World Economic Outlook, October 2008 - Chapter 5: Fiscal Policy as a Countercyclical Tool, October 2, 2008

159159

c h a p t e r

This chapter investigates whether fiscal policy should

be used to combat business cycle fluctuations, especially

downturns. Can discretionary fiscal policy successfully

stimulate output? Or does it do more harm than good?

New evidence presented here, from emerging as well as

advanced economies, indicates that the effects of fiscal

stimulus can be positive, albeit modest. But policymak-

ers must be very careful about how stimulus pack-

ages are implemented, ensuring that they are timely

and that they are not likely to become entrenched and

raise concerns about debt sustainability. The chapter

concludes with a discussion of how automatic stabiliz-

ers could be made more effective and how governance

improvements could reduce “debt bias” concerns related

to discretionary actions.

n recent months, as economies have been

buffeted by falling asset prices, rising costs

for raw materials and credit, and waning

conﬁdence, there have been renewed calls

for governments to actively use ﬁscal policy to

support efforts taken by central banks to prevent

sharp declines in activity. Once again, there is a

lively debate about the appropriate role of ﬁscal

policy in managing the business cycle, especially

during a downturn: Are discretionary ﬁscal

actions helpful, or do they sometimes do more

harm than good? When is a discretionary pack-

age most effective? When is it better simply to

let automatic stabilizers do the job?

The debate over the appropriate role of ﬁs-

cal policy in managing the business cycle has

persisted for many years. One school of thought

argues that taxes, transfers, and spending can

be used judiciously to lean against ﬂuctuations

in economic activity, especially to the extent that

economic ﬂuctuations are mainly due to mar-

kets falling out of equilibrium instead of react-

ing to changes in fundamental factors such as

productivity. Others contend that ﬁscal policy

actions are generally either ineffective or make

things worse, because the actions are ill timed

or they create damaging distortions. This latter

point of view has dominated the debate over the

past two decades; consequently, ﬁscal policy has

taken a backseat to monetary policy. But there

also has been a recognition that there are times

when monetary policy needs the support of ﬁs

cal stimulus, such as when nominal interest rates

approach zero or the channels of monetary

policy transmission are in some way impeded.

Against this background, this chapter takes

a fresh look at the role of ﬁscal policy during

economic downturns. The main objectives are

to (1) analyze how ﬁscal policy has typically

responded during downturns; (2) examine the

effects on economic activity of ﬁscal stimulus

during downturns; (3) identify the main fac-

tors that affect the outcomes of ﬁscal policy

interventions; and (4) offer policy suggestions,

in light of both empirical evidence and insights

from theoretical work, on (a) whether and when

to use discretionary ﬁscal policy, (b) the implica

tions of using various ﬁscal policy instruments,

and (c) the appropriate balance between auto-

matic stabilizers and discretionary actions.

This chapter seeks to contribute to the con-

siderable literature on ﬁscal policy as a counter-

cyclical tool in three ways. First, it speciﬁcally

evaluates whether discretionary ﬁscal policy

responses to downturns have been timely and

temporary. Second, whereas most previous

studies have focused on the effects of policy in

advanced economies, this chapter also looks

at evidence for emerging economies. Finally,

the chapter complements the empirical analy-

sis with simulation analysis designed to assess

how ﬁscal multipliers depend on the choice of

The main authors of this chapter are Alasdair Scott

(team leader), Steven Barnett, Mark De Broeck, Anna

Ivanova, Daehaeng Kim, Michael Kumhof, Douglas

Laxton, Daniel Leigh, Sven Jari Stehn, and Steven

Symansky, with support from Elaine Hensle, Annette

Kyobe, Susanna Mursula, and Ben Sutton.

FISCAL POLICY AS A COUNTERCYCLICAL TOOL

CHAPTER 5 Fiscal Policy as a countercyclical tool

160

ﬁscal instruments and the characteristics of the

economy.

The policy record shows that discretionary

ﬁscal policy has been more timely than some

critiques suggest. But there are valid concerns

about whether ﬁscal stimulus packages will be

temporary and the implications for the path

of government debt. Empirical evidence sug-

gests that discretionary ﬁscal stimulus has a

moderately positive effect on output growth

in advanced economies. However, the effects

appear to be constrained in emerging econo-

mies. This might be because of credibility

issues, especially debt concerns. Simulation

experiments show that ﬁscal multipliers can

vary considerably, depending on the instrument

used, the degree of monetary policy accom-

modation, and the type of economy. Consistent

with the empirical evidence, increases in interest

rate risk premiums as a result of debt concerns

can render ﬁscal multipliers negative, suggesting

that discretionary ﬁscal stimulus may do more

harm than good.

Does this mean there is no role for counter-

cyclical ﬁscal policy? In practice, the extent of

automatic stabilizers has been related to the size

of government, but more extensive government

is generally associated with lower growth. Given

this dichotomy, it is worth investigating further

whether countercyclical ﬁscal rules and the ﬁscal

policy framework can be designed to increase

the ability of ﬁscal policy to smooth ﬂuctua-

tions in output and income over the course of

business cycles—without increasing the size of

government or placing debt stability at risk.

The chapter is organized as follows. The next

section provides a brief review of the empirical

and theoretical literature on the role of ﬁscal

policy in stabilizing output. The following two

sections present, ﬁrst, the results of new empiri-

cal work that characterizes how ﬁscal policy

has been used in both advanced and emerging

economies and then an analysis of its effects.

The subsequent section uses formal simula-

tion-based analysis to examine the effectiveness

of various stimulus options and the effects of

various macroeconomic factors when the policy

is implemented. The concluding section offers

some policy suggestions.

Understanding the Fiscal Policy Debate

Fiscal policy can work in two general ways to

stabilize the business cycle. One way is through

automatic stabilizers, which arise from parts of

the ﬁscal system that naturally vary with changes

in economic activity—for example, as output

falls, tax revenues also fall and unemployment

payments rise.

Discretionary ﬁscal policy, on the

other hand, involves active changes in policies

that affect government expenditures, taxes, and

transfers and are often undertaken for reasons

other than stabilization.

By their nature, automatic stabilizers play an

immediate role during downturns. But they are

usually by-products of other ﬁscal policy objec-

tives. As such, the size of automatic stabilizers

tends to be associated with the size of govern-

ment (see, for example, Fatás and Mihov, 2001),

suggesting that an increase in the size of govern-

ment can help dampen output volatility (see

Galí, 1994). However, many argue that a larger

government acts as a drag on growth over the

longer term. Hence, there is a potential con-

ﬂict between increasing stability and increasing

economic efﬁciency. Moreover, the effectiveness

of automatic stabilizers may be more a matter of

proper design than size.

Because automatic stabilizers are often limited

in scope—Box 5.1 reviews the extent of auto-

matic stabilizers across economies—the active

use of discretionary ﬁscal measures is often

promoted as a countercyclical tool. Skeptics,

however, question governments’ ability to deliver

well-timed measures as well as the macroeco-

nomic effects of discretionary ﬁscal measures

and the longer-term implications for ﬁscal

sustainability.

Hence, the strength of automatic stabilizers depends

on the size of transfers (such as the scope of unemploy-

ment insurance), the progressivity of the tax system, and

the effects of taxes and transfers on labor participation

and demand for workers and capital.

161

How important are automatic stabilizers?

This box looks at their quantitative impact

on the ﬁscal balance, especially in compari-

son with discretionary ﬁscal policy. First, the

impact of automatic stabilizers on the primary

balance varies across countries. The volatil-

ity in the primary balance is more a result of

changes in discretionary policy than of auto-

matic stabilizers. However, for many countries,

changes in discretionary policy are not well

synchronized with the business cycle, suggest-

ing that automatic stabilizers are often a more

important source of systematic countercyclical

policy actions.

Automatic stabilizers are measured using

the change in the cyclical balances estimated

in the event analysis in the main text of this

chapter.

The impact of automatic stabiliz-

ers on ﬁscal outcomes varies across countries

and is positively related to both government

size and output volatility. Government size is a

good proxy for the size of automatic stabilizers,

and provides the horizontal axis in the first

figure.

Realized volatility in the cyclical bal-

ance—measured as the standard deviation of

the change in the cyclical balance—is roughly

equal to government size times the volatil-

ity in the output gap. The ﬁrst ﬁgure shows

that even though emerging economies have

smaller governments, they tend to experience

higher volatility in the cyclical balance than

advanced economies. This is largely because

emerging economies have more volatile output

gaps. However, looking separately at emerging

economies and advanced economies (to control

for the higher output volatility in emerging

economies), there is a positive relationship

between government size and cyclical bal-

ance volatility—that is, countries with larger

The main author of this box is Steven Barnett.

The elasticity-based measure is used for the analysis

in this box. The sample period is 1992–2007.

Balassone and Kumar (2007), Box 4.2, explains

why this holds. This general ﬁnding is robust to

income elasticity assumptions.

automatic stabilizers have more variation in the

cyclical balance.

Changes in discretionary ﬁscal policy,

however, account for more of the volatility of

primary balances than automatic stabilizers. On

average, the volatility of the cyclically adjusted

balance is about three times greater than that

of the cyclical balance. This is true for advanced

economies and for emerging economies. But

the extent to which these policy changes play a

countercyclical role depends on how well they

are synchronized with the business cycle. To

examine this empirically, a measure of the cycli-

cality of ﬁscal policy discretion is compared with

Government size, however, is often found to

be negatively correlated with output volatility (for

example, Andrés, Doménech, and Fatás, 2008), which

would dampen the otherwise mechanical positive

relationship between government size and cyclical

balance volatility.

Box 5.1. Differences in the Extent of Automatic Stabilizers and Their Relationship with

Discretionary Fiscal Policy

understanding the Fiscal Policy debate

10 20 30 40 50 60

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Volatility in Cyclical Balance

Source: IMF staff calculations.

Standard deviation of change in cyclical balance

Government size (percent of GDP)

Emerging economies

Advanced economies

CHAPTER 5 Fiscal Policy as a countercyclical tool

162

the size of automatic stabilizers.

The second fig-

ure shows that discretionary ﬁscal policy tends

to be more countercyclical in advanced econo-

mies (when the countercyclicality of discretion

is greater than zero), but is often procyclical in

emerging economies (below zero). The units

on the two axes are comparable and indicate

the percentage point change in the respective

balance (after dividing by 100) for a 1 percent

age point increase in the output gap. If a coun-

try lies above the 45-degree line, it indicates that

discretionary policy makes overall ﬁscal policy

more countercyclical than automatic stabilizers

Cyclicality of ﬁscal policy is measured by a regres-

sion, run in ﬁrst differences, with the cyclically

adjusted primary balance as the dependent variable

and the output gap as the explanatory one. A positive

coefﬁcient indicates a more countercyclical policy.

This regression, however, is potentially problematic in

that it ignores the relationship (endogeneity) between

ﬁscal policy and the output gap.

do. As can be seen, this happens in only a few

cases, including some of the Anglophone coun-

tries with smaller governments, as well as some

of the Nordic ones with larger governments.

However, there is little systematic evidence that

countries with smaller governments compensate

for weaker automatic stabilizers by using more

discretion.

Together, these ﬁndings would suggest that

(1) automatic stabilizers have, in general,

played a more consistently countercyclical role

than discretionary ﬁscal policy, and (2) changes

in discretionary ﬁscal policy are either poorly

timed or related to factors other than output

stabilization. A caveat, however, is that ﬁscal

policy discretion is measured by the cyclically

adjusted balance, which, as discussed in the

main text, is an imperfect proxy, because it may

also capture factors unrelated to discretionary

changes, notably asset price ﬂuctuations.

Asset price movements directly affect

ﬁnancial transaction and capital gains taxes,

but they also have broader, indirect revenue

implications, notably through a wealth effect

on consumption. To the extent that these

movements do not fully track the business

cycle (for example, ampliﬁed ﬂuctuations rela-

tive to those of the output gap), the revenue

effects will not be captured by conventional

tax revenue elasticities and will be part of the

cyclically adjusted component of revenue. In

an unpublished study, the IMF staff prepared

econometric estimates of the short-run sen-

sitivity of cyclically adjusted tax revenue to

house and equity price ﬂuctuations in the G7

countries. The cyclically adjusted revenue data

are computed using the conventional adjust-

ment methods, ensuring consistency of the

results. The estimates suggest that a 1 percent

decline in both house and equity prices could

reduce total tax revenue by up to almost 1

percent, with the house price decline account-

ing for most of the drop. The estimates also

indicate that Canada, Japan, the United King-

dom, and the United States are more sensitive

to house and equity price ﬂuctuations than

the continental European G7.

Box 5.1 (concluded)

0 10 20 30 40 50 60

-100

-50

100

Cyclicality of Structural Balance

Source: IMF staff calculations.

Cyclicality of discretion

Government size (percent of GDP)

Emerging economies

Advanced economies

163

These skeptics argue that discretionary ﬁscal

measures cannot be delivered quickly enough

by legislatures, especially compared with the

speed with which a central bank can change

its policy rate. Hence, there is a risk that ﬁscal

stimulus will arrive just as the economy recovers

from a downturn. Moreover, argue the critics,

ﬁscal stimulus measures are not likely to be well

targeted, but are likely instead to be directed

to wasteful and distortionary public spending

and revenue measures more responsive to the

pressures of interest groups than the needs of

the economy. Furthermore, they are not likely

to be withdrawn sufﬁciently quickly to pre-

serve ﬁscal sustainability. For instance, there is

widespread evidence that ﬁscal policy in emerg-

ing and less developed economies is procyclical

rather than countercyclical, in part because of

political incentives to run larger deﬁcits in good

times, when ﬁnancing is available (Talvi and

Végh, 2000).

Even if ﬁscal stimulus can be delivered

quickly, does that justify the use of discretionary

ﬁscal policy? There is still considerable debate

and little theoretical consensus. A textbook

Keynesian position is that private consumption

and investment are driven by current income,

with the implication that output is highly

responsive to changes in ﬁscal policy. But ﬁscal

policy can be much less effective in an open

economy, depending on the degree of capital

mobility and the exchange rate regime, because

ﬁscal stimulus might simply “leak out.” In addi-

tion to the standard crowding-out arguments,

many neoclassical theorists emphasize the role

of expectations about future income and taxes,

arguing that ﬁscal multipliers are likely to be

small because forward-looking households will

ﬁgure out that temporary ﬁscal stimulus mat

ters little to their lifetime income; multipliers

may even be negative, if increased government

expenditures lead to offsetting reductions in

private consumption and investment.

By con-

For example, the well-known Ricardian equivalence

critique of Barro (1974) argues that households and

ﬁrms understand that deﬁcits accompanied by future tax

trast, recent work using so-called New Keynesian

models argues that an increase in government

consumption still can have positive consump-

tion and real wage effects, if there are nominal

and real rigidities and liquidity constraints (see,

for example, Galí, 2006). These models also

suggest that not all temporary ﬁscal measures

are ineffective: policies that affect the incentive

to switch the timing of consumption—such as

changes in consumption taxes—are likely to be

most effective when they are understood to be

temporary rather than permanent.

In recent years, four factors may have become

increasingly relevant:

•

The extent of market rigidities: Rigidities in goods

and labor markets may have decreased over

time, as a result of microeconomic reforms,

and access to credit may have become more

widely available, reducing fiscal multipliers.

•

The monetary policy framework: The impact of

fiscal policy can be expected to increase if it

is accommodated by monetary policy, thus

alleviating the crowding-out effect.

•

Globalization and openness: To the extent that

economies are more integrated—that is, an

increasing share of domestic demand falls on

imported goods—discretionary fiscal policy

will be less effective today than previously.

•

Financial innovation: Deregulation of finan-

cial markets and increased access to global

capital may have eased credit constraints on

households and firms, with the implication

that consumption and investment are less con-

strained by current income and less respon-

sive to discretionary fiscal policy measures.

However, cross-border financial integration

can also reduce the sensitivity of interest rates

to government borrowing and ease crowding-

out effects.

Unfortunately, empirical work has not settled

the theoretical debates. Estimates of ﬁscal multi-

rises leave them no better off in net present value terms,

and therefore they save rather than spend temporary

(lump-sum) tax cuts. Neoclassical models often exhibit

negative wealth effects following increases in govern-

ment spending that are strong enough to reduce private

consumption and investment.

how has discretionary Fiscal Policy tyPically resPonded?

CHAPTER 5 Fiscal Policy as a countercyclical tool

164

Perhaps surprisingly, the empirical literature

on the effects of ﬁscal policy does not provide a

clear answer to the simple question of whether

discretionary ﬁscal policy can successfully

stimulate the economy during downturns. Esti-

mates of the effects of ﬁscal policy on many key

macroeconomic variables can differ not merely

in degree but in sign. This box aims to show

why demonstrating conclusively what happens as

a result of discretionary ﬁscal policy is, in fact,

extremely difﬁcult.

Any empirical work on this issue faces the

following problems: (1) Every assessment of

the impact of a policy change must take into

account the economic circumstances when the

policy was implemented. (2) A ﬁscal stimulus

can be achieved by many different combina-

tions of taxes, transfers, and spending, each of

which can have different effects. (3) There will

sometimes be a difference between the date on

which a change in ﬁscal policy is measured from

the data and the date on which the policy was

common knowledge to households and ﬁrms.

(4) Policy measures and economic activity are

both endogenous—they depend on each other

at the same time—and so it is not immediately

clear what determines what just by looking

at simple correlations. This last problem is

arguably the most difﬁcult to overcome. The

researcher must somehow strip out those parts

of changes in taxes, transfers, and spending that

occur passively (such as from automatic stabiliz-

ers) from those that represent the true policy

initiative, and use that measure of ﬁscal impulse

to determine the effects on economic activity.

To illustrate, suppose overall ﬁscal policy, g,

evolves according to

g = (a + b)y + h, (1)

where y is the output gap. For simplicity, one

can think of g as representing only government

expenditures, so that a stimulus occurs when

g is positive. There are two reactions of ﬁscal

policy to the state of the economy: an automatic

component, represented by a, and a system-

atic discretionary component, represented by

b. Unexpected discretionary ﬁscal policy is

denoted by h.

Now suppose that the output process is

y = dg + ε, (2)

where d is the ﬁscal multiplier and ε repre-

sents shocks independent of policy. There are

two signiﬁcant problems presented by this

system. First, we have a classic simultaneity

problem—attempting to assess the effects of

ﬁscal policy on output by estimating (1) will

result in biased estimates. The second prob-

lem is a measurement problem—the difﬁculty

of distinguishing systematic discretionary

policy changes from automatic stabilizers. The

elasticity-based ﬁscal impulse measure can be

thought of as using OECD estimates of a and

constructing

= f – ay.

Estimating the cyclicality of this measure is

equivalent to estimating the parameter b.

1,2

When examining the effectiveness of ﬁscal

policy in the regression framework, a ﬁscal

impulse measure that mistakenly includes cycli-

cal changes generated by automatic stabilizers

will lead to invalid inferences about the effects

of discretionary ﬁscal policy. The second ﬁscal

impulse measure therefore focuses entirely

on h, the effects of unexpected ﬁscal policy

shocks.

Other approaches in the literature attempt

to address the same issues. Structural vector

autoregressions (SVARs) use statistical criteria

to estimate shocks to ﬁscal policy and measure

See also Galí and Perotti (2003) for an application

of the same method.

When looking at the reaction of ﬁscal policy in

emerging economies, it is necessary to make the

“zero-one” assumption of income elasticities of expen-

ditures and revenues, which is a cruder approach to

measuring a but conceptually the same.

For precise details on how the ﬁscal impulse mea-

sures are constructed, see Appendix 5.1.

Box 5.2. Why Is It So Hard to Determine the Effects of Fiscal Stimulus?

The main author of this box is Alasdair Scott.

165

how has discretionary Fiscal Policy tyPically resPonded?

how well those shocks can explain movements

in output that are not accounted for by other

economic shocks. Three problems are poten-

tially relevant. As with reduced-form regressions,

statistical assumptions need to be made to iden-

tify the ﬁscal shocks. Second, most VARs ignore

the importance of debt dynamics in condition-

ing responses (whether or not a temporary rise

in debt causes households and ﬁrms to expect

future higher taxes is a key distinction between

Keynesian and classical views on the effective-

ness of discretionary ﬁscal policy).

Finally, as

with reduced-form regressions, VARs might not

reliably be able to resolve the timing issue.

By contrast, “narrative” approaches estimate

policy-driven changes in ﬁscal stimulus by look-

ing directly at the historical record of legisla-

tion and public statements. The advantage of

this approach is that careful attention can be

directed to picking the timing of the shocks by

examining carefully when policy decisions were

made and announced. But such studies are very

resource intensive, making their application

across countries almost impossible. Further,

they are subjective, just as VARs and reduced-

form analysis rely on identifying assumptions. In

practice, analysis has centered around a small

number of extraordinary episodes of military

buildups, and there are questions as to how

much can be learned from such episodes about

discretionary ﬁscal policy during downturns.

A ﬁnal approach examines speciﬁc “natural

experiments,” such as the effects of tax rebates.

See Chung and Leeper (2007). Favero and Giavazzi

(2007) do include debt stock.

The advantage of this approach is that it can

be directed at speciﬁc episodes for which it is

relatively easy to identify the policy change and

its intent. The corresponding disadvantage is

that, by examining a speciﬁc case, it can be hard

to draw broader lessons for policy.

This empirical work provides a mixed

picture of the ability of government spend-

ing to stimulate private demand.

(There is

less evidence about revenue-based measures.)

Moreover, there appears to be a pattern

between the method used and the qualitative

results obtained. The table summarizes the

results of a selection of prominent papers in

the literature in terms of the signs of responses

of key variables to discretionary increases in

government spending.

In particular, SVAR-based studies in which

ﬁscal interventions are identiﬁed by assum-

ing that government spending is predeter-

mined within the quarter (see Blanchard and

Perotti, 2002) tend to ﬁnd relatively strong

positive effects, whereas narrative stud

ies that rely on the reactions to episodes of

extraordinary spending have tended to ﬁnd

much weaker, and even negative, relation-

ships between episodes of ﬁscal stimulus and

Results from case studies usually ﬁnd positive

effects, but the effects are generally not as strong as

those generated by VAR studies. Studies of the 1975

tax rebates generally conclude that the effects were

positive but modest (that is, short-run multipliers of

about 0.2–0.5); see Modigliani and Steindel (1977)

and Blinder (1981). Studies of the 2001 tax rebates

have generated similar results; see Shapiro and

Slemrod (2002).

Assessment of Impacts of Discretionary Fiscal Policy Stimulus by Empirical Method

Output Private Consumption

Private Investment

in Durables

Private

Capital Investment

VAR studies Neutral to positive Neutral to positive Negative to positive Negative to positive

Narrative studies Positive Negative Negative . . .

Case studies Positive Positive . . . . . .

Note: Studies placed in the vector autoregression (VAR) category include Fatás and Mihov (2001); Mountford and Uhlig (2002);

Blanchard and Perotti (2002); and Galí, López-Salido, and Vallés (2007). Studies placed in the narrative category include Ramey and

Shapiro (1998) and Edelberg, Eichenbaum, and Fisher (1999). Case studies include Johnson, Parker, and Souleles (2006).

CHAPTER 5 Fiscal Policy as a countercyclical tool

166

pliers cover a wide range, from positive through

insigniﬁcant to negative.

One reason is that

taking account of all the appropriate condition-

ing factors can be very difﬁcult. Another reason

is methodological. Put simply, separating out

changes in discretionary ﬁscal policy from auto-

matic stabilizers and evaluating their effects is

very difﬁcult—in particular, ﬁscal policy simul-

taneously both responds to and causes changes

in economic activity. This “endogeneity prob-

lem” poses a major challenge for estimating the

effects of ﬁscal policy, as discussed in Box 5.2.

How Has Discretionary Fiscal Policy

Typically Responded?

The previous section identiﬁed two types of

critique of ﬁscal policy: skepticism that discre-

tionary ﬁscal policy can be delivered efﬁciently,

owing to political constraints, and doubts that

it can be effective, for economic reasons. These

critiques frame the empirical analysis in this

A typical range of expenditure multipliers would be

from 0.5 (for example, Mountford and Uhlig, 2002) to

about 1 (for example, Blanchard and Perotti, 2002). But

Perotti (2007) has outliers as high as 4 and Krogstrup

(2002) as low as –2.

section, which examines how ﬁscal policy has

typically responded to downturns.

Deﬁning economic downturns and measur-

ing ﬁscal stimulus are inevitably somewhat

subjective exercises. In the analysis that follows,

downturns are deﬁned as periods during which

either the growth rate is negative or the output

gap is unusually negative, the precise thresh-

old depending on whether quarterly or annual

data are used. This deﬁnition is arguably more

sensible than deﬁning a downturn simply in

terms of negative growth, because that would

miss periods during which output is signiﬁcantly

below potential but still rising.

The measures of ﬁscal stimulus used in this

chapter all start with the primary ﬁscal balance,

the difference between total general govern-

ment revenues and expenditure net of interest

payments on consolidated general government

liabilities. Changes in the primary balance can

arise passively, as revenues and expenditures rise

and fall with economic activity, or actively, as

governments make choices about tax, transfer,

and spending policies. What is needed, there-

fore, is a measure of the cyclically adjusted pri-

mary balance, the intuition being that changes

in the cyclically adjusted primary balance should

reﬂect changes in policy. The ﬁrst part of this

consumption.

Ramey (2008) suggests that this

difference relates to the way that VARs treat

timing—if discretionary ﬁscal policy measures

are pre-announced, and households decrease

their spending right away (as predicted by neo-

classical theory), VARs that measure the effect

based on actual changes to ﬁscal balances or

components might record a rise in the growth

rate of consumption on that date. This would

support a Keynesian view of ﬁscal policy, but

in fact the growth in consumption is driven

Note, however, that narrative studies of the effects

of tax changes ﬁnd very large multipliers—see Romer

and Romer (2007).

by recovery from the previous fall. Narra-

tive approaches, on the other hand, take into

account the moment discretionary measures

are announced.

Compared with these studies,

the reduced-form approach employed in this

chapter is conceptually closest to the SVAR

approach of Blanchard and Perotti (2002); to

the extent that the timing criticism applies to

this paper and those like it, it also applies to

our methodology. However, a comparative nar-

rative study of all 41 economies in this study is

beyond the scope of this chapter.

But see also the rebuttal in Perotti (2007).

Box 5.2 (concluded)

167

section looks at the responses of ﬁscal policy

to changes in economic activity, identifying

automatic stabilizers with changes in the cycli-

cal component of the primary balance and

discretionary ﬁscal policy with changes in the

cyclically adjusted primary balance.

Construct-

ing this measure requires two slightly different

approaches, depending on the information

available for the economies being analyzed.

Evidence on the Responsiveness of Fiscal Policy

The empirical investigation begins with

analysis of advanced economies, for which long

spans of ﬁscal data are available on a quarterly

basis.

Discretionary ﬁscal actions are those that

change the cyclically adjusted budget balance,

using estimates of the output gap together with

estimates of income elasticities of revenues and

expenditures to extract the cyclical component

from the budget.

Figure 5.1 presents a sum-

mary of policy responses in G7 economies over

the past four decades. The numbers indicate

that discretionary ﬁscal stimulus has been deliv-

ered in downturns, but it has been used much

less frequently than automatic stabilizers and

monetary policy. Discretionary ﬁscal stimulus

has been used in about 23 percent of all down

turn quarters—less than half as frequently as

interest-rate easing—whereas automatic stabi-

lizers are observed in well over 95 percent of

downturns (upper panel).

Discretionary policy

As deﬁned in Box 5.1 and the event analysis, the

cyclically adjusted balance is a residual and embodies all

changes in the primary balance not removed by cyclical

adjustment. This includes many factors not necessar-

ily related to output stabilization, such as the impact of

structural reform, one-off items, and other economic

events (including asset price changes that are not cyclical

in nature and could therefore be identiﬁed as “auto-

matic” changes in the ﬁscal balance—see Jaeger and

Schuknecht, 2007).

For further details about the following analysis, see

Leigh and Stehn (forthcoming).

These elasticities are taken from the OECD Economic

Outlook; see Appendix 5.1 for details.

Note that automatic stabilizers do not necessarily

ease in all downturns, because the applied deﬁnition of

a downturn does not rule out an increase in growth or

the output gap (as long as the output gap is unusually

negative).

how has discretionary Fiscal Policy tyPically resPonded?

Discretionary fiscal policy has been used less frequently than monetary policy and

automatic stabilizers during downturns, and has taken longer to arrive.

0 1 2 3 4 5

0 20 40 60 80 100

Source: IMF staff calculations.

G7 comprises Canada, France, Germany, Italy, Japan, United Kingdom, and United

States.

Share of downturns with easing in:

Lag after start of downturn until policies eased

Figure 5.1. How Often and Quickly Has Fiscal Stimulus

Been Used in G7 Economies?

Group of 7 (G7) Anglophone G7 countries Other G7

Cyclically adjusted

primary balance

Cyclically adjusted

current spending

Cyclically adjusted

revenue

Cyclical primary

balance

Nominal policy

interest rate

Capital spending

Cyclically adjusted

primary balance

Cyclically adjusted

current spending

Cyclically adjusted

revenue

Cyclical primary

balance

Nominal policy

interest rate

Capital spending

Quarters

Percent

CHAPTER 5 Fiscal Policy as a countercyclical tool

168

also arrives later, on average about two and a

half quarters after the onset of a downturn, and

about one and a half quarters after interest-rate

easing (lower panel). Capital spending is par-

ticularly slow, with an arrival lag of almost four

quarters. By contrast, automatic ﬁscal easing,

proxied by a fall in the cyclical primary balance,

occurred in almost all downturns in the quarter

of the downturn itself.

The size of discretionary ﬁscal easing is also

much smaller on average than that of automatic

stabilizers. Figure 5.2 shows average impulse

responses of discretionary ﬁscal measures,

automatic stabilizers, and interest rates for the

G7 economies, drawing from vector autoregres-

sions (VARs) estimated for two samples, an

“early” sample covering 1980:Q1–1991:Q4 and

a “late” sample covering 1992:Q1–2007:Q4.

both samples, the discretionary ﬁscal easing is

much smaller than the automatic stabilizers and

is slower to arrive than both changes in interest

rates and automatic stabilizers. However, a com-

parison of the two panels also suggests that the

countercyclical response of discretionary ﬁscal

policy has strengthened since the early 1990s.

The responses of spending and revenue compo-

nents in the early sample reﬂect a combination

of mildly procyclical revenue increases, small

countercyclical current spending increases, and

large procyclical capital spending cuts. The

greater degree of ﬁscal policy countercyclical-

ity observed since the early 1990s is the result

of cuts in revenues, larger increases in current

spending, and smaller procyclical cuts in capital

spending. The response of automatic stabiliz-

See Appendix 5.1 for more details. Note that, unlike

much of the VAR literature, the analysis presented here

does not evaluate the response of growth to ﬁscal policy

shocks. Rather, the focus is on the response of ﬁscal

policy variables to changes in growth.

In the early sample, discretionary ﬁscal policy is pro-

cyclical on impact and provides a cumulative procyclical

contraction of around 0.1 percentage point of potential

GDP over four quarters. In the later sample, even though

discretionary policy still produces no stimulus on impact,

it leads to a cumulative stimulus of 0.2 percentage point

over four quarters. This ﬁnding is consistent with, for

example, Galí and Perotti (2003) and World Economic

Outlook (September 2003).

0 1 2 3 4 5 6 7 8 9

-0.5

-0.4

-0.3

-0.2

-0.1

0.0

0.1

0 1 2 3 4 5 6 7 8 9

-0.4

-0.3

-0.2

-0.1

0.0

0.1

0.2

Source: IMF staff calculations.

Early Sample (1980:Q1–91:Q4)

Late Sample (1992:Q1–2007:Q4)

Following an unexpected 1 percentage point fall in growth below potential, interest

rates and the automatic component of the fiscal balance ease on impact;

discretionary fiscal stimulus takes longer to arrive. In recent years, discretionary

fiscal policy has become more countercyclical.

Figure 5.2. How Strong Was the Fiscal Policy Response

in G7 Economies?

(Percentage point deviation; quarters on x-axis; shock occurs in period

zero)

Interest rate Discretionary policy Automatic stabilizers

169

ers remained unchanged in the second sample,

while that of monetary policy strengthened.

Figure 5.3

shows that there are noticeable

cross-country differences across advanced econo

mies. Discretionary ﬁscal policy and monetary

policy have been more timely and more coun-

tercyclical in the United States, Canada, and the

United Kingdom (the G7’s three Anglophone

countries) than in the rest of the G7. The

other Organization for Economic Cooperation

and Development (OECD) member countries

display even weaker countercyclicality than the

United States, Canada, and the United Kingdom

in both monetary and discretionary ﬁscal policy.

Data Uncertainties and the Risk of Debt Bias

A concern that often arises regarding coun-

tercyclical ﬁscal activism is that policymakers

may respond in an asymmetric manner, easing

in downturns and not tightening sufﬁciently in

upturns, implying a permanent increase in the

public-debt-to-GDP ratio with potentially adverse

consequences for long-run growth. To investi-

gate whether ﬁscal policy in G7 countries has

displayed such an asymmetric tendency, the VAR

framework is adapted to allow for an asymmetric

response to upturns and downturns (see Appen-

dix 5.1). The results suggest that both ﬁscal

policy and monetary policy are subject to an eas-

ing bias; that is, more easing during downturns

than tightening during upturns (Figure 5.4). In

contrast, automatic stabilizers respond in a sym-

metric way, with the easing observed in down-

turns almost exactly offset by tightening during

upturns.

Hence, although discretionary ﬁscal policy

has been actively used, there are valid concerns

about debt bias. For illustration, a case study

of tax-based stimulus legislation in the United

States is provided in Box 5.3. The study ﬁnds

that, although reasonably timely, 38 percent of

cyclically motivated tax cuts were permanent.

An additional concern in the analysis of

countercyclical ﬁscal activism is that policymak-

ers face substantial uncertainties regarding the

cyclical position and run the risk of destabilizing

are Fiscal Policy reactions diFFerent in emerging and advanced economies?

0 1 2 3 4 5 6 7 8 9

-0.4

-0.3

-0.2

-0.1

0.0

0.1

0.2

0.3

0.4

0 1 2 3 4 5 6 7 8 9

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0.0

0.1

Source: IMF staff calculations.

Change in interest rate

Change in discretionary fiscal balance

Following an unexpected 1 percentage point fall in growth below potential,

Anglophone countries have provided both monetary and fiscal stimulus; the rest of

the Organization for Economic Cooperation and Development (OECD) countries have

provided a weaker monetary response and procyclical discretionary fiscal tightening.

The figure displays policy responses for the late sample (1992:Q1–2007:Q4).

Figure 5.3. How Have Fiscal Policy Responses Varied

across Advanced Economies?

(Percentage point deviation; quarters on x-axis; shock occurs in period

zero)

Group of 7 (G7)

Other G7

Anglophone G7 countries

Other OECD

CHAPTER 5 Fiscal Policy as a countercyclical tool

170

the economy by responding to erroneously per-

ceived downturns. This appears to be a serious

problem, based on an assessment of the reliabil-

ity of preliminary GDP estimates produced by

national authorities.

There is a strong negative

relationship between preliminary growth esti-

mates and subsequent revisions. Forty percent

of preliminary estimates indicating negative

quarter-over-quarter growth were subsequently

revised to positive growth.

Forecast efﬁciency

tests ﬁnd strong evidence of a bias toward pes-

simism in preliminary growth estimates.

To investigate how ﬁscal policy in G7 coun-

tries has been affected by errors in growth

estimates, the VAR framework is augmented

with growth-estimation errors (see Appendix

5.1). The results reported in Figure 5.5 conﬁrm

that both ﬁscal and interest rate policy have

been affected by errors in preliminary growth

estimates, with a 1 percentage point fall in

perceived growth relative to ﬁnal revised growth

associated with an easing in interest rates and

the discretionary ﬁscal-balance-to-potential GDP

ratio by about 0.2 percentage point. This ﬁnding

suggests that concern over policy errors is well

founded, especially as ﬁscal policy decisions

appear to be less easily reversed than monetary

policy decisions, and ﬁscal policy errors bear

potentially long-lived consequences for debt.

Are Fiscal Policy Reactions Different in

Emerging and Advanced Economies?

Some of the reservations about the applica-

tion of discretionary ﬁscal policy may apply

even more strongly in less advanced economies.

Unfortunately, although the data in the previous

section were available at quarterly frequency,

consistent data for a broader set of econo-

See Appendix 5.1. See also Cimadomo (2008) for

further analysis of ﬁscal policy using real-time data.

At the same time, 30 percent of quarters that, accord-

ing to the ﬁnal data actually had negative growth, showed

positive growth in preliminary estimates.

While remaining statistically signiﬁcant, this bias

appears to have declined in recent years, possibly reﬂect-

ing the more stable and predictable growth environment.

0 1 2 3 4 5 6 7 8 9

-0.6

-0.4

-0.2

0.0

0.2

0.4

0 1 2 3 4 5 6 7 8 9

-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

Source: IMF staff calculations.

Change in interest rate

Change in fiscal balances

Following a 1 percentage point shock to growth, both discretionary fiscal policy and

monetary policy are subject to an easing bias, with more stimulus during downturns

than tightening during upturns. In contrast, automatic stabilizers respond

symmetrically to upturns and downturns. The figure displays policy responses for

the late sample (1992:Q1–2007:Q4).

Figure 5.4. Is There a Bias toward Easing during

Downturns in G7 Economies?

(Percentage point deviation; quarters on x-axis; shock occurs in period

zero)

Upturn Downturn

Automatic stabilizers

Discretionary policy

Automatic

stabilizers

Discretionary policy

171

mies are available only at annual frequency.

In what follows, the analysis uses a sample of

21 advanced economies and 20 emerging econo

mies, covering the period from 1970 to 2007.

The deﬁnition of “downturn” is conceptually

the same as used previously with the quarterly

data, but “unusually negative” is now deﬁned

as below –0.5 standard deviation of the output

gap, on account of the use of annual data.

For advanced economies, OECD estimates of

income elasticities of revenues and expendi-

tures are used to calculate the cyclical balance.

However, such estimates are not available for

emerging economies, and so it is assumed

that revenues move one-for-one with the busi-

ness cycle, but expenditures do not—that is,

the income elasticity of revenues is 1 and the

income elasticity of expenditures is zero (see

Appendix 5.1 for details). A ﬁscal expansion is

then deﬁned as a negative change in the cycli-

cally adjusted primary balance of more than

0.25 percentage point and a ﬁscal contraction

as a positive change of more than 0.25 percent

age point. When the change in the cyclically

adjusted primary balance is less than 0.25 per

centage point (either positive or negative), ﬁscal

policy is considered neutral. Hence, we have

three states for the ﬁscal stance: stimulus (397

episodes), neutral (155 episodes), and tighten-

ing (437 episodes).

In addition to the assumptions necessarily

imposed when choosing data sets and deﬁni-

tions, a number of caveats apply to analysis using

these measures. In particular, the use of annual

data limits the ability to accurately characterize

ﬁscal interventions that begin and end within

a year. Second, what is relevant is policymak-

ers’ perceptions of the state of the economy in

real time, which might differ substantially from

inferences made using revised data, but, in the

See Appendix 5.1 for a list of economies and episodes

of downturns.

Correspondingly, upturns are deﬁned as episodes

during which the output gap is above 0.5 standard devia-

tion. Potential output is measured using the Hodrick-

Prescott ﬁlter, with λ set to 6.25, the value recommended

in Ravn and Uhlig (2002).

the macroeconomic eFFects oF discretionary Fiscal Policy

Following an erroneously perceived 1 percentage point fall in growth, both

discretionary fiscal policy and monetary policy have eased, particularly in

Anglophone countries. The figure displays policy responses for the late sample

(1992:Q1–2007:Q4).

0 1 2 3 4 5 6 7 8 9

-0.25

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0 1 2 3 4 5 6 7 8 9

-0.4

-0.3

-0.2

-0.1

0.0

0.1

Source: IMF staff calculations.

Change in interest rate

Change in fiscal balances

Figure 5.5. Did G7 Economies Respond to Erroneously

Perceived Downturns?

(Percentage point deviation; quarters on x-axis; shock occurs in period

zero)

Group of 7 (G7) Other G7Anglophone G7 countries

CHAPTER 5 Fiscal Policy as a countercyclical tool

172

This box takes a closer look at whether ﬁscal

interventions in the United States have been

timely, temporary, and targeted (TTT). A

recent data set compiled by Romer and Romer

(2007) of all signiﬁcant tax changes signed

into law since 1945 permits a detailed analysis

of this issue. By consulting ofﬁcial documents,

Romer and Romer distinguish tax changes

that were explicitly motivated by cyclical

considerations from those motivated by other

factors, including long-run growth support,

debt reduction, and the ﬁnancing of additional

expenditures. Of all the 50 signiﬁcant federal

tax actions identiﬁed, 7 were assessed as cycli-

cal, and, of these, 5 were tax cuts designed to

stimulate short-run growth.

This box focuses on these ﬁve tax cuts,

implemented between 1970 and 2002, as well

as the Economic Stimulus Act, signed into law

in February 2008. The box assesses how quickly

after the onset of a downturn the tax cuts were

legislated and implemented, how temporary

they were, and how well targeted they were. In

assessing how close to a downturn the tax cuts

arrived, the analysis deﬁnes a downturn as in

the main text. Growth data to assess the 2008:

Q2 stimulus are not yet available.

The main results are as follows:

•

Timeliness: Four out of the ﬁve cyclically moti-

vated tax cuts occurred within one quarter of

a downturn (see table). In the case of 2002,

the stimulus arrived three quarters after the

downturn. The average implementation lag of

tax cuts; that is, the delay between the signing

of the legislation into law and its impact on

revenue, was one quarter.

•

Temporariness: Although only one of the six

cyclically motivated tax cuts was permanent,

the remainder contained a permanent

component (see table). In particular, about

79 percent of the tax cuts were designed to be

temporary, with an average planned dura-

tion of two quarters. Some of the tax cuts

were subsequently extended, so that a smaller

proportion—62 percent—actually ended up

Box 5.3. Have U.S. Tax Cuts Been “TTT”?

The main authors of this box are Daniel Leigh and

Sven Jari Stehn.

How Timely, Temporary, and Targeted Were the Tax Cuts?

Legislated Tax Cut

Timeliness

Temporariness

Targeting

Date

stimulus

arrived

Name of

act

Size of

stimulus

(percent

of GDP)

Date of

nearest

downturn

Inside

lag

(quarters)

Proportion temporary

Duration of temporary

portion (quarters)

Bang-

for-the-

buck score

Planned Actual Planned Actual

1970:Q1 Tax Reform 1.2 1970:Q1 1 0 0 permanent 1.0

1975:Q2 Tax Reduction 3.6 1975:Q1 1 97 78 2.3 1.0 2.5

1977:Q3 Tax Reduction

and Simplification

1.0 1977:Q4 1 77 67 1.3 1.0 1.9

2001:Q3 Economic Growth

and Tax Relief

Reconciliation

1.7 2001:Q3 1 100 100 1.3 1.3 2.4

2002:Q2 Job Creation

and Worker

Assistance

1.7 2001:Q3 1 100 67 3.7 4.0 1.3

2008:Q2 Economic Stimulus 1.1 . . . 1 100 . . . 1.6 . . . 2.7

Mean 1.6 . . . 1 79 62 2.0 1.8 2.0

Temporary stimulus is deﬁned as a stimulus that expires. Actual duration may exceed planned duration because of legislated

extensions.

Downturn is deﬁned as a quarter with negative or below-trend growth and an output gap more than one standard deviation below

zero.

Inside lag denotes the period between the date the stimulus was signed into law and the date it was implemented (quarter in which

tax liabilities actually changed).

Bang-for-the-buck score (3 = high, 2 = medium, 1 = low) indicates the degree of cost-effectiveness according to CBO (2008)

classiﬁcation.

173

absence of consistent real-time vintages of data,

it is difﬁcult to adjust for this difference.

Bearing these caveats in mind, the analysis

identiﬁed the following stylized facts:

• Emerging economies respond during down

turns with fiscal stimulus only half as fre-

quently as advanced economies: 22 percent

versus 41 percent (Figure 5.6, top panel).

When emerging economies do implement fis-

cal stimulus, the response is slightly higher, as

measured by changes in the cyclically adjusted

primary balance as a percent of potential

GDP (Figure 5.6, middle panel, first and third

bars). But this is because downturns are larger

(Figure 5.6, middle panel, second and fourth

bars).

• In just over one-third of episodes, fiscal stimu

lus involved a mixture of revenue and expen-

diture changes. Of those that relied mainly on

one kind of stimulus, expenditure measures

dominate for both advanced and emerging

economies (Figure 5.6, bottom panel).

• In emerging economies, changes in the over

all primary balance are usually procyclical,

despite countercyclical effects from automatic

stabilizers (Figure 5.7, top panel).

And they

are more procyclical in downturns when

This ﬁnding is consistent with Kaminsky, Reinhart,

and Végh (2004) and a number of other studies. It holds

advanced economies are simultaneously expe-

riencing downturns, consistent with rises in

external financing premiums (Figure 5.7, bot

tom panel). In advanced economies, changes

in the primary fiscal balance are, on average,

countercyclical, mostly because of automatic

stabilizers, as measured by changes in the

cyclical balance.

The Macroeconomic Effects of

Discretionary Fiscal Policy

Having deﬁned downturns and episodes of

ﬁscal stimulus, this section turns to the central

question: What are the macroeconomic effects

of discretionary ﬁscal policy, especially during

downturns? An event analysis identiﬁes some

of the basic patterns, using the same elasticity-

based ﬁscal impulse measure as in the previous

section, and then regressions provide a more

systematic assessment of cause and effect.

An Event Analysis of Episodes of Downturns and

Fiscal Stimulus

The event analysis shows the dynamics of key

macroeconomic variables—real GDP growth, the

across both ﬁxed and ﬂoating exchange rate regimes at

the time of the episode.

the macroeconomic eFFects oF discretionary Fiscal Policy

being temporary, and 38 percent became

permanent.

•

Targeting: The targeting efﬁciency of each

tax cut package is assessed using the cost-

effectiveness classiﬁcation scheme of the

Congressional Budget Ofﬁce (CBO, 2008),

which indicates the likely bang-for-the-buck

impact on aggregate demand of a range of

possible ﬁscal stimulus tools. Based on this

classiﬁcation scheme, three out of the six

cyclically motivated tax cuts are classiﬁed as

cost-effective. More than half of the content

of these three tax packages consisted of per-

sonal direct transfers and personal lump-sum

rebates—two ﬁscal tools assessed as being

the most cost-effective by the CBO. The most

recent, 2008, stimulus scored highest on this

account, followed by 1975 and 2001. The

least cost-effective stimulus measures were

the 1970 and 2002 tax reductions, the bulk

of which consisted of corporate lump-sum

rebates and personal and corporate tax-rate

reductions.

Hence, for the most part, ﬁscal interventions

in the United States have been timely, but not

always temporary or well targeted.

Box 5.3 (concluded)

CHAPTER 5 Fiscal Policy as a countercyclical tool

174

debt-to-GDP ratio, inﬂation, exchange rates, the

current account, and money growth—around

episodes of downturns. Table 5.1 and Figure 5.8

show how macroeconomic variables move

together with ﬁscal stimulus before, during, and

after downturns. As expected, the debt-to-GDP

ratio increases following a ﬁscal stimulus and

improves when it tightens, while current account

balances improve in the downturn year when

there is tightening and deteriorate when there is

stimulus. But for other variables, the results are

generally ambiguous. In particular, growth rates

are larger in episodes without ﬁscal stimulus, but

the change in growth rates from the downturn

year to the ﬁrst year after the downturn is some-

what larger when there is ﬁscal stimulus. These

observations are common across advanced and

emerging economies.

Table 5.2

shows median values of real GDP

growth across all economies during episodes

of downturns and ﬁscal stimulus for a num-

ber of variables that theory suggests could

have important effects: public debt, current

account balances, trade openness, and the

exchange rate regime.

Figure 5.9 shows the

difference between growth rates in the year of

the downturn and the year following. Looking

across these conditioning factors, there is little

discernible difference in the impact of ﬁscal

policy from variations in the current account

balance, openness to trade, and the exchange

rate regime, despite what theory suggests. How-

ever, the level of public debt does appear to be

associated with consistent differences in growth

outcomes—economies that implement ﬁscal

stimulus and have high public debt going into

a downturn typically experience lower growth

rates before and after the downturn year and

For the ﬁrst three of these variables, the results are

divided into “high” and “low” cases, based on the average

for that variable three years before the recession episode.

The thresholds for high and low are the median values of

the overall sample, except debt, for which the threshold

for high debt is 75 percent for advanced economies

and 25 percent for emerging economies. Exchange

rate regimes are categorized according to whether the

exchange rate was ﬁxed or ﬂoating in the ﬁrst year of the

downturn.

Advanced

economies

Emerging

economies

Both

Expenditure

Revenue

Total number of responding economies that pursued stimulus driven by:

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

Figure 5.6. Composition of Fiscal Stimulus during

Downturns for Advanced and Emerging Economies

The pie charts at the top show the types of fiscal policy response—stimulus,

neutral, or tightening—during episodes of downturns for advanced economies and

emerging economies. The bar chart indicates the average size of fiscal stimulus.

Areas indicate the average proportion of the total sample stimulus from changes in

revenues only, changes in expenditures, or both. The pie charts at the bottom

indicate the frequency of using revenue only, changes in expenditures, or both for

advanced economies and emerging economies.

Average change in cyclically adjusted primary balance during downturns

Emerging

economies

Advanced

economies

Total number of fiscal responses during downturns

Tightening

Neutral

Stimulus

Both

Expenditure

Revenue

1,2

Emerging

economies

Advanced

economies

Source: IMF staff calculations.

Average change in cyclically adjusted primary balance associated with various types of

fiscal stimulus weighted by the share of fiscal stimulus cases of a particular type among

countries that responded with fiscal stimulus during downturns.

For each group of economies the left-hand column is the change in cyclically adjusted

primary balance in percent of GDP. The right-hand column is the change in cyclically

adjusted primary balance in percent of GDP scaled by the standard deviations of changes

in output gap.

Unadjusted Scaled

175

less of a pickup in growth in the year following

ﬁscal stimulus, whereas high-debt economies

that implement ﬁscal tightening experience

stronger gains in growth.

Turning to the ways ﬁscal policy was imple-

mented, economies that employed a combi-

nation of revenue and expenditure stimulus

experienced less-severe downturns compared

with those that relied on revenue or expenditure

measures alone, although revenue-based policies

were associated with faster recoveries and higher

growth in the years following (Table 5.3).

Con-

versely, expenditure-based ﬁscal tightening was

associated with higher growth in years following

the downturn.

In summary, the event analysis indicates that

taking into account debt and the composition

of ﬁscal stimulus could be important to under-

standing the effects of ﬁscal policy. Conversely,

it is difﬁcult to see clear patterns with other vari-

ables that theory indicates could be important.

Regression Analysis

Event analysis records only associations

between ﬁscal stance and the dynamics of

the macroeconomic variable in question, but

indicates nothing about causation between the

variables.

Further, by characterizing variables

according to simple categories and considering

them one by one in isolation from one another

might hide important information about the

size of and interaction between variables. A

regression framework is used to address this.

The conceptual framework for these

regressions is an examination of the effects

of discretionary ﬁscal policy on real GDP growth,

while controlling for the potential effects from

monetary policy and other sources of demand

The small sample size of episodes involving revenue

impulse, however, warrants caution in interpreting these

results.

Growth associations are a prime example: If there are

lower growth rates in downturns when ﬁscal policy was

very aggressive, is the appropriate conclusion that ﬁscal

policy is not effective or that ﬁscal policy had to be very

aggressive because the downturn was very severe?

the macroeconomic eFFects oF discretionary Fiscal Policy

ADV EME ADV EME ADV EME

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

Source: IMF staff calculations.

Average change in the balance scaled by the standard deviations of changes in output

gap. A good year is defined as a year in which the GDP-weighted average gap of advanced

economies is below the median GDP-weighted average gap of advanced economies across

all years.

Responses of advanced and emerging economies, depending on position in cycle

The upper bar chart shows average fiscal policy responses for advanced (ADV) and

emerging (EME) economies in (left to right) GDP downturn episodes, neutral

episodes, and upturn episodes. A negative number indicates fiscal stimulus.

Discretionary fiscal policy is associated with the cyclically adjusted primary balance.

The lower bar chart shows average fiscal policy responses in emerging economies

when advanced economies are in upturns and downturns. In both charts, the

average change in the balance is scaled by the standard deviations of changes in the

output gap.

Figure 5.7. Fiscal Policy Responses in Downturns and

Upturns

(Average change, percent of GDP)

Change in primary balance

Change in cyclically adjusted primary balance

Change in cyclical balance

Downturn Neutral Upturn

Good year Bad year

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

Response of emerging economies to downturn, depending on position of

advanced economies in cycle

CHAPTER 5 Fiscal Policy as a countercyclical tool

176

stimulus, and taking into account factors that

might affect the transmission of ﬁscal stimulus.

The main regressor of interest is the ﬁscal

impulse measure.

Ideally, the ﬁscal impulse

measure would pick up all discretionary changes

in ﬁscal stance, whether from systematic reac-

tions to the state of the economy or nonsystem-

atic (that is, unexpected) discretionary actions.

The systematic component of the ﬁscal impulse

measure is, however, endogenous, which leads

to problems with statistical inference. Moreover,

as discussed in Box 5.2, it is very difﬁcult to

distinguish systematic changes in ﬁscal policy

from automatic stabilizers. In principle, the

elasticity-based ﬁscal impulse measure used in

the previous section should achieve this, but

Note that all the variables are now continuous and no

longer use the categories of the event analysis.

unless the elasticities are perfectly accurate for

each period—and potential output is measured

correctly—this type of ﬁscal impulse measure

will likely suffer from additional, measurement-

error-related endogeneity, undermining the

validity of the regressions.

To reduce these endogeneity problems and

check for robustness, a second ﬁscal impulse

measure is used that focuses exclusively on

the nonsystematic component of discretion-

ary ﬁscal policy (as is also the case in the ﬁscal

literature that uses structural vector autoregres-

sion (SVAR) and “narrative” approaches; see

Box 5.2). This measure aims to identify unex

pected changes in ﬁscal stance, based for each

country on separate regressions of revenues

and expenditures on output growth and a time

trend—see Appendix 5.1 for details. (In what

follows, this measure will be referred to as the

Table 5.1. Macroeconomic Indicators around Downturns, with and without a Fiscal Impulse: All

Economies

Median

Number of

Observations

in Downturn

Three-Year

Average before

Downturn

One Year

before

Downturn

Year of

Downturn

One Year

after

Downturn

Four-Year

Average after

Downturn

Real GDP growth

Fiscal stimulus 51 3.1 2.2 –0.1 3.6 3.2

Fiscal tightening 83 2.5 2.8 0.7 4.2 3.6

Change in debt-to-GDP ratio

Fiscal stimulus 43 –1.4 –0.5 2.2 1.1 0.8

Fiscal tightening 61 1.4 1.5 1.2 –0.9 –1.2

Change in cyclically adjusted

primary balance

Fiscal stimulus 51 0.0 –0.2 –1.1 0.0 0.2

Fiscal tightening 83 0.0 0.1 1.6 –0.2 0.2

Inflation

Fiscal stimulus 48 5.6 5.5 4.7 3.0 2.7

Fiscal tightening 78 7.1 6.2 5.2 5.0 5.1

Change in nominal exchange rate

Fiscal stimulus 41 –0.6 0.0 2.9 –0.5 0.1

Fiscal tightening 72 4.6 3.3 7.9 3.5 2.3

Current account surplus

Fiscal stimulus 51 –2.4 –2.9 –0.8 –0.9 –1.2

Fiscal tightening 81 –0.9 –0.8 0.0 0.2 –0.1

Real money growth

Fiscal stimulus 32 5.0 2.6 1.7 4.2 4.8

Fiscal tightening 54 4.6 4.3 3.3 4.9 5.0

Note: For each variable, the median is recorded for the three categories of fiscal stance during the first year of the downturn: stimulus, neutral

policy, and tightening. In each case, values are recorded for the average of the median three years before the downturn, one year before the

downturn, the first year of the downturn itself, one year after the whole downturn episode, and the average for the four years after the downturn

episode. Note that some downturns last for more than one year. In a multiyear downturn, the year after the downturn is the first year after the

last downturn year.

Fiscal impulse identified during the first year of a downturn as a decline in the cyclically adjusted primary balance to GDP below 0.25 percentage

point of GDP.

Exchange rate is given as local currency/U.S. dollars (+ sign denotes a depreciation).

177

the macroeconomic eFFects oF discretionary Fiscal Policy

regression-based ﬁscal impulse measure, to dis-

tinguish it from the elasticity-based measure.)

Other regressors include two lags of real GDP

growth, to control for endogenous inertia in the

economy; real money growth (contemporaneous

and two lags), as a measure of monetary policy;

changes in foreign demand (contemporaneous

and two lags); and government size. These were

found to be signiﬁcant at the 10 percent level

and were retained in all regression speciﬁcations

that follow.

Table 5.4

presents the key results in terms

of responses of real GDP to a 1 percent ﬁscal

impulse, using both the elasticity-based and

regression-based ﬁscal impulse measures.

The

values show the output effects in the year of the

ﬁscal intervention and three years later, with a

positive number indicating that positive ﬁscal

stimulus raises output.

The results for the base-

line speciﬁcation are presented in the ﬁrst row.

For both ﬁscal impulse measures, the estimated

effect of ﬁscal stimulus on output growth in the

baseline speciﬁcation is weak—closer to zero

than the Keynesian assumption of 1 or more—

and turns negative after three years. However, as

can be seen in the second and third rows of the

table, this conceals important differences across

countries. In advanced economies, the multipli-

ers are statistically signiﬁcant and moderately

positive—a 1 percentage point ﬁscal stimulus

leads to an increase in real GDP growth of about

0.1 percent on impact, and up to 0.5 percent

above its level in year 0 after three years. This is

broadly comparable with the effects found from

previous SVAR studies and case studies. By con-

trast, although emerging economies see impact

effects similar to those of advanced economies,

the effects on output in the medium term are

consistently negative across both ﬁscal impulse

measures—for these economies, discretionary

See Appendix 5.1 for tables of coefﬁcient estimates

and regression diagnostics.

Note, however, that the regressions underlying the

ﬁrst nine rows do not distinguish between ﬁscal stimulus

and ﬁscal tightening—a negative effect on output from

ﬁscal tightening is therefore assumed to be consistent

with a positive effect from ﬁscal stimulus.

Figure 5.8. Macroeconomic Indicators after Downturns,

with and without a Fiscal Stimulus

The bar charts indicate changes in macroeconomic indicators from the year of

downturn to the first year after downturn.

Source: IMF staff calculations.

Fiscal stimulus during the first year of a downturn is defined as a decline in the cyclically

adjusted primary balance to GDP below 0.25 percentage point of GDP.

Exchange rate is given as local currency/U.S. dollar (+ sign denotes a depreciation).

Value for emerging economies with fiscal stimulus is –10.5; with fiscal tightening, –21.2.

Fiscal tightening

-8 -6 -4 -2 0 2 4 6

Emerging economies

Advanced economies

All

Fiscal stimulus

Neutral fiscal policy

0-2

-4

-6-11

Change in current

account balance

Change in nominal

exchange rate

Change in inflation

Change in real GDP

growth

Debt-to-GDP ratio

Cyclically adjusted

primary balance

Real money growth

0-2

-4

-6-22

Change in current

account balance

Change in nominal

exchange rate

Change in inflation

Change in real GDP

growth

Debt-to-GDP ratio

Cyclically adjusted

primary balance

Real money growth

Change in current

account balance

Change in nominal

exchange rate

Change in inflation

Change in real GDP

growth

Debt-to-GDP ratio

Cyclically adjusted

primary balance

Real money growth

CHAPTER 5 Fiscal Policy as a countercyclical tool

178

ﬁscal policy does indeed appear to do more

harm than good.

The output responses shown in the next six

rows of the table indicate that, overall, rev

enue-based stimulus measures seem to be more

effective in boosting real GDP than expendi-

ture-based measures, particularly in the medium

term and in advanced economies. Expenditure-

based impulses are found to have consistently

negative effects in emerging economies after

three years, perhaps reﬂecting concerns that,

once implemented, increased expenditures are

difﬁcult to remove.

A key question is whether discretionary ﬁscal

policy can successfully stimulate the economy

during downturns. This is addressed in the ﬁnal

four rows of the table. When controlling for

downturns, the general effects of ﬁscal interven-

tions appear to be positive and, if anything, show

slightly stronger effects than the baseline speciﬁ-

cation. However, it is possible that the results for

these multipliers are driven by strong negative

effects from ﬁscal tightening and do not reﬂect

signiﬁcantly positive effects from ﬁscal stimulus.

When controlling speciﬁcally for the effects of

ﬁscal stimulus, the effects are in fact consistently

negative across the two ﬁscal impulse measures

(although there is some improvement in output

growth in the years that follow, such that the

level of output is less negative than initially).

What could be driving such a different result?

One concern is that the ﬁscal impulse measures

are not adequately dealing with the endogeneity

problem, especially the elasticity-based measure,

which could lead to biased results.

If it is not a

measurement problem, the effects could depend

on private sector expectations of the debt

implications of the ﬁscal stimulus. The ﬁnal two

rows show how the effects depend on the level

of public debt at the time of the intervention. In

low-debt economies, the initial effect of a ﬁscal

stimulus is negative, but there is a positive effect

on growth in the years that follow, such that the

net effect after three years is relatively nega-

tive when using the elasticity-based measure,

and positive when using the regression-based

measure. By contrast, in high-debt economies

For example, during downturns both ﬁscal revenues

and output fall. To the extent that the regressions do

not correct for the response of automatic stabilizers,

an automatic response might be picked up as a ﬁscal

stimulus, which, unsurprisingly, is identiﬁed as “inef-

fective” in the regressions. This is more likely in the

elasticity-based approach—the assumption of unit-rev-

enue elasticities for emerging economies, for example,

may well be too low. This would tend to bias results,

especially for the short run.

Table 5.2. Real GDP Growth and Fiscal Impulse under Various Initial Conditions: All Economies

1,2

Conditioning Variables

Number of

Observations in

Downturn

Three-Year

Average

before Downturn

One Year

before

Downturn

Year of

Downturn

Real GDP Growth

One Year after

Downturn

Four-Year

Average after

Downturn

Public debt

High 13 2.1 1.5 –0.1 2.7 2.0

Low 30 3.1 2.4 –0.3 3.6 3.2

Current account balance

High 22 2.7 2.4 0.3 2.6 2.4

Low 27 3.2 2.0 –0.7 3.9 3.4

Openness to trade

High 24 3.0 2.6 –0.1 2.7 3.1

Low 25 3.4 1.6 –0.3 3.9 3.4

Exchange rate

Fixed 20 2.8 2.0 –0.3 3.1 3.0

Floating 26 3.1 1.9 0.2 3.7 3.3

Fiscal impulse is identified during the first year of a downturn as a decline in the cyclically adjusted primary-balance-to-GDP ratio below 0.25

percentage point of GDP.

Initial conditions for variables are defined as a three-year average before the year of a downturn.

The threshold for high debt is 75 percent for advanced economies and 25 percent for emerging economies. All other variable thresholds are

the median of the variable across the sample.

A positive value for the current account balance indicates a surplus; a negative value indicates a deficit.

179

the effect is consistently large and persistently

negative. This suggests that concerns about ﬁscal

sustainability may be dominating spending deci-

sions, even if current ﬁscal policy would tradi-

tionally be thought of as stimulatory.

Additional regressions were run that included

interaction terms of the ﬁscal impulse measure

and dummies indicating (1) high or low open-

ness to trade; (2) high or low levels of ﬁnancial

development, as a measure of liquidity con-

straints; (3) ﬁxed versus ﬂoating exchange rate

regimes; and (4) high or low current account

surpluses, as a measure of external sustainabil-

ity. Higher levels of trade openness and ﬁnan-

cial development yield higher multipliers, and

multipliers are higher under ﬂoating exchange

rate regimes. These results run contrary to

economic theory, suggesting that debt concerns

might dominate the effectiveness of ﬁscal policy.

Indeed, higher-than-average current account

balances (generally surpluses) tend to be associ-

ated with larger multipliers.

Finally, running

the baseline regression using two different time

subsamples yields a cautionary note: multipliers

have apparently been weaker in recent years.

The evidence from this analysis indicates that

discretionary ﬁscal policy can successfully stimu-

late output growth, especially if it is revenue-

based. But there are reasons for caution in

employing stimulus packages during downturns,

with evidence suggesting that, if it is to work at

all, it will do so only when underlying ﬁscal posi-

tions are sound. This indicates that governments

need to improve balances during upturns and

make credible commitments that stimulus pack-

ages will not threaten debt sustainability.

The effects of both ﬁscal stimulus and ﬁscal tighten-

ing are much worse when controlling for severe down-

turns. See Appendix 5.1 for more details.

In the medium term, the multipliers are positive

when using the regression-based ﬁscal impulse measure

but still negative when using the elasticity-based ﬁscal

impulse measure.

This is particularly true for advanced economies. One

potential explanation, consistent with both the empiri-

cal evidence and the simulations presented later, is that

monetary policy has become less accommodative in those

economies.

a simulation-based PersPective on Fiscal stimulus

Figure 5.9. Changes in Real GDP Growth and Fiscal

Policies under Various Initial Conditions

The bar charts indicate changes in real GDP growth from year of downturn to first

year after downturn, differentiated by macroeconomic conditions three years before

the downturn (debt, current account, openness to trade, and money growth) and by

the exchange rate regime and composition of fiscal impulse in the year of downturn.

Source: IMF staff calculations.

The threshold for high debt is 75 percent for advanced economies and 25 percent for

emerging economies. The thresholds for current account balance and trade openness are

the median of the variable across the sample.

High Low FloatingFixed

1 1

0 1 2 3 4 5

Public debt

Current account balance

0 1 2 3 4 5

Openness to trade

Exchange rate

0 1 2 3 4 5

Fiscal stimulus

Neutral policy

Fiscal tightening

Fiscal stimulus

Neutral policy

Fiscal tightening

Fiscal stimulus

Neutral policy

Fiscal tightening

Fiscal stimulus

Neutral policy

Fiscal tightening

CHAPTER 5 Fiscal Policy as a countercyclical tool

180

A Simulation-Based Perspective on

Fiscal Stimulus

The previous section ﬁnds some evidence

for moderately positive multipliers, but with

important caveats about the type of economy,

the composition of the ﬁscal impulse, and the

level of debt. Clearly, there is a large number

of potentially important factors that policymak-

ers need to take into account when designing a

discretionary ﬁscal policy action. The objective

of this section is to examine, in a controlled

setting, how the effects of ﬁscal stimulus depend

on the structure of the economy in question.

The model used is an annual version of the

Global Integrated Monetary and Fiscal Model

(GIMF). GIMF is a multicountry dynamic sto-

chastic general equilibrium model that includes

a number of useful features relative to existing

monetary business cycle models (such as both

myopic and liquidity-constrained consumers

and potential long-term productivity beneﬁts

from government investment) and a wide range

of ﬁscal instruments affecting household and

business intertemporal choices (government

investment, labor taxes, consumption taxes, and

transfers to households).

The country blocs are the United States, the euro

area, Japan, emerging Asia, and the remaining econo-

mies. For a more detailed description of the model, see

Kumhof and Laxton (2008).

The ﬁrst exercise compares outcomes for key

macroeconomic variables using various ﬁscal

policy instruments for a large economy, cali-

brated to match the United States. The results

are presented in Figure 5.10. The shock is a

temporary ﬁscal expansion, calibrated to deliver

a primary deﬁcit that is 1 percent above baseline

in year 1 and 0.5 percent above baseline in year

2. Thereafter, a ﬁscal reaction function ensures

that debt is brought back to its initial level by

raising lump-sum taxes. The ﬁscal stimulus is

completely unanticipated in the ﬁrst year, but

its time proﬁle, including the further stimulus

in year 2 and the longer-term implications for

taxes, is fully understood once initiated. Each

row of Figure 5.10 shows the reactions of, from

left to right, GDP (in percentage deviations

from the baseline), inﬂation and nominal inter-

est rates (in percentage point deviations from

baseline), and real interest rates (in percentage

point deviations from baseline). Going down

the ﬁgure, successive rows show the impact of

various ﬁscal instruments: government invest-

ment, consumption taxes, labor income taxes,

and transfers to households. In each panel, two

responses are shown: one in which nominal

interest rates are assumed to react to expected

deviations of inﬂation from target, and one in

which nominal interest rates are held constant

for the initial two years, thereby accommodating

the ﬁscal stimulus.

Table 5.3. Real GDP Growth and Fiscal Impulse by Composition: All Economies

1,2

Conditioning Variables

Number of

Observations

in Downturn

Three-Year

Average before

Downturn

One Year

before

Downturn

Year of

Downturn

Real GDP Growth

One Year

after

Downturn

Four-Year

Average after

Downturn

Fiscal stimulus

Revenue-based impulse 5 4.4 2.8 –0.7 3.6 4.1

Expenditure-based impulse 31 3.1 2.0 –0.4 2.9 3.0

Both expenditure and revenue

impulses 15 3.0 1.6 0.6 4.1 3.5

Fiscal tightening

Revenue-based impulse 31 2.4 2.3 –0.2 3.3 3.1

Expenditure-based impulse 17 2.8 3.2 1.2 5.0 4.3

Both expenditure and revenue

impulses 35 2.7 3.3 1.1 4.3 4.2

Fiscal impulse is identified during the first year of a downturn as a decline in the cyclically adjusted primary balance to GDP below

0.25 percentage point of GDP.

Initial conditions for variables are defined as a three-year average before the year of a downturn.

181

In each case, there are no long-run changes

in potential output; eventually, each of the

variables will return to zero.

Hence, the experi-

ment focuses on the differences in the short-run

impact of the policy measures. The results show

the following:

• For the same increase in deficit, there are

large differences in the size of short-run mul-

tipliers across instruments. On the assump-

tion that it can be implemented immediately

and efficiently, government investment has

a larger effect than other measures.

This

is because it has a direct effect on aggregate

demand, whereas the effects of taxes and

transfers depend on propensities to consume.

Investment also has the largest effect on infla-

tion and real interest rates.

This is also true for government investment, but in

this case the effect on output is much more long lived,

because government infrastructure capital has productive

beneﬁts that depreciate only slowly over time.

This is in contrast to the empirical results, which

showed more positive effects from revenue-based stimu-

lus. In these simulations, private agents understand that

debt will be maintained at initial levels. In practice, it

could be that expenditure-based packages are more likely

to be made permanent and therefore raise concerns

about debt sustainability.

• The monetary policy regime plays a key role

in the effectiveness of fiscal stimulus—with

accommodation, the output multipliers

are up to twice as large, and the effects are

more persistent.

Concomitantly, inflation

is higher. The difference is least for labor

taxes, because lowering labor taxes increases

incentives for work as well as consumption. As

a result, a supply response mutes the inflation-

ary impact. It can also be shown that without

monetary accommodation, multipliers are

smaller when prices are more flexible.

This

is because inflation increases more strongly

following the stimulus, thereby necessitating

a more aggressive hike in interest rates that

reduces the output response. With monetary

accommodation, greater price flexibility has

the opposite effect, because higher inflation

implies a larger drop in real interest rates.

• Cuts in the consumption tax and temporar

ily higher household transfers have a clear

This is consistent with the view that ﬁscal policy could

be most effective when monetary policy is least effective,

such as when nominal interest rates are close to zero or

the monetary harmonization mechanism is imparied.

Simulations for different degrees of price ﬂexibility

are not shown in Figure 5.7.

a simulation-based PersPective on Fiscal stimulus

Table 5.4. Responses of Real GDP to Discretionary Fiscal Policy Changes

Real GDP Response

Elasticity-based fiscal impulse measure Regression-based fiscal impulse measure

Effect in: Year zero Year three Year zero Year three

(with respect to positive fiscal impulse by 1 percentage point of GDP)

Baseline specification 0.15 –0.16 0.08 –0.02

Country differences

Advanced economies only 0.12 0.13 0.11 0.51

Emerging economies only 0.21 –0.03 0.10 –0.09

Composition

Revenue-based policy changes 0.21 0.12 0.10 0.14

Expenditure-based policy changes 0.13 –0.21 0.06 –0.06

Composition: advanced economies only

Revenue-based policy changes 0.35 0.59 0.01 0.40

Expenditure-based policy changes –0.09 –0.26 0.15 0.52

Composition: emerging economies only

Revenue-based policy changes 0.23 0.23 0.13 0.17

Expenditure-based policy changes 0.20 –0.18 0.08 –0.23

Downturns 0.29 0.00 0.10 0.04

Fiscal stimulus only –1.30 –0.88 –0.87 –0.29

Fiscal stimulus only, high initial debt –1.75 –2.05 –1.05 –0.80

Fiscal stimulus only, low initial debt –0.96 –0.36 –0.65 0.13

CHAPTER 5 Fiscal Policy as a countercyclical tool

182

0 1 2 3 4 5

-1

Source: IMF staff calculations.

Figure 5.10. Effect of Fiscal Expansion in a Large Economy

(Deviation from baseline; years on x-axis; shock occurs in year 0)

Impulse responses to 1 percent increase in deficit in year 1 and 0.5 percent increase in deficit in year 2.

0 1 2 3 4 5

-3

-2

-1

0 1 2 3 4 5

-1.0

-0.5

0.0

0.5

0 1 2 3 4 5

-0.25

0.00

0.25

0.50

0 1 2 3 4 5

-0.5

0.0

0.5

1.0

0 1 2 3 4 5

-0.25

0.00

0.25

0.50

0 1 2 3 4 5

-1.0

-0.5

0.0

0.5

0 1 2 3 4 5

-0.25

0.00

0.25

0.50

0 1 2 3 4 5

-1.0

-0.5

0.0

0.5

0 1 2 3 4 5

-0.5

0.0

0.5

1.0

0 1 2 3 4 5

-0.5

0.0

0.5

1.0

With monetary accommodation

Without monetary accommodation

GDP

(percent)

Inflation (solid) and

Nominal Interest Rate (dashed)

(percentage points)

Real Interest Rate

(percentage points)

Transfers

Government Investment

Consumption Taxes

Labor Taxes

183

“tilting” effect on output (output is above,

then below baseline), because they provide

incentives to bring forward consumption and

investment.

Cuts in labor taxes, on the other

hand, generate a more consistently positive

supply response.

If policy measures are made permanent and

ﬁnanced by an increase in debt, then long-run

supply and debt effects become much more

important. For all ﬁscal instruments, higher debt

tends to crowd out private output because it

leads to higher real interest rates.

When there

is a permanent increase in transfers, regardless

of short-run monetary accommodation, the real

interest rate rises in the long run, which reduces

output or, at best, leaves it unchanged. Lower

tax rates, on the other hand, reduce supply

distortions, and therefore generate permanent

increases in output, more so when labor taxes

are lowered than when consumption taxes are

lowered. Making lower tax rates permanent

could raise the short-term impact, depending

on the balance between the positive supply-side

effect and negative interest rate effects. The

effects from permanently higher government

investment depend on whether the spending

can generate a higher rate of return than if the

resources were available to private investors.

How do the multipliers differ according to

the characteristics of the economy? Additional

simulations show the following:

• For any given size of fiscal stimulus, multi

pliers are lower in smaller and more open

economies—see Figure 5.11—although those

for labor taxes fall by less.

This is an example of a temporary ﬁscal policy

change that is effective because of forward-looking expec-

tations, showing that the “permanent income” criticism of

temporary policy measures does not always hold.

In small countries—that is, small enough that inter-

est rates are exogenous—this is still likely to happen.

The degree depends on changes in interest rate risk

premiums.

The empirical results in the previous section point to

the opposite result: multipliers are higher in smaller and

more open economies. This suggests that the measure

of openness used in the regressions is picking up other

effects not accounted for in these simulations.

• A higher share of liquidity-constrained con-

sumers, as might be expected in most emerg-

ing economies, results in significantly larger

multipliers.

• At the same time, fiscal stimulus may lead, in

high-debt emerging economies, to an increase

in real interest rates as market participants

demand a higher interest rate risk premium.

This reduces output multipliers, especially

for revenue-based measures, as shown in

Figure 5.12

. If the increase in interest rate

risk premiums is large enough, the multipli-

ers are negative. It is possible that this is the

mechanism driving the negative results of

fiscal stimulus seen from the empirical work

in Table 5.4.

These results indicate that the effects of ﬁscal

stimulus are likely to vary considerably, depend-

ing on how the stimulus is implemented and on

the type of economy. The results support the

idea that the degree of monetary policy accom-

modation is important, which may have played

a role in the smaller estimates of ﬁscal multipli-

ers in recent years. This is not to say that ﬁscal

policy cannot work; rather, it is likely to be most

effective when monetary policy is constrained

and ineffective (see also Blinder, 2006). The

results also illustrate a potentially important

mechanism by which concerns about public

debt sustainability could lower ﬁscal multipliers

to a point at which discretionary ﬁscal policy

would do more harm than good.

Conclusions and Policy Considerations

This chapter addresses a simple question:

What are the effects of ﬁscal policy during

downturns? The analysis indicates that the

answer is complicated and highly dependent on

an economy’s characteristics.

One obvious appeal of discretionary ﬁscal

policy is that governments can potentially have

a quick effect on spending power, whereas the

effects of monetary policy are subject to long

and sometimes uncertain lags. And in practice,

the policy record in advanced economies shows

that discretionary ﬁscal policy has been used

a simulation-based PersPective on Fiscal stimulus

CHAPTER 5 Fiscal Policy as a countercyclical tool

184

0 1 2 3 4 5

-1

Source: IMF staff calculations.

Figure 5.11. Fiscal Expansion in a Large Economy Compared with a Small Open

Economy with Monetary Accommodation

(Deviation from baseline; years on x-axis; shock occurs in year 0)

Impulse responses to 1 percent increase in deficit in year 1 and 0.5 percent increase in deficit in year 2.

0 1 2 3 4 5

-3

-2

-1

0 1 2 3 4 5

-1.0

-0.5

0.0

0.5

0 1 2 3 4 5

-0.25

0.00

0.25

0.50

0 1 2 3 4 5

-0.5

0.0

0.5

1.0

0 1 2 3 4 5

-0.25

0.00

0.25

0.50

0 1 2 3 4 5

-1.0

-0.5

0.0

0.5

0 1 2 3 4 5

-0.25

0.00

0.25

0.50

0 1 2 3 4 5

-1.0

-0.5

0.0

0.5

0 1 2 3 4 5

-0.5

0.0

0.5

1.0

0 1 2 3 4 5

-0.5

0.0

0.5

1.0

Large economy

Small open economy

GDP

(percent)

Inflation (solid) and

Nominal Interest Rate (dashed)

(percentage points)

Real Interest Rate

(percentage points)

Transfers

Government Investment

Consumption Taxes

Labor Taxes

185

0 1 2 3 4 5

-0.5

0.0

0.5

1.0

Source: IMF staff calculations.

Figure 5.12. Effect of Fiscal Expansion in a Small Economy with Market-Risk-Premium

Reaction

(Deviation from baseline; years on x-axis; shock occurs in year 0)

Impulse responses to 1 percent increase in deficit in year 1 and 0.5 percent increase in year 2.

0 1 2 3 4 5

-2

-1

0 1 2 3 4 5

-1.0

-0.5

0.0

0.5

1.0

1.5

0 1 2 3 4 5

-2

-1

0 1 2 3 4 5

-1.0

-0.5

0.0

0.5

0 1 2 3 4 5

-0.5

0.0

0.5

1.0

0 1 2 3 4 5

-0.5

0.0

0.5

0 1 2 3 4 5

-2

-1

0 1 2 3 4 5

-1.0

-0.5

0.0

0.5

0 1 2 3 4 5

-2

-1

0 1 2 3 4 5

-0.5

0.0

0.5

1.0

0 1 2 3 4 5

-0.5

0.0

0.5

1.0

GDP

(percent)

Inflation

(percentage points)

Real Interest Rate

(percentage points)

Transfers

Government Investment

Consumption Taxes

Labor Taxes

Fiscal expansion

Fiscal expansion with small market reaction Fiscal expansion with large market reaction

conclusions and Policy considerations

CHAPTER 5 Fiscal Policy as a countercyclical tool

186

actively, although not nearly as much as auto-

matic stabilizers or monetary policy. However,

discretionary measures have typically been

implemented later than automatic stabilizers

and changes in monetary stance; they are more

often a response to downturns than upturns,

sometimes more than necessary; and stimulus

measures have often been made permanent,

which has had adverse implications for ﬁscal

sustainability.

An examination of the average effects of

discretionary ﬁscal policy across a combined

sample of advanced and emerging economies

does not provide strong evidence of counter-

cyclical effects on activity. However, a closer

analysis suggests that the effects are moderately

countercyclical in advanced economies. By

contrast, there is only weak evidence for coun-

tercylical effects in emerging economies, and

only initially, with indications that effects turn

negative in subsequent years. Revenue-based

stimulus measures seem to be more effective

at boosting output than expenditure-based

measures, especially in emerging economies,

perhaps reﬂecting concerns that, once imple-

mented, increased expenditures are difﬁcult

to remove.

These empirical ﬁndings are broadly con-

sistent with simulations from a multiperiod

general equilibrium model. The simulations

show how the ﬁscal multiplier can vary from

Keynesian (1 or greater) to negative, depend

ing on the instrument used and the type of

economy. In particular, the multiplier is lower

when monetary reaction does not accommodate

the ﬁscal stimulus and when there is a strong

increase in risk premiums following ﬁscal stimu-

lus (such as when concerns about servicing

debt obligations are high). Increased govern-

ment spending can be the most direct means

of increasing output, if it can be implemented

quickly. On the other hand, it is the most

inﬂationary. Tax changes that provide greater

rewards for work effort or incentives for bring-

ing consumption forward might be nearly as

effective in supporting economic activity, with

less risk of inﬂation.

Given both the interest in ﬁscal policy as a

countercyclical tool and the evidence that discre-

tionary ﬁscal stimulus can have adverse effects,

should governments rely more on automatic

stabilizers? Or is it possible to design alternative

countercyclical ﬁscal policy mechanisms that

would respond symmetrically and more quickly

to changes in the state of economy?

There are two broad possibilities, each with its

advantages and disadvantages.

Increasing the responsiveness of automatic stabiliz-

ers: The extent of passive automatic stabilizers

could be augmented, for example, by increas-

ing the progressivity of the revenue system.

Such mechanisms would work automatically

and would not necessarily increase the size

of government. A related approach would be

to change certain tax, transfer, or spending

programs to introduce links to the state of

the economy following simple rules, akin to

the Taylor rule for setting interest rates. This

could be done by implementing pre-approved

temporary spending programs or raising

unemployment insurance beneﬁts once the

unemployment rate reaches a certain threshold.

An advantage of such an approach would be its

transparency.

However, such schemes could also bring

unintended consequences that would need

to be weighed against possible stabilization

beneﬁts. A system of temporary consumption

tax changes could lead to self-fulﬁlling falls in

current consumption if tax cuts were antici-

pated. Proposals that call for automatic triggers

in response to cyclical developments are also

problematic because there are no completely

reliable real-time measures of the state of the

economy. Responses based on previous periods’

outcomes—such as an automatic tax rebate—

could be more accurate and less distortionary

but might not be as well targeted as those that

This idea goes back at least to Musgrave (1959, p.

512), who coined the phrase “formula ﬂexibility” to

describe a system in which changes in taxes and/or

expenditures would be legislated in advance to respond

to changes in income. More recently, versions have been

advocated in Seidman (2003).

187

are based on current income. It might also be

difﬁcult to develop predetermined state-contin-

gent spending programs that are a well-targeted

and efﬁcient use of public money (Solow, 2005).

Furthermore, all of the above could introduce

distortions: schemes to increase tax progressiv-

ity or tie unemployment insurance generosity to

the state of the economy would likely alter work

incentives, and might prove politically difﬁcult

to adhere to during upturns. Thus, they would

have to ﬂanked with measures to improve the

targeting of support during downturns. Better

targeting, however, is likely to pose administra-

tive challenges that could prove expensive to

address.

Changes in ﬁscal policy governance: Broader

reforms could bolster the credibility of discre-

tionary policy actions, in particular, to reduce

the risk of debt bias. This might involve estab-

lishing an independent, nonpartisan govern-

ment agency, such as already exist in many

countries—a sort of “ﬁscal watchdog”—charged

with identifying changes in the cyclical state of

the economy, assessing the extent to which ﬁscal

policy is consistent with medium-term objectives,

and providing advice on various policy mea-

sures.

This would minimize partisan judgment

in the evaluation of economic information and

would avoid relying solely on statistical mea-

sures of the state of the economy, which can be

imprecise. In addition, this arrangement could

increase the timeliness and temporariness of

the ﬁscal impulse. Such agencies could also be

entrusted with giving advice on which tax and

expenditure parameters to vary, as they indeed

already do in a number of countries.

For example, the objective of the Swedish Fiscal

Policy Council is to provide an independent evaluation of

the Swedish government’s ﬁscal policy, including whether

ﬁscal policy is consistent with the state of the economy in

the business cycle.

Some have even proposed that governments del-

egate limited ﬁscal responsibility to these nonpartisan

agencies, for exclusive use in macroeconomic stabiliza-

tion (see Ball, 1997, and Calmfors, 2003). Under exist-

ing proposals, such agencies could vary certain tax or

expenditure parameters, within certain limits set out by

the legislative branch and on the basis of a narrow stabi-

Clearly, a careful examination of the poten-

tial costs and risks of such systems would

be required before implementing any such

approaches. In addition to the choice of ﬁscal

instruments and the administrative complexities

of changing tax rates or expenditure plans, the

system would have to be coordinated with mone-

tary policy goals (see Taylor, 2000). Nonetheless,

given the limitations of automatic stabilizers as

currently implemented and the risks associated

with discretionary ﬁscal policy, the idea deserves

further examination.

Appendix 5.1. Data and Empirical

Methods

Evidence on the Responsiveness of Fiscal Policy

Quarterly data on the output gap and real

GDP growth are taken from the OECD Economic

Outlook, and are seasonally adjusted. Downturns

are deﬁned as quarters in which growth is either

negative or below potential, with the output gap

more than one standard deviation below zero.

Changes in monetary policy are proxied by the

quarterly change in the nominal short-term

interest rate taken from the IMF’s International

Financial Statistics database. All changes are

quarter-over-quarter and unannualized. The

analysis focuses on “large” changes in discretion-

ary ﬁscal variables, deﬁned as those that exceed

0.25 percent of GDP a quarter. Similarly, discre

tionary changes in nominal short-term interest

rates are deﬁned as those that exceed 0.25 per

cent in one quarter.

The vector autoregression (VAR) is estimated

for each country using quarterly data. The vari-

ables included in the VARs, and their ordering,

are as follows: actual real GDP growth minus

potential real GDP growth, inﬂation (based

lization mandate supplemented by strict accountability

requirements. A weakness of such proposals is they pres-

ent a challenge regarding the role of government and

they make it diﬁcult to establish a dividing line between

the agency and government in terms of countercyclical

ﬁscal policy (see Debrun, Hauner, and Kumar, 2008, for

a detailed survey).

aPPendix 5.1. data and emPirical methods

CHAPTER 5 Fiscal Policy as a countercyclical tool

188

on the GDP deﬂator), changes in the nominal

interest rate, changes in the primary cyclically

adjusted ﬁscal balance, and changes in the

automatic (cyclical) ﬁscal balance. This order-

ing implies that although policy variables can

respond to growth and inﬂation shocks within

one quarter, the transmission lag from policy

variables to growth and inﬂation is at least one

quarter. Two lags of each variable are included

in the VAR.

Data Uncertainties and the Risk of Debt Bias

For the purposes of testing for asymmetric

responses, each VAR now includes the follow-

ing variables: growth when the economy is in a

downturn and zero otherwise; growth when the

economy is in an upturn and zero otherwise;

and the previously included variables, that is,

inﬂation, changes in nominal interest rates, and

changes in ﬁscal balances. As before, downturns

are deﬁned as quarters in which growth is either

negative or below potential, with the output gap

more than one standard deviation below zero.

The results are robust to changing the order-

ing of the two halves of growth (downturns and

upturns) in the VAR, to alternative ordering

for the ﬁscal and monetary policy variables,

and to including a time trend in each equation.

Because the VAR is speciﬁed in ﬁrst differences,

any trend in ﬁscal balances over the sample

period affects the constant term in the ﬁscal bal-

ance equation.

For the purposes of testing the reliability of

preliminary GDP estimates, the analysis updates

the estimates of Faust, Rogers, and Wright

(2005), which used data ending in 1997. Revi

sions are deﬁned as the difference between the

data as they stood in the most recent OECD

Monthly Economic Indicators (June 2008) and

the data when they were ﬁrst published in the

Monthly Economic Indicators. For the United

States, the United Kingdom, and Canada,

preliminary data are available beginning

in 1965:Q1. For Japan, the starting date is 1970:

Q1; for Italy and Germany, 1979:Q4; and for

France, 1987:Q4.

For the purposes of evaluating the effect

of growth estimation errors, each VAR now

includes the preliminary estimation errors in

addition to the previously included variables.

The estimation errors are ordered in the

VARs after growth and inﬂation but before the

policy variables. The results are robust to alter-

native ordering among the errors and policy

variables.

Policy Reactions in Emerging and Advanced

Economies

The analysis uses a sample of 21 advanced

economies and 20 emerging economies from

the IMF’s World Economic Outlook (WEO)

database, covering the period from 1970

to 2007.

The sample includes annual data for

general government revenues and expenditures

(net of interest payments). Other macroeco-

nomic data (for example, for external balances

and inﬂation) are sourced from the World

Bank’s World Development Indicators database,

the WEO database, and other public sources.

The list of economies and episodes of down

turn is in Table 5.5 (with years of ﬁscal stimu-

lus in bold).

In addition to the WEO data, an examina-

tion was made using the IMF’s Government

Finance Statistics Manual (GFS) data. One

advantage of this data set is that it offers

greater disaggregation—revenues can be bro-

ken down into personal, corporate, consump-

tion, and trade. Taxes and expenditures can be

broken down into household, nonproﬁt institu-

tion, and corporate transfers (subsidies); inter-

est; government employee wages; and other

expenditures as well as capital spending. More-

disaggregated data potentially allow for ﬁner

distinctions regarding the income elasticities

of taxes and spending and therefore a more

accurate measure of automatic versus cyclical

adjustments in revenues and expenditures.

Extensive comparisons were made between

Owing to data limitations, India was dropped from

the sample used for regressions.

189

WEO and GFS data for the same selection of

countries. Two major problems arose. First, to

create a sufﬁciently long time series, various

GFS vintages needed to be spliced together,

leading to situations in which the components

listed above jumped at the splice points, appar-

ently simply because of reclassiﬁcations. This

led to spurious measures of ﬁscal impulses,

taking away the theoretical advantage of using

these data. Second, long time series of GFS

data are available only for central govern-

ment. This can present a deceptive picture of

changes in ﬁscal policy. For example, estimates

of ﬁscal impulses at the central level of govern-

ment were found to be countercyclical (with

the output cycle) for all countries. This ﬁnding

deserves more investigation, but is outside the

scope of this study.

Fiscal Impulse Measures

The elasticity-based ﬁscal impulse measure

used for the stylized facts, event analysis, and

regressions is a cyclically adjusted primary bal-

ance, calculated as

real

capb

= r

– e

————,

tr–real

where r

is the revenue-to-GDP ratio in period t,

is the primary expenditure-to-GDP ratio in

period t, and Y

real

tr–real

is real output divided

by potential (trend) output in period t. These

estimates of the cyclically adjusted balance

rely on output gap estimates derived using a

time-series ﬁlter, which may not work well when

supply shocks are frequent and large, as for

many emerging economies. Applying the same

elasticities across economies (as assumed for

emerging economies), where one has a low elas-

ticity of taxes to output and another has a high

elasticity of taxes to output could lead to results

implying that the former uses discretionary

ﬁscal policy more actively than the latter,

whereas in fact the cause is stronger automatic

stabilizers.

The regression-based ﬁscal impulse measure

used for the regressions is constructed as the

Table 5.5. List of Countries and Downturn

Episodes

Country Years in Downturn

Argentina 1975, 1976, 1978, 1981, 1982, 1985, 1988,

1989, 1990, 1995, 1999, 2000, 2001, 2002

Australia

1972, 1978, 1982, 1983, 1991, 1992

Austria

1975, 1978, 1981, 1988, 1997

Belgium

1975, 1977, 1987, 1993, 2003

Brazil 1970, 1981, 1983, 1990, 1992

Canada

1975, 1982, 1991, 1992

Chile

1972, 1973, 1975, 1982, 1983, 1999

China 1976, 1990, 1991

Colombia

1976, 1977, 1983, 1985, 1991, 1992, 1999

Czech Republic

1990, 1991, 1992, 1997, 1998

Denmark

1974, 1975, 1980, 1981, 1983, 1988, 1993,

2003

Egypt 1973, 1974, 1981

Finland

1977, 1978, 1991, 1992, 1993

France

1975, 1986, 1987, 1993, 1997

Germany

1975, 1982, 1989, 1990, 1993, 2003

Greece 1974, 1981, 1982, 1983, 1987, 1993

Hungary

1985, 1988, 1990, 1991

Iceland

1975, 1976, 1983, 1985, 1988, 1991, 1992,

2003

India 1972, 1974, 1979, 1980, 1987, 2002

Indonesia 1998

Ireland 1975, 1976, 1983, 1993, 1994

Italy

1972, 1975, 1980, 1983, 1993, 2003

Japan

1974, 1975, 1987, 1994, 1998, 1999

Malaysia

1971, 1975, 1985, 1986, 1987, 1998

Mexico 1977, 1982, 1983, 1986, 1988, 1995, 2001

Netherlands

1975, 1980, 1981, 1982, 1993, 2003, 2005

New Zealand

1972, 1976, 1977, 1979, 1983, 1991, 1992,

1998

Pakistan 1970, 1972, 2002, 2003

Poland

1980, 1981, 1982, 1984, 1990, 1991

Portugal

1975, 1984, 1985, 1986, 1993, 2003

Romania

1975, 1985, 1988, 1989, 1990, 1991, 1992,

1997, 1998, 1999

Slovak Republic 1990, 1991, 1992, 1993

Slovenia 1976, 1983, 1987, 1988, 1990, 1991, 1992

South Africa

1977, 1978, 1982, 1983, 1985, 1986, 1990,

1991, 1992

Spain

1971, 1981, 1985, 1986, 1993

Sweden

1977, 1981, 1983, 1991, 1992, 1993, 2003

Switzerland

1975, 1976, 1978, 1982, 1983, 1991, 1993,

2003

Turkey 1973, 1979, 1980, 1989, 1994, 1999, 2001

Ukraine 1987, 1990, 1991, 1992, 1993, 1994, 1996,

1997, 1998, 1999

United Kingdom

1971, 1974, 1975, 1980, 1981, 1991, 1992

United States

1970, 1974, 1975, 1980, 1982, 1991

Years in bold correspond to use of a fiscal stimulus in a

downturn, with fiscal stimulus defined as a decline in the cyclically

adjusted primary balance to GDP below 0.25 percentage point of

GDP.

aPPendix 5.1. data and emPirical methods

CHAPTER 5 Fiscal Policy as a countercyclical tool

190

difference between a hypothetical primary

deﬁcit in period t assuming no changes in the

economic environment and the actual primary

deﬁcit in period t–1. As a ﬁrst step, note that

the actual primary balance in period t can be

expressed as a function of the discretionary

policies, P

, and the economic environment

prevailing in that period, E

= B(P

The change in the primary balance with respect

to the previous year can then be decomposed as

follows:

= B(P

, E

) – B(P

t–1

, E

t–1

)

= [B(P

, E

) – B(P

, E

t–1

)] + [B(P

, E

t–1

)

–

B(P

t–1

, E

t–1

)]

= DB

+ DB

The term B(P

, E

t–1

) captures what the primary

balance would have been under the period

t policies, assuming the economic environ-

ment was the same as in period t–1. It is then

possible to break the change in the balance

into two elements. The ﬁrst element,

represents the ﬁscal effects of changes in the

economic environment from

t–1

to E

. The

second element,

, captures the change in

the balance as a result of changes in discretion-

ary policies.

In practice, the initial step for calculating the

regression-based measure of ﬁscal impulse is to

estimate the following equations, assuming real

GDP growth is a good proxy for the economic

environment:

= a

+ b

· growth

+ g

· trend

+ u

= a

+ b

· growth

+ g

· trend

+ e

where R is general government revenue in per-

cent of GDP, G is general government primary

expenditure in percent of GDP, growth is real

GDP growth, trend is a time trend, and u and

e are residuals. The growth-adjusted revenue,

which indicates what the revenue would have

been in period t if the growth rate remained

unchanged from the previous period, is com-

puted as R

(growth

t–1

) = a

+ b

· growth

t–1

· trend

+ uˆ

. The growth-adjusted primary

expenditure is computed in the same way, as

(growth

t–1

) = a

+ b

· growth

t–1

+ g

· trend

+ eˆ

The measure for the primary balance that would

have prevailed in period t if the growth rate had

been equal to that in period t – 1, B(P

, E

t–1

can then be calculated as

(growth

t--1

) –

(growth

t–1

). The actual primary balance in the

previous period, B(P

t–1

, E

t–1

), is simply R

t–1

– G

t–1

The ﬁnal step in the construction of the ﬁs-

cal impulse measure is to take the difference

between the growth-adjusted measure for the

primary balance in period t and the primary bal-

ance in the previous period:

Fiscal impulse

= [R

(growth

t–1

) – G

(growth

t–1

)]

– [

t–1

– G

t–1

]

= (g

– g

) + (u

– u

t–1

)

– (

– e

t–1

Note that although uˆ

and eˆ

can be expected

to be uncorrelated with y

, uˆ

t–1

and eˆ

t–1

are cor-

related with y

Regression Analysis

Dynamic panel regressions were run using the

Arellano-Bond estimator.

The multipliers presented in Table 5.4

are derived from regression results shown

in Table 5.6 (using the elasticity-based ﬁscal

impulse measure) and Table 5.7 (using the

regression-based ﬁscal impulse measure). Note

that, because it is based on the primary balance,

a negative change in the regression-based mea-

sure represents ﬁscal stimulus, so that a negative

coefﬁcient indicates that ﬁscal stimulus typically

has a positive effect on real GDP growth. A posi-

tive coefﬁcient on the expenditures-only ﬁscal

impulse or a negative coefﬁcient on the rev-

enue-only ﬁscal impulse indicate positive effects

on growth.

Experiments were also run with single-equation

regressions for individual economies. In most cases,

the results were insigniﬁcant, indicating that there

was insufﬁcient variation in the short time samples to

adequately differentiate the effects of ﬁscal stimulus on

output growth.

191

Table 5.6. Discretionary Fiscal Policy and Growth: Regression Results with Arellano-Bond Dynamic

Panel Estimator Using Elasticity-Based Fiscal Impulse Measure

aPPendix 5.1. data and emPirical methods

Right-Hand-Side Variables

Baseline

Specification

Country

Differences,

Advanced

Economies

Country

Differences,

Emerging

Economies Downturns Components

Components,

Advanced

Economies

Components,

Emerging

Economies

Real GDP growth

Lag1 0.36 0.53 0.33 0.42 0.37 0.53 0.31

(4.18) (8.11) (3.11) (7.21) (4.08) (8.52) (2.87)

Lag2 –0.01 –0.04 0.06 0.11 0.02 –0.04 0.08

(–0.15) (–0.85) (1.11) (2.83) (0.49) (–0.67) (1.47)

Changes in cyclically adjusted

primary balance (dCAPB)

–0.15 –0.12 –0.21 . . . . . . . . . . . .

(–1.93) (–1.89) (–2.51) . . . . . . . . . . . .

Lag1 0.14 0.01 0.13 . . . . . . . . . . . .

(3.03) (0.28) (2.01) . . . . . . . . . . . .

Lag2 0.13 0.05 0.12 . . . . . . . . . . . .

(3.78) (0.90) (3.44) . . . . . . . . . . . .

Changes in cyclically adjusted

primary expenditure

. . . . . . . . . . . . 0.13 –0.09 0.20

. . . . . . . . . . . . (1.34) (–0.83) (1.59)

Lag1 . . . . . . . . . . . . –0.16 0.00 –0.21

. . . . . . . . . . . . (–2.66) (0.13) (–2.39)

Changes in revenue . . . . . . . . . . . . –0.21 –0.35 –0.23

. . . . . . . . . . . . (–3.42) (–3.97) (–3.35)

Lag1 . . . . . . . . . . . . 0.05 0.02 0.03

. . . . . . . . . . . . (1.10) (0.29) (0.49)

Lag2 . . . . . . . . . . . . 0.10 0.02 0.06

. . . . . . . . . . . . (2.23) (0.32) (1.31)

Neutral dummy x positive

fiscal impulse x dCAPB

. . . . . . . . . –0.35 . . . . . . . . .

. . . . . . . . . (–2.84) . . . . . . . . .

Lag1 . . . . . . . . . –0.15 . . . . . . . . .

. . . . . . . . . (–1.45) . . . . . . . . .

Lag2 . . . . . . . . . 0.10 . . . . . . . . .

. . . . . . . . . (1.13) . . . . . . . . .

Neutral dummy x negative

fiscal impulse x dCAPB

. . . . . . . . . –0.06 . . . . . . . . .

. . . . . . . . . (–0.71) . . . . . . . . .

Lag1 . . . . . . . . . 0.19 . . . . . . . . .

. . . . . . . . . (1.82) . . . . . . . . .

Lag2

. . . . . . . . . 0.13 . . . . . . . . .

. . . . . . . . . (1.74) . . . . . . . . .

Downturn dummy x positive

fiscal impulse x high-debt

dummy x dCAPB

. . . . . . . . . 1.75 . . . . . . . . .

. . . . . . . . . (2.36) . . . . . . . . .

Lag1 . . . . . . . . . –0.30 . . . . . . . . .

. . . . . . . . . (–0.54) . . . . . . . . .

Lag2 . . . . . . . . . –0.51 . . . . . . . . .

. . . . . . . . . (–0.98) . . . . . . . . .

Downturn dummy x positive

fiscal impulse x low-debt

dummy x dCAPB

. . . . . . . . . 0.96 . . . . . . . . .

. . . . . . . . . (3.59) . . . . . . . . .

Lag1 . . . . . . . . . –0.50 . . . . . . . . .

. . . . . . . . . (–3.60) . . . . . . . . .

Lag2 . . . . . . . . . –0.42 . . . . . . . . .

. . . . . . . . . (–2.19) . . . . . . . . .

Downturn dummy x negative

fiscal impulse x high-debt

dummy x dCAPB

. . . . . . . . . –0.44 . . . . . . . . .

(–2.05)

Lag1 0.44

(1.98)

Lag2 0.15

(1.59)

CHAPTER 5 Fiscal Policy as a countercyclical tool

192

Right-Hand-Side Variables

Baseline

Specification

Country

Differences,

Advanced

Economies

Country

Differences,

Emerging

Economies Downturns Components

Components,

Advanced

Economies

Components,

Emerging

Economies

Downturn dummy x negative

fiscal impulse x low-debt

dummy x dCAPB

. . . . . . . . . –0.52 . . . . . . . . .

. . . . . . . . . (–3.75) . . . . . . . . .

Lag1 . . . . . . . . . 0.50 . . . . . . . . .

. . . . . . . . . (2.39) . . . . . . . . .

Lag2 . . . . . . . . . 0.21 . . . . . . . . .

. . . . . . . . . (1.65) . . . . . . . . .

Deep downturn dummy x

positive fiscal impulse x

dCAPB

. . . . . . . . . 0.00 . . . . . . . . .

. . . . . . . . . (0.00) . . . . . . . . .

Lag1 . . . . . . . . . –0.80 . . . . . . . . .

. . . . . . . . . (–4.76) . . . . . . . . .

Lag2 . . . . . . . . . 0.84 . . . . . . . . .

. . . . . . . . . (4.00) . . . . . . . . .

Deep downturn dummy x

negative fiscal impulse x

dCAPB

. . . . . . . . . 0.28 . . . . . . . . .

. . . . . . . . . (1.53) . . . . . . . . .

Lag1 . . . . . . . . . 0.00 . . . . . . . . .

. . . . . . . . . (0.00) . . . . . . . . .

Lag2 . . . . . . . . . 0.57 . . . . . . . . .

. . . . . . . . . (3.63) . . . . . . . . .

Upturn dummy x positive

fiscal impulse x dCAPB

. . . . . . . . . –0.80 . . . . . . . . .

. . . . . . . . . (–4.76) . . . . . . . . .

Lag1 . . . . . . . . . 0.84 . . . . . . . . .

. . . . . . . . . (4.00) . . . . . . . . .

Lag2 . . . . . . . . . 0.28 . . . . . . . . .

. . . . . . . . . (1.53) . . . . . . . . .

Upturn dummy x negative

fiscal impulse x dCAPB

. . . . . . . . . 0.57 . . . . . . . . .

. . . . . . . . . (3.63) . . . . . . . . .

Lag1 . . . . . . . . . –0.86 . . . . . . . . .

. . . . . . . . . (–3.95) . . . . . . . . .

Lag2 . . . . . . . . . –0.57 . . . . . . . . .

. . . . . . . . . (–3.10) . . . . . . . . .

Real money growth 0.04 0.02 0.07 0.05 0.05 0.02 0.07

(1.67) (0.95) (2.16) (1.94) (1.96) (1.13) (2.16)

Lag1 0.02 0.01 0.03 –0.01 0.02 0.01 0.03

(0.91) (0.46) (1.02) (–0.46) (0.90) (1.35) (1.17)

Lag2 –0.02 0.00 –0.02 –0.02 –0.02 0.00 –0.02

(–1.30) (0.22) (–1.05) (–1.02) (–1.17) (–0.23) (–1.18)

Government size –0.03 –0.01 –0.04 –0.02 –0.03 –0.02 –0.04

(–1.97) (–0.99) (–1.56) (–2.16) (–1.88) (–1.55) (–1.45)

Trade-weighted growth of

trading partners

0.35 0.10 0.42 0.17 0.33 –0.01 0.44

(2.06) (0.71) (1.81) (1.37) (1.96) (–0.06) (1.77)

EMU dummy

–0.80 –0.13 . . . –0.67 –0.78 –0.12 . . .

(–2.35) (–0.50) . . . (–2.50) (–2.58) (–0.47) . . .

Number of observations 796 487 309 650 796 487 309

Number of countries 40 21 19 40 40 21 19

p-value for Sargan test of

overidentifying restrictions

0.000 0.000 0.003 0.000 0.000 0.011 0.002

p-value for Hansen test of

overidentifying restrictions

1.000 1.000 1.000 1.000 1.000 1.000 1.000

p-value for the test of

no-second-order serial

correlation

0.811 0.270 0.868 0.010 0.606 0.242 0.845

Dependent variable is real GDP growth. All regressions also included a set of time dummies.

EMU = European Monetary Union.

Table 5.6 (continued)

193

Table 5.7. Discretionary Fiscal Policy and Growth: Regression Results with Arellano-Bond Dynamic

Panel Estimator Using Regression-Based Fiscal Impulse Measure

Right-Hand-Side Variables Baseline

Country

Differences,

Advanced

Economies

Country

Differences,

Emerging

Economies Downturns Components

Components,

Advanced

Economies

Components,

Emerging

Economies

Real GDP growth

Lag1 0.37 0.54 0.30 0.43 0.38 0.56 0.29

(3.86) (8.09) (2.67) (7.10) (3.73) (7.58) (2.51)

Lag2 –0.03 –0.01 0.04 0.12 –0.03 –0.01 0.05

(–0.71) (–0.18) (0.83) (3.04) (–0.68) (–0.25) (0.86)

Changes in cyclically adjusted

primary balance (dCAPB)

–0.08 –0.11 –0.10 . . . . . . . . . …

(–1.18) (–1.81) (–1.50) . . . . . . . . . …

Lag1 0.04 –0.14 0.08 . . . . . . . . . …

(0.79) (–3.18) (1.25) . . . . . . . . . …

Lag2 0.06 –0.02 0.10 . . . . . . . . . …

(1.89) (–0.33) (2.00) . . . . . . . . . …

Changes in cyclically adjusted

primary expenditure

. . . . . . . . . . . . 0.06 0.15 0.08

. . . . . . . . . . . . (0.84) (2.27) (0.87)

Lag1 . . . . . . . . . . . . –0.05 0.13 –0.14

. . . . . . . . . . . . (–1.13) (2.89) (–1.78)

Lag2 . . . . . . . . . . . . –0.06 –0.01 –0.12

. . . . . . . . . . . . (–1.62) (–0.20) (–1.77)

Changes in revenue . . . . . . . . . . . . –0.10 –0.01 –0.13

. . . . . . . . . . . . (–1.87) (–0.17) (–1.90)

Lag1 . . . . . . . . . . . . –0.02 –0.13 –0.01

. . . . . . . . . . . . (–0.36) (–1.85) (–0.18)

Lag2 . . . . . . . . . . . . 0.03 –0.08 0.03

. . . . . . . . . . . . (0.97) (–1.29) (0.53)

Neutral dummy x positive

fiscal impulse x dCAPB

. . . . . . . . . –0.39 . . . . . . …

. . . . . . . . . (–3.15) . . . . . . …

Lag1 . . . . . . . . . –0.17 . . . . . . …

. . . . . . . . . (–2.43) . . . . . . …

Lag2 . . . . . . . . . 0.08 . . . . . . …

. . . . . . . . . (0.79) . . . . . . …

Neutral dummy x negative

fiscal impulse x dCAPB

. . . . . . . . . 0.07 . . . . . . …

. . . . . . . . . (0.51) . . . . . . …

Lag1 . . . . . . . . . 0.03 . . . . . . …

. . . . . . . . . (0.31) . . . . . . …

Lag2 . . . . . . . . . 0.19 . . . . . . …

. . . . . . . . . (2.28) . . . . . . …

Downturn dummy x positive

fiscal impulse x high debt

dummy x dCAPB

. . . . . . . . . 1.05 . . . . . . . . .

. . . . . . . . . (2.58) . . . . . . . . .

Lag1 . . . . . . . . . –0.37 . . . . . . . . .

. . . . . . . . . (–1.12) . . . . . . . . .

Lag2 . . . . . . . . . –0.38 . . . . . . . . .

. . . . . . . . . (–1.54) . . . . . . . . .

Downturn dummy x positive

fiscal impulse x low debt

dummy x dCAPB

. . . . . . . . . 0.65 . . . . . . . . .

. . . . . . . . . (4.87) . . . . . . . . .

Lag1 . . . . . . . . . –0.53 . . . . . . . . .

. . . . . . . . . (–5.50) . . . . . . . . .

Lag2 . . . . . . . . . –0.33 . . . . . . . . .

. . . . . . . . . (–2.52) . . . . . . . . .

aPPendix 5.1. data and emPirical methods

CHAPTER 5 Fiscal Policy as a countercyclical tool

194

Table 5.7 (concluded)

Right-Hand-Side Variables Baseline

Country

Differences,

Advanced

Economies

Country

Differences,

Emerging

Economies Downturns Components

Components,

Advanced

Economies

Components,

Emerging

Economies

Downturn dummy x negative

fiscal impulse x high debt

dummy x dCAPB

. . . . . . . . . –0.40 . . . . . . . . .

. . . . . . . . . (–1.93) . . . . . . . . .

Lag1 . . . . . . . . . 0.34 . . . . . . . . .

. . . . . . . . . (1.87) . . . . . . . . .

Lag2 . . . . . . . . . 0.14 . . . . . . . . .

. . . . . . . . . (1.29) . . . . . . . . .

Downturn dummy x negative

fiscal impulse x low debt

dummy x dCAPB

. . . . . . . . . –0.46 . . . . . . . . .

. . . . . . . . . (–3.24) . . . . . . . . .

Lag1 . . . . . . . . . 0.30 . . . . . . . . .

. . . . . . . . . (1.29) . . . . . . . . .

Lag2 . . . . . . . . . 0.21 . . . . . . . . .

. . . . . . . . . (1.69) . . . . . . . . .

Upturn dummy x positive

fiscal impulse x dCAPB

. . . . . . . . . –0.91 . . . . . . . . .

. . . . . . . . . (–4.59) . . . . . . . . .

Lag1 . . . . . . . . . 0.86 . . . . . . . . .

. . . . . . . . . (3.67) . . . . . . . . .

Lag2 . . . . . . . . . 0.19 . . . . . . . . .

. . . . . . . . . (0.84) . . . . . . . . .

Upturn dummy x negative

fiscal impulse x dCAPB

. . . . . . . . . 0.57 . . . . . . . . .

. . . . . . . . . (4.27) . . . . . . . . .

Lag1 . . . . . . . . . –0.91 . . . . . . . . .

. . . . . . . . . (–5.62) . . . . . . . . .

Lag2 . . . . . . . . . –0.37 . . . . . . . . .

. . . . . . . . . (–2.04) . . . . . . . . .

Real money growth 0.05 0.02 0.07 0.05 0.06 0.02 0.08

(1.92) (1.06) (2.41) (1.92) (2.19) (1.11) (2.65)

Lag1 0.01 0.01 0.03 –0.01 0.01 0.01 0.03

(0.83) (0.50) (1.03) (–0.43) (0.85) (0.50) (0.99)

Lag2 –0.02 0.00 –0.02 –0.02 –0.02 0.00 –0.02

(–1.37) (0.15) (–0.97) (–1.03) (–1.34) (0.27) (–0.94)

Government size –0.04 –0.01 –0.04 –0.02 –0.04 –0.01 –0.04

(–2.44) (–1.00) (–1.62) (–2.26) (–2.17) (–0.97) (–1.36)

Trade-weighted growth of

trading partners

0.34 0.08 0.40 0.16 0.35 0.08 0.43

(1.93) (0.60) (1.77) (1.29) (1.93) (0.54) (1.69)

EMU dummy –0.79 –0.19 –0.71 –0.82 –0.19 . . .

(–2.28) (–0.80) (–2.61) (–2.50) (–0.83) . . .

Number of observations 796 487 309 650 796 487 309

Number of countries 40 21 19 40 40 21 19

p-value for Sargan test of

overidentifying restrictions

0.000 0.000 0.001 0.000 0 0.004 0.003

p-value for Hansen test of

overidentifying restrictions

1.000 1.000 1.000 1.000 1.000 1.000 1.000

p-value for the test of no

second order serial

correlation

0.790 0.254 0.758 0.019 0.739 0.428 0.641

Dependent variable is real GDP growth. All regressions also included a set of time dummies.

195

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