

quarterly figures. This yields estimates of the effects on employment and GDP as of the third 

quarter of 2009. Because August is the middle month of the quarter, the quarterly employment 

effect can reasonably be interpreted as an estimate of the employment effect in August.23

This exercise, like the one based on statistical projections, will obviously not yield exact 

figures for the effects of the ARRA. To begin with, there is uncertainty about the size of the 

economic effects of a “typical” increase in government purchases or a “typical” tax cut. There is 

                                                           

22 Council of Economic Advisers (2009). 

23 We also make several smaller adjustments to the earlier analysis to reflect the fact that our goal here is largely to 

estimate the effects at a particular point, rather than to estimate the broad contours of the effects. First, an important 

component of spending under the Act to date (though not over its entire life) consists of one-time payments to 

seniors, veterans, and the disabled. These constituted $13 billion of the $29 billion of individual tax cuts and similar 

payments through the end of June shown in Table 2. In terms of short-run macroeconomic effects, such one-time 

payments are similar to one-time tax rebates, whose effects are smaller than those of tax cuts that are perceived as 

permanent. The analysis therefore uses multipliers for the one-time payments equal to one-half the multipliers for 

conventional tax cuts. Second, we assume that recipients of the various types of aid to those directly impacted by 

the recession (such as extended unemployment insurance) spend two-thirds of the funds in the quarter they receive 

them and one-third in the following quarter (rather than spending all of the funds within the quarter). Third, we 

assume that the impact of state fiscal relief on state budget decisions is spread over the quarter that funds are 

transferred to the states and the subsequent three quarters (rather than assuming the effects all occur with a onequarter lag). Finally, we adjust the multipliers for investment incentives to account for the fact that while the size of 

those incentives is similar to what was assumed in the earlier analysis, the timing of the revenue changes associated 

with them involves larger reductions in 2009 and 2010 and larger increases in 2011 and beyond. 
24 

even more uncertainty about the precise timing of those effects, and modest changes in timing 

have noticeable effects on the impact at a specific point in time. In addition, the current 

exceptional economic environment could make the effects of stimulus somewhat larger or 

smaller than normal, or could cause them to occur somewhat more or less quickly. Finally, the 

ARRA – appropriately – was not just typical stimulus. For types of stimulus that are used less 

frequently, there is even greater uncertainty about the size and timing of the macroeconomic 

effects. 

The results of this analysis are shown in Table 6. They imply that the ARRA is having a 

substantial beneficial effect on production and employment. Specifically, they suggest that the 

ARRA added roughly 3.1 percentage points to GDP growth in the second quarter and is likely to 

add roughly 3.6 percentage points to GDP growth in the third quarter. The approach also 

suggests that the Act increased employment relative to what it otherwise would have been in the 

second quarter (or May) by about 434,000 jobs, and that it is likely increasing employment in the 

third quarter (or August) by about 1.159 million jobs. These estimates are broadly similar to the 

estimates described in Section III obtained by comparing employment and output with 

projections of how those variables would have behaved in the absence of stimulus. They are also 

broadly similar to the estimates of many knowledgeable outside observers that we discuss below. 

2009:Q2 2009:Q3

GDP Growth (Percentage Points) +3.1 +3.6

Employment +434,000 +1,159,000

Source: CEA calculations. 

Table 6. Estimates of the Effect of the ARRA Using CEA Multiplier Model

B. Comparison with Other Estimates of the Effects of the ARRA 

Many other economists and forecasters have estimated the likely effects of the Recovery 

Act. Most of those estimates are based on formal macroeconomic models. These estimates 

provide further evidence about the effects of the act, and serve as a check on the reasonableness 

of our own estimates.

Table 7 reports estimates of the contribution of the ARRA to GDP growth in the second 

and third quarters of 2009 from an array of public and private forecasters.24 The first row 

                                                           

24 The sources are as follows. CBO: Congressional Budget Office (2009b, p. 33). Goldman Sachs: Goldman 

Sachs (2009). IHS/Global Insight: described in IHS/Global Insight (2009); exact numbers from Nigel Gault, email 

communication, August 28, 2009. James Glassman, J.P.Morgan Chase: Glassman (2009). Macroeconomic 

Advisers: Macroeconomic Advisers (2009a, 2009b). Moody’s economy.com: described in Zandi (2009); exact 
25

repeats the estimates from Section III based on the comparison of actual outcomes with 

projections of the normal evolution of the economy, and the second row shows our model-based 

estimates described above. The next two rows show the low and high projections prepared by 

the Congressional Budget Office.25 The estimates from both of our approaches are well within 

the CBO range, and are generally in its lower part. To put the numbers in context, recall the real 

GDP fell at an annual rate of 1.0 percent in the second quarter. An estimate that the ARRA 

added 2.3 percentage points to GDP growth in that quarter implies that in the absence of 

stimulus, real GDP would have fallen at a 3.3 percent annual rate. 

2009:Q2 2009:Q3

CEA: Projection Approach +2.3 +2.7

CEA: Model Approach +3.1 +3.6

CBO: Low +1.9a +1.9a

CBO: High +5.1a +5.1a

Goldman Sachs +2.2 +3.3

IHS/Global Insight +2.3 +2.3

James Glassman, J.P.Morgan Chase +3.0 +4.0

Macroeconomic Advisers +2.1 +1.9

Mark Zandi, Moody's Economy.com +2.8 +3.6

NABE Survey +0.5 +0.8b

Sources: See text for details.

Notes: a. Data reflect the average effect on growth, 2009:Q2 - 2009:Q4.

Table 7. Estimates of the Effects of the ARRA on GDP Growth

Percentage Points, Annual Rate

b. Approximate. NABE reports that about 1/3 of respondents expect the Recovery Act to add less than 0.5 

percentage points to growth in the second half of 2009, and slightly over half expect it to add between 0.5 and 1.5 

points; the remainder presumably expect it to add more than 1.5 points.

The remaining lines of the table show the private sector estimates that we have been able 

to gather. These estimates are generally similar to the estimates from our projection-based 

approach and slightly below those from our model-based approach. 

 

The one set of private sector estimates that stands out as much lower than all the others is 

that from a survey conducted by the National Association of Business Economics. Since these 

are the results of a survey, we have no information about the reasoning behind them. The survey 

reflects the views of a substantial number of economists. At the same time, the average amount 

of effort devoted to each individual response to the survey was almost certainly much smaller 

                                                                                                                                                                                               

numbers from Mark Zandi, email communication, September 4, 2009. NABE Survey: National Association of 

Business Economics (2009). 

25 CBO estimated a range for the likely effects on the level of GDP in 2009:Q4. We convert these into growth 

projections by assuming that the Recovery Act would have no impact on growth before 2009:Q2 and that the effect 

on growth would be uniform over 2009:Q2-2009:Q4. Consider, for example, CBO’s low estimate that the Act 

would raise the level of GDP in 2009:Q4 by 1.4 percent. The constant growth rate that would generate a rise of 1.4 

percent over three quarters is 0.46 percent per quarter (since 1.00463

 = 1.014). At an annual rate, this is 1.9 percent 

(since 1.00464

= 1.019). 
26 

than the effort that went into the other estimates reported in the table. 

There are far fewer estimates of the employment effects of the Recovery Act. The ones 

that we have been able to gather are reported in Table 8, together with the estimates from our 

two approaches.26 Again, our estimates are well within the ranges of other projections. 

2009:Q2 2009:Q3

CEA: Projection Approach +507,000a +1,040,000b

CEA: Model Approach +434,000 +1,159,000

CBO: Low +300,000 +600,000

CBO: High +767,000 +1,533,000

IHS/Global Insight +250,000 +690,000

Macroeconomic Advisers +250,000 +620,000

Moody's Economy.com +502,000 +1,073,000

Sources: See text for details. 

Note: a. Datapoint reflects an estimate for June.

b. Datapoint reflects an estimate for August.

Table 8. Estimates of the Effects of the ARRA on Employment

This discussion shows that there is nothing unusual about CEA’s estimates of the impact 

of the Recovery Act on GDP growth and employment: our estimates are consistent with a broad, 

though not universal, consensus of numerous professional forecasters. The fact such a wide 

range of public and private forecasters broadly agree with our assessment should increase 

confidence that the Act is having a substantial stimulative effect. 

Given the widespread agreement that the ARRA is contributing strongly to real GDP 

growth and the change in employment, it is natural to wonder why both GDP and employment 

have continued to fall since the Act was passed. The answer rests in the baseline trajectory of 

the economy. The contractionary shocks that hit the U.S. and world economy last fall and winter 

were so strong that they set in motion an economic decline of nearly unprecedented proportions. 

Indeed, the downward trajectory was more severe than most forecasters predicted and than 

economic indicators suggested at the time the ARRA was proposed and passed. In an economy 

in a severe downward slide, fiscal stimulus naturally first manifests itself as a smaller 

contraction. Only once recovery is established do the effects show up in GDP increases and 

employment gains. 

                                                           

26 The CBO estimates are from Congressional Budget Office (2009c). The estimates from Macroeconomic Advisers 

are from an email communication, August 10, 2009. The sources for the other estimates are the same as in Table 7. 
27

V. EVIDENCE OF EFFECTS FROM THE EXPERIENCE OF MANY COUNTRIES27

Nearly every industrialized country and many emerging economies undertook fiscal 

stimulus in response to the financial and economic crisis. By supporting demand throughout the 

world, these policies have helped to soften the downturn. They also allow us to examine another 

type of evidence about the effects of stimulus. 

A. Fiscal Stimulus around the World 

As the full onset of the world financial crisis was being realized at the start of 2009, many 

countries decided that an aggressive fiscal stimulus was necessary. The logic was similar to that 

behind the ARRA. Aggregate demand was falling rapidly, and in many cases conventional 

monetary policy was largely out of ammunition. It was hoped that government spending and tax 

cuts could step into the breach and provide the necessary lift to the economy to prevent a slide 

into a deep recession or worse. 

The stimulus measures used in this analysis are an average of three published estimates of 

stimulus across countries: an International Monetary Fund (IMF) report on stimulus in G20 

countries, a Brookings Institution report on stimulus announcements, and an Organisation for 

Economic Co-operation and Development (OECD) report on stimulus.28 The estimates are 

typically quite close. Table 9 shows the amount of fiscal stimulus estimated to take effect in 

2009 as a share of GDP.29 Although many countries (including the United States) have stimulus 

that will extend beyond 2009, the estimates below are strictly for the portion of stimulus that will 

be done in 2009. The strength of the stimulus varied across the world, ranging from Italy’s near 

non-existent stimulus (0.1 percent of GDP) to Korea’s 3.0 percent of GDP. The average 

stimulus for the full sample is 1.6 percent of GDP, and for the OECD is 1.5 percent. The U.S. 

stimulus was above average, estimated at 2 percent of GDP for 2009. 

                                                           

27 Many of the results in this section are developed in greater detail in the CEA report “The Effects of Fiscal 

Stimulus: A Cross-Country Perspective.” 

28 IMF (2009); OECD (2009a); Brookings Institution (2009). Both the IMF and OECD measures include any 

stimulus announcements up through the middle of June 2009. The Brookings figures were not updated after March, 

so stimulus announced in the late spring is not included. Including the Brookings estimates in the average thus 

slightly down-weights any stimulus announced after March. Given that we seek to measure the impact on second 

quarter GDP, this is appropriate. The Brookings estimates are largely based on a prior IMF report, although they 

include calculations by Brookings staff as well. A simple average of just the IMF and OECD estimates is correlated 

with our measure at 0.98, so the decision to include the Brookings estimates does not play a substantial role. 

29 The sample of countries is based on data availability for stimulus, private forecast data, and actual real GDP 

growth in 2009:Q2. There is a slight difference between this table and that in Romer (2009). Since that speech, we 

have found a Brookings estimate for stimulus in South Korea. Adding that to our average slightly lowers the 

estimate of South Korea’s stimulus and shifts the accompanying figures slightly. No qualitative conclusions change. 

In addition, three countries have not released second quarter GDP data and have been dropped from the sample. 
28 

Country Share of GDP Country Share of GDP

Australiaa 2.2% Koreaa 3.0%

Canadaa 1.7% Mexicoa 1.4%

China 2.6% Norwaya 1.2%

Czech Republica 1.6% Polanda 0.8%

Francea 0.6% Russia 2.9%

Germany

a 1.5% South Africa 2.2%

India 0.6% Swedena 1.4%

Indonesia 1.4% Switzerlanda 0.6%

Italya 0.1% United Kingdoma 1.5%

Japana 2.4% United Statesa 2.0%

Source: CEA estimates based on IMF, OECD, and Brookings data. 

Note: a. Country is an OECD member.

Table 9. Discretionary Fiscal Stimulus in 2009 around the Globe

Stimulus plans were not simply a function of how bad the shock in 2009 was expected to 

be. In fact, there is no correlation between the size of stimulus and forecasts for the performance 

of the economy in the second quarter of 2009.30 Countries that experienced a bigger drop in the 

fourth quarter of 2008 undertook a slightly larger stimulus, but this relationship is not 

statistically significant and the relationship can explain only a small share of stimulus variation.31

The size of discretionary stimulus is correlated with other fiscal policy, however. 

Discretionary stimulus is not the only way fiscal policy responds to a crisis; automatic stabilizers 

(unemployment insurance, welfare, reduction in taxes collected due to lower payrolls, and so on) 

are triggered when an economy slows down. The size of automatic stabilizers present in the 

economy appears to be negatively correlated with the size of discretionary stimulus. We use the 

level of taxation in the economy as a proxy for automatic stabilizers. Countries with large levels 

of taxation see immediate automatic stabilizers as any lost income immediately reduces taxes. 

Those same countries often tend to have more generous social safety nets (funded by their higher 

taxes). As Figure 11 shows, those countries that already had large automatic stabilizers in place 

as of 2006 appear to have done less discretionary fiscal stimulus.32 

                                                           

30 A regression of stimulus size on the difference between predicted growth in 2009:Q2 and average growth in the 

2000’s generates a coefficient close to zero (-0.07) with a standard error of 0.10 and an R2

 of 0.03. The data on 

forecasts are described in more detail below. 

31 The correlation between fourth quarter GDP growth and size of stimulus is -0.29. Regressing stimulus on fourth 

quarter GDP growth generates a statistically insignificant coefficient of -0.037, suggesting a 1 standard deviation 

difference in fourth quarter growth rates (roughly 6 percentage points) leads to a 0.2 percent of GDP larger stimulus. 

The R2

 is 0.09, thus explaining a small amount of the variation. See CEA, “The Effects of Fiscal Stimulus: A 

Cross-Country Perspective,” for more details. 

32 A consistent measure of level of taxation is only available across the OECD countries. We use the measure of 

taxation in the economy from OECD (OECD, 2009b). The correlation between the stimulus and the tax share is 

-0.48. 
29

Australia

Canada

Czech Republic

France

Germany

Italy

Japan

Korea

Mexico

Norway

Poland

Sweden

Switzerland

United Kingdom

United States

0

1

2

3

20 30 40 50

Tax revenue (percent of GDP)

Sources: OECD; IMF; Brookings Institution; CEA calculations.

Note: the regression line is stimulus = 3.1 - 0.046 * (tax share).

The coefficient on tax share is significant at the 90% confidence level. The R-squared is 0.23.

Stimulus (percent of GDP)

Figure 11. Stimulus and Tax Share of the Economy

B. The Impact of Stimulus on Growth 

Countries have different normal rates of growth, and they have experienced the shock of 

this crisis to different degrees. Thus, a key element of examining the cross-country evidence 

about the effects of stimulus is to build a counterfactual: what would we expect to have 

happened to countries’ economies in the absence of stimulus? 

 

We use as our measure of the counterfactual the private sector forecast by J.P.Morgan of 

GDP growth for the second quarter of 2009 that was made in November 2008.33 The 

J.P.Morgan forecast has the advantage over market average expectations of being reported far in 

advance (before any stimulus is announced) and of having public forecasts for a wide set of 

countries made on a specific day.34 We take these expectations and subtract them from current 

performance to get a measure of whether countries outperformed expectations. Current 

performance is measured by the actual GDP growth rate in the second quarter of 2009.35

                                                           

33 See J.P.Morgan (2008). 

34 As a robustness check, we also explore a simple time-series forecasting model to predict a “no-stimulus” growth 

rate across countries. Results using this method are consistent with the results provided here. They can be found in 

the CEA report “The Effects of Fiscal Stimulus: A Cross-Country Perspective.” 35 For Norway we use the Mainland GDP series (which is what J.P.Morgan forecasts), and we use the J.P.Morgan 

seasonal adjustment of Russia’s data given that this is the series that is consistent with their forecast. China and the 

Czech Republic’s flash estimate release only year on year changes at the quarterly frequency, so we use 

J.P.Morgan’s estimate of what those yearly changes imply for quarterly growth. See J.P.Morgan (2009). 
30 

If countries that experienced larger negative shocks adopted greater stimulus, the 

relationship between stimulus and the difference between actual performance and pre-crisis 

expectations will tend to understate the benefits of stimulus. As noted above, however, our first 

effort to look for such an effect – the examination of the relationship between stimulus and prestimulus expectations of growth in 2009:Q2 – finds no evidence of such behavior. However, this 

does not fully eliminate the possibility that one source of the cross-country variation in stimulus 

was variation in the size of shocks. 

A more serious problem is the negative correlation between discretionary stimulus and 

automatic stabilizers. Countries with smaller discretionary packages tended to have larger 

swings in automatic policy. As a result, total fiscal stimulus in the countries with low 

discretionary stimulus is more similar to the countries with high discretionary stimulus than the 

measure of discretionary stimulus alone suggests. Thus, examining the relationship between 

discretionary stimulus and growth performance relative to expectations could underestimate the 

impact of stimulus on growth. 

A final possible confounding factor is the possibility of other policies that are correlated 

with discretionary fiscal policy. If monetary policy stimulus or some other policy that increases 

growth is positively correlated with discretionary stimulus, we might mistakenly attribute some 

of the impact of the other policy to fiscal stimulus. Alternatively, if countries that pursued less 

discretionary stimulus used other policies more, our analysis will understate the effects of 

stimulus. For all of these reasons, our analysis should be interpreted with caution. 

Figures 12 and 13 show the relationship between discretionary stimulus and the 

difference between actual growth in the second quarter and pre-crisis expectations for the full 

sample of countries and for OECD countries only. There is a clear upward sloping relationship. 

Countries that undertook larger stimulus outperformed expectations when compared to countries 

that undertook smaller stimulus. The relationship is even stronger for the OECD-only sample. 

Some of the outliers in Figure 12 are non-OECD countries like South Africa. It is sensible that 

the relationship may be more consistent across the OECD countries, which have more 

similarities in the way fiscal policy is pursued, the channels through which it affects the 

economy, and the extent to which the shock of the recession hit them. 
31

Australia

Canada

China

Czech Republic

France Germany India Indonesia

Italy

Japan

Korea

Mexico

Poland Norway

Russia

South Africa

Sweden

Switzerland United KingdomUnited States

-5

0

5

10

0 1 2 3

Discretionary stimulus in 2009 (percent of GDP)

Sources: OECD; IMF; Brookings Institution; J.P.Morgan; CEA calculations. 

Note: the regression line is (growth - forecast) = -2.6 + 1.95 * stimulus.

The coefficient on stiumulus is significant at the 95% confidence level. The R-squared is 0.20.

Actual Q2 GDP growth minus November forecast (percentage points)

Figure 12. Outperforming Expectations and Stimulus, Full Sample

Australia

Canada

Czech Republic

France Germany

Italy

Japan

Korea

Mexico

Poland Norway

Sweden

Switzerland United KingdomUnited States

-5

0

5

10

0 1 2 3

Discretionary stimulus in 2009 (percent of GDP)

Sources: OECD; IMF; Brookings Institution; J.P.Morgan; CEA calculations.

Note: the regression line is (growth - forecast) = -3.1 + 2.34 * stimulus.

The coefficient on stiumulus is significant at the 95% confidence level. The R-squared is 0.26.

Actual Q2 GDP growth minus November forecast (percentage points)

Figure 13. Outperforming Expectations and Stimulus, OECD Sample

In both samples, this relationship is statistically significant. Further, despite including 

only one explanatory variable – size of stimulus – we can explain a considerable amount of the 

variation in how well countries performed relative to expectations. The R2

 is 0.20 for the full 

sample and 0.26 for the OECD sample. 
32 

The coefficient on stimulus is 1.95 in the full sample and 2.34 for the OECD sample. 

Taken literally, this would suggest that a stimulus of 1 percent of GDP led to faster growth in the 

second quarter of 2 percentage points (at an annualized rate).36 This would be a substantial 

multiplier. We do not know the precise distribution of stimulus spending by quarter. If more 

than a quarter of the spending was in 2009:Q2, we might want to interpret the multiplier as 

somewhat smaller. 

The results suggest that rather than having a GDP growth rate of -1 percent in the second 

quarter of 2009, absent the stimulus of 2 percent of GDP in 2009, the United States may have 

had a GDP growth rate in the range of -3.1 to -5 percent.37 This estimate that the stimulus led to 

a growth rate 2.1 to 4 percentage points higher in the second quarter is consistent with the 

analysis presented in Sections III and IV suggesting the U.S. growth rate was about 2.3 to 3.1 

percentage points higher due to stimulus. 

As noted, automatic stabilizers may partially mitigate the estimated relationship between 

stimulus and growth. If we control for the tax share of the economy in the OECD sample, we 

find even stronger results. The coefficient on stimulus gets even larger and the picture becomes 

even clearer.38 

Observers in many countries see the link between stimulus and the beginnings of 

recovery. Chinese officials credit stimulus with being crucial to its GDP performance.39 The 

German statistical agency reported that not only was government spending higher because of the 

stimulus there, but personal consumption expenditure’s positive contribution to growth was 

largely a result of stimulus (specifically, Germany’s “cash for clunkers”).40 In Japan, according 

                                                           

36 To be clear, the growth rate is annualized, meaning if one had higher stimulus of 1 percent of GDP, one would 

expect higher growth of 2 percentage points over the whole year, suggesting a multiplier of 2. If one-quarter of the 

stimulus is spent in the second quarter (so 0.25 percent of GDP) and the quarterly growth rate is higher by 0.5 

percent, we again get a stimulus multiplier of 2. 

37 The forecast in November 2008 for 2009:Q2 growth for the Unite States was 0 percent. The constant in the 

OECD sample suggests countries would have fallen short of expectations by 3.1 percentage points if they had done 

no stimulus. That suggests absent stimulus the United States would have had a growth rate of -3.1 percent. 

Alternatively, the coefficient in the regression suggests that the 2 percent of GDP stimulus the United States did 

should have lifted U.S. growth by about 4 percentage points, so without a stimulus the United States would have 

grown at a rate of roughly -5 percent. The range across these two methods is attributable to the fact that the United 

States lies slightly below the regression line. 

38 See CEA report “The Effects of Fiscal Stimulus: A Cross-Country Perspective.” When we control for the tax 

share, this helps explain the relatively small stimulus in France and Norway (and hence shifts these points to the 

right – towards the regression line), and shifts Mexico to the left as it had low stimulus and a low tax share. These 

adjustments lead to a larger, more significant coefficient. 

39 Zhuang Jian, senior economist with the Asian Development Bank, stated that government-led investment and 

ample credit are the main reason behind the growth in China. Also, the spokesman for the National Bureau of 

Statistics in China has stated that the stimulus package was the reason for improving economic performance. For 

example, extensive government construction has helped fixed asset investment increase 33.5 percent in the last six 

months, the most in five years. See Xinhua News (2009). 

40 See Statistisches Bundesamt Deutschland (2009). 
33

to government officials, public investment has shown a steady improvement and private 

consumption has been supported by the effects of the policy packages.41 And, in Korea, the 

statistical agency reported that in the second quarter, construction investment and government 

expenditure showed sustained growth, and construction investment growth was due to an 

increase in the public sector.42 Stimulus has not acted alone. In both Germany and Korea, 

exports have been an important part of a return to growth, but stimulus has played a significant 

role. 

The cross-country evidence relies on a small number of outcomes and the stimulus 

measures are for a year, and hence not the perfect measure of stimulus in the quarter. As a result, 

all of these estimates are subject to some revision and substantial uncertainty. But, we do see a 

consistent positive statistically robust relationship between stimulus and growth performance. 

Countries with stimulus did better than expected, and did so by a margin that is consistent with a 

sizable multiplier effect. 

VI. THE IMPACT OF STATE FISCAL RELIEF43

One central feature of the ARRA is that it contains a multitude of different tax cuts and 

spending increases. In this section, we discuss in more detail the impact of one component that 

has been particularly significant in the early months of the Act: fiscal relief to the states. 

 

State budget relief has been especially important because states, which normally must 

end the year with a balanced budget, experienced budget gaps of up to 20 percent of their general 

funds at some point during the 2009 fiscal year. In response to these gaps, states were already 

raising taxes and reducing spending by the time the ARRA was passed.44 These actions not only 

placed further burdens on families already suffering from the recession and cut crucial services, 

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

helped mitigate some of the tax increases and cuts to government social programs and services 

that otherwise would have taken place. 

Another reason that state fiscal relief has been important is that funds can be disbursed 

quickly. As Table 2 showed, this relief comprised a large majority of the stimulus in the first six 

weeks of the ARRA. And, through the end of August, $38.4 billion of fiscal relief has been 

provided to the states. This represents almost half of outlays and one-quarter of total ARRA 

stimulus (that is, outlays plus tax reductions). 

                                                           

41 See Cabinet Office, Government of Japanese (2009). 

42 See Bank of Korea (2009). 

43 Many of the results in this section are developed in greater detail in the CEA report “The Effects of State Fiscal 

Relief.” 

44 National Conference of State Legislatures (2009). 
34 

The two main forms the relief has taken are an adjustment in the Federal Medicaid 

matching rate (FMAP) and an increase in formula grants to state governments for education 

through the State Fiscal Stabilization Fund.45 Of the $38.4 billion provided through the end of 

August, $28.1 billion came through the higher Federal share of Medicaid spending, and the 

remainder through increased education grants. 

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.46 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. However, 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 

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

To investigate the effects of state fiscal relief, we clearly cannot simply ask whether 

states that have received more ARRA funds have generally performed better: as we described, 

the ARRA was designed so that states that were “sicker” on average received more “medicine.” 

To get evidence about the effects of the fiscal relief, we therefore 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. In addition to the increases tied to states’ economic circumstances, 

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 

45 Indeed, as discussed in Section II, we include only these two categories of ARRA outlays in computing state fiscal 

relief. Spending on specific projects and support for individuals hurt by the recession that are paid for via the states 

are classified as government investment and aid to those directly impacted by the recession, respectively. 46 A possible effect operating in the opposite direction is that states with larger economic declines might 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. 
35

0.062 times Medicaid spending per person in the state in 2007. Since this component, which we 

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

recession, it is almost certainly 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 present evidence elsewhere that 

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

states that received more money and states that received less.47 Figure 14 shows the estimated 

non-cyclical ARRA Medicaid payouts for each state. 

0

20

40

60

80

100

120

140

160

AK

AL

AR

AZ

CA

CO

CT

DC

DE

FL

GA

HI

IA

ID

IL

IN

KSKY

LA

MA

MD

ME

MI

MN

MO

MS

MTNCND

NE

NH

NJ

NM

NVNY

OH

OK

OR

PA

RI

SCSD

TN

TX

UT

VA

VT

WA

WI

WVWY

Figure 14. 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. 

We can then study the relationship between the change in state employment from January 

to July (the latest month for which we have employment data by state) and the estimated ARRA 

non-cyclical Medicaid payout. This comparison can show whether the states that received 

relatively large amounts of this type of fiscal relief saw smaller declines in employment. 

Figure 15 shows the relationship between state fiscal relief not tied to economic 

conditions and economic performance. The horizontal axis plots our estimated non-cyclical 

ARRA Medicaid payouts (per person) that a state received. The vertical axis shows the change 

in the percent of the state’s population that was employed from January 2009 to July 2009.48 

Because the outcome variable is measured more precisely for states with larger populations, the 

                                                           

47 See Council of Economic Advisers, “The Effects of State Fiscal Relief.” 48 The outcome variable is the change in the state’s seasonally adjusted employment from January to July 2009, 

divided by its 2008 population. The data come from the Bureau of Labor Statistics (BLS) of the Department of 

Labor, Current Employment Statistics (CES). 
36 

best-fit line weights states by their population. However, the weighting affects the results little.

The size of the circle represents the size of a state’s population.49

-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 15. 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 relative to what otherwise would 

have occurred.50 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. Nonetheless, the picture changes little if 

we control for variables like region or industry composition.51 

For fiscal relief to affect economic outcomes, it has to affect state budgetary decisions. 

One concern with fiscal relief is that states might not spend it but instead use it to bolster their 

                                                           

49 Without weights, the coefficient on estimated payouts is 0.0106 and is significant at the 99 percent confidence 

level. We have 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; the 

coefficient on estimated payouts is 0.0076 and is significant at the 99 percent level. 

50 We calculate this number as follows. We multiply the difference between $120 per capita and $60 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, approximate 10 million, to 

arrive at 45,600. As stressed in the text, these results are correlations and should not be interpreted as a causal 

relationship. 

51 See CEA report “The Effects of State Fiscal Relief” for a fuller discussion. The relationship is not sensitive to 

moving the initial month earlier or later by a month or moving the final month earlier by a month. Furthermore, 

there is no significant relationship between estimated ARRA Medicaid payments and employment during preARRA periods such as June to December 2008. 
37

“rainy day” funds. Available evidence indicates that this did not occur. By June 2009, 42 states 

had cut their planned fiscal 2009 budgets by $31.6 billion total.52 If states increased their rainy 

day funds, it would mean that they were cutting programs while increasing savings in the same 

fiscal year, which seems unlikely. 

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

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

contains both the rainy day fund and the state’s ending balance. Figure 16 plots the estimated 

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

terms.53 The best-fit line is slightly downward sloping, the opposite of what one would expect if 

larger transfers resulted in total balances build-up. 

-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 Governors

Association and 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 16. Total Budget Reserve Balances

Many state governors have described 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.”54 Governor Martin O’Malley of Maryland told of “looking down the barrel of those 

                                                           

52 Budget cut data are from National Governors Association and National Association of State Budget Officers 

(2009). 

53 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 a 

state’s rainy day funds are taken from National Governors Association and National Association of State Budget 

Officers (2009). 

54 Brewer (2009). 
38 

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

until the ARRA passed and allowed the state to “maintain [its] programmatic funding levels.”55

Governor Deval Patrick of Massachusetts 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.”56 

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 

sectors where state governments provide a large amount of financial support. Figure 17 shows 

the relationship between the estimated amount of fiscal relief and the change in the percent of the 

population employed in state and local government, education, and health care.57 

-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 17. Change in Government Employment

The figure shows that states that received more dollars in fiscal transfers added or saved 

more jobs in these sectors. Comparing Figure 17 to Figure 15, about one-quarter to one-half of 

the relationship between estimated non-cyclical ARRA Medicaid payouts and total employment 

results from jobs created or saved in government-related sectors. 

Of course, this analysis is not a definitive examination of the effects of state fiscal relief. 

For example, it is based on only six months of data. As more data become available and the 

existing data are revised, the jobs picture may become clearer. And, importantly, looking at 

                                                           

55 O’Malley (2009).

56 Patrick (2009). 

57 There is a similar correlation if we restrict attention to government employees only. 
39

state-level outcomes gives only a partial picture of the economic benefits of state fiscal relief. 

Because there are spillovers across states, important parts of the effects of relief to one state will 

be felt in other states. Our analysis does not incorporate these spillover effects. 

Despite these caveats, this preliminary analysis adds to the general evidence that fiscal 

stimulus improves short-term economic outcomes, and provides some direct evidence that 

stimulus remains effective when it takes the form of fiscal aid to the states. 

VII. CONCLUSION

This report provides an initial assessment of the economic impact of the American 

Recovery and Reinvestment Act of 2009. Because we are still in the early stages of the Act, it 

must be reiterated that all of are findings are preliminary and subject to substantial uncertainty. 

Later reports will be able to examine a longer and richer set of economic indicators, including 

the estimates of jobs retained or created reported by ARRA recipients, and will surely lead to 

new findings and refinements to our analysis. 

Because of this inherent uncertainty, we have approached the task of evaluating the 

impact of the ARRA from a wide range of perspectives. Importantly, the different approaches 

yield remarkably consistent findings. Both time-series econometric analysis and standard 

economic model-based analysis indicate that the Recovery Act has helped to change the 

trajectory of the economy. The estimates suggest that the ARRA will likely add about 3 

percentage points to real GDP growth in the third quarter and will have raised employment by 

roughly 1 million relative to what would have happened without stimulus. 

Further evidence on the impact of fiscal stimulus is provided by examining the 

experience of a number of countries. Countries throughout the world have responded to the 

crisis by enacting stimulus packages. However, they have differed substantially in the size of 

those packages. Our analysis suggests that countries with larger fiscal stimulus measures have 

experienced better outcomes relative to expectations than those with smaller packages. And, the 

estimated sensitivity is consistent with other estimates of the impact of the ARRA in the United 

States. 

Because fiscal relief to the states has been a key component of the early months of the 

stimulus, we look in more detail at how states have responded. We find no evidence of the 

Recovery Act funds being squirreled away in state rainy day funds. Instead, as governors 

throughout the country have emphasized, the money has gone into maintaining state and local 

employment and hence crucial state services. We find that state fiscal relief has helped raise 

state employment relative to what it otherwise would have been. 
40 

In this context, it is useful to mention the Car Allowance Rebate System (CARS), the 

program commonly referred to as “Cash for Clunkers.” Though not part of the original ARRA, 

the popular CARS program was funded largely with ARRA funds that were reallocated by 

supplemental legislation. As described in a separate report, the CEA has conducted an analysis 

of the evidence to date on the effects of the program.58 The surge in automobile sales in July and 

August was one of the largest two-month increases in history. Our estimates suggest that the 

program likely added between 0.1and 0.4 percentage points to real GDP growth in the third 

quarter of 2009. It is likely increasing employment relative to the baseline by roughly 40,000 to 

120,000 in the second half of 2009. 

While important in its own right, the CARS program also has much in common with a 

range of initiatives in the ARRA. The First-Time Homebuyer Tax Credit, the business 

investment incentives, and the weatherization subsidies are all programs designed to move 

demand from the future, when it is likely to be less crucial, to today, when it is clearly vital to 

generating recovery. That the CARS program has had beneficial effects is suggestive that these 

elements of the ARRA will as well. 

In the quarters to come, the Council of Economic Advisers will continue to investigate 

the impact of the individual components and the overall effectiveness of the American Recovery 

and Reinvestment Act of 2009. In this way, we hope to provide Congress and the American 

people with the accountability they expect and deserve, and future policymakers with 

information about the impact of this bold action to rescue the American economy.

                                                           

58 CEA Report, “Economic Analysis of the Car Allowance Rebate System.” 
41

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