Has EMU shifted policy?
Date: 2003-08-09
Institutions: Directorate-General for Economic and Financial Affairs
Subjects: EU statistics, Economic and Monetary Union, economic policy, fiscal policy, monetary policy

ECONOMIC
PAPERS

EUROPEAN COMMISSION
DIRECTORATE-GENERAL FOR ECONOMIC AND FINANCIAL AFFAIRS

http://europa.eu.int/comm/economy_finance

Number 166

February 2002

Has EMU shifted policy?
by

F. Ballabriga and C. Martinez-Mongay

Has EMU shifted policy?

by

Fernando Ballabriga(*) and Carlos Martinez-Mongay(*)

(*) The authors are respectively Economic Advisor and Head of Unit at the Directorate-General for
Economic and Financial Affairs of the European Commission. Excellent research and editorial
assistance by, respectively, K. Havik and H. Caplen is very much appreciated. The views
expressed are those of the authors and are not attributable to the European Commission.

ECFIN/176/02-EN

This paper only exists in English.

©European Communities, 2002

TABLE OF CONTENTS

1.

2.

3.

INTRODUCTION ...........................................................................................................................5

THE CASE FOR SIMPLE RULES.................................................................................................6

SPECIFICATION OF THE FISCAL AND MONETARY POLICY RULES ................................8
3.1.
Fiscal policy rules.................................................................................................................9
3.2. Monetary policy rules .........................................................................................................10

4.

ESTIMATION...............................................................................................................................11

5. ANALYSIS AND INTERPRETATION OF THE RESULTS......................................................14
5.1. The empirical relevance of the rules ..................................................................................14
Fiscal rules...........................................................................................................14
5.1.1.
5.1.2. Monetary Rule .....................................................................................................19
5.2. The policy regime during the 20 pre-EMU years ...............................................................26
Policy shocks during the 20 pre-EMU years ......................................................................31
5.3.

6.

7.

TO WHAT EXTENT IS THE EMU MACRO POLICY FRAMEWORK “NEW”?....................34

CONCLUDING REMARKS.........................................................................................................36

STATISTICAL ANNEX........................................................................................................................39

1.

2.

3.

LIST OF COUNTRIES .................................................................................................................39

LIST OF VARIABLES AND INSTRUMENTS...........................................................................39
2.1. List of policy instruments ...................................................................................................39
2.2. List of policy targets ...........................................................................................................39
2.3. List of instrumental variables .............................................................................................40

ESTIMATION...............................................................................................................................40
3.1.
Fiscal rule ...........................................................................................................................41
3.2. Monetary rule .....................................................................................................................41

REFERENCES.......................................................................................................................................43

TABLE OF TABLES

Table 1: Fiscal policy rules, 1979-1998................................................................................................ 14

Table 2: Discretionary fiscal policy, 1979-1998................................................................................... 19

Table 3: Monetary policy rules, 1979Q1-1998Q4 ................................................................................ 20

Table 4: Test of the informational content of money............................................................................ 26

Table 5: Correlations across policy shocks........................................................................................... 32

Table 6: Standard deviations of policy shocks...................................................................................... 33

TABLE OF FIGURES

Figure 1: Actual and Target Government Primary Surplus (% of GDP) .............................................. 16

Figure 2: Actual and Target Short Term Interest Rates ........................................................................ 22

Figure 3: Actual and Target Short Term Interest Rates (model excluding German interest rates) ...... 24

Figure 4: Difference Between Actual and Counterfactual Short Term Interest Rates ......................... 30

Figure A1: Quarterly inflation rate ....................................................................................................... 45

Figure A2: Quarterly output gap ........................................................................................................... 47

Figure A3: Annual output gap............................................................................................................... 49

Figure A4: Public Debt as a Percentage of GDP. ................................................................................. 51

3

NON-TECHNICAL SUMMARY

This paper assesses the extent to which the macroeconomic policy architecture of EMU represents a
break with the past. This is carried out by estimating forward-looking fiscal and monetary policy rules
for the Member States and by analysing them within the conceptual framework of the Fiscal Theory
of the Price level. The pre-EMU economic policy system turns out to be a monetary dominance
regime, in which monetary authorities in the Member States apply an ‘active’ (counter-inflationary)
monetary policy, whereas fiscal policy is ‘passive’. In particular, fiscal authorities react to debt
accumulation by increasing primary surpluses, thereby guaranteeing fiscal solvency. Interestingly, the
macroeconomic institutional architecture of EMU can also be categorised as a monetary dominance
regime. While the ECB pursues an ‘active’ monetary policy, the SGP objective is that fiscal discipline
prevails, so that governments guarantee their own solvency. In sum, the key characteristics of the
systematic component of macroeconomic policy in EMU may not be different from what they used to
be. Yet, some differences are worth noting.

First, although fiscal solvency seems to be guaranteed in both regimes, there is a clear contrast as
regards the way it is ensured. While the SGP puts a brake on debt accumulation by explicitly limiting
the variability of the deficit, the rules applied by fiscal authorities in the past basically relied on the
systematic responses to debt accumulation. Second, pre-EMU fiscal behaviour did not ensure close-to-
balance positions in the medium term, while deficits above 3% were not unusual. Third, a stronger
response to debt
in EMU might accelerate the consolidation efforts to reach close-to-balance
positions. Finally, and perhaps more important, a reduction in the variability of fiscal-policy shocks
may be needed in order to respect the 3% constraint. Overall, the volatility of such shocks should
remain low if just automatic stabilisation and no discretionary actions prevails in EMU.

Several by-products from our analysis should be mentioned:

• The fiscal rule characterises governments as generally reactive to debt accumulation and applying

a counter-cyclical fiscal policy.

• Monetary authorities across the EU have systematically adjusted nominal

interest rates to

counteract inflation pressures. This reproduces previous results published in the literature.

• However, in this paper, the counter-cyclical activity of monetary policy looks stronger than

previously reported.

• There is unambiguous and robust empirical evidence of the leading role of Germany in the setting

of European monetary policy during the 80s and 90s.

• In connection with the two pillar strategy of the ECB, we present evidence suggesting that money
may legitimately belong to the second pillar, but its relative informational content may not justify
the existence of a first pillar.

• Finally, our results regarding non-systematic policy behaviour suggest that co-ordination has been
absent at the level of discretionary shocks. While the variability of monetary and fiscal shocks
does not show significant correlation both within and across countries, non-systematic fiscal policy
appears as a more active policy tool than non-systematic monetary policy.

4

1.

INTRODUCTION

The official adoption of the euro by 11 EU Member States1 in January 1999 marked a key step in the

process of economic and political integration in Europe. Currencies contain a mix of economics and

politics, as they convey elements of national identity. In that sense, Economic and Monetary Union

(EMU) is not only the latest step in the process toward an “ever closer union” that took off in Europe

after World War II, but probably the most daring so far. The importance of the event may have

created a tendency to label as “new” basically any element connected with EMU. This is certainly the

case with its key aspect, namely its macroeconomic policy architecture. This architecture has a single

independent central bank on the monetary policy side with a strict mandate to preserve price stability,

and the Stability and Growth Pact setting behavioural lines for national authorities on the fiscal policy

side. The resulting combination is commonly referred to as a fully new macroeconomic policy

framework. This paper attempts to assess the extent to which such macroeconomic policy architecture

of EMU represents a genuine policy-regime change.

In the spirit of the holistic approach to macroeconomic policy analysis emphasised in the recently

proposed Fiscal Theory of the Price Level (FTPL), we look jointly at fiscal and monetary policy

behaviour. This is done in contrast with the bulk of the policy rule literature, which has focused on

monetary policy behaviour. We use two decades of pre-EMU macroeconomic data to estimate

forward-looking fiscal and monetary policy rules for the individual EU countries. The resulting rules

provide a characterisation of the systematic and non-systematic components of macroeconomic policy

behaviour before the formal start of EMU. The identified behaviour for the pre-EMU period is then

compared with the one implied by the EMU framework. Within the conceptual framework of the

FTPL, we identify and characterise both pre-EMU and EMU policy behaviour as representing a

“monetary dominance” regime. This suggests that the shift brought by EMU might not represent a

dramatic change in the conduct of economic policy across Europe. Yet, we also present empirical

evidence that the EMU framework may affect the exogenous component of policy.

Beyond this central conclusion, other interesting contributions of this paper include the identification

and estimation of the pre-EMU fiscal behaviour in each Member State, while previous monetary rule

results have been extended to a larger set of countries and to a longer sample period. Moreover, the

paper presents an assessment of the informational content of money to forecast inflation. Finally, it

also analyses of the correlation among fiscal and monetary policy shocks.

1 Belgium, Germany, Spain, France, Ireland, Italy, Luxembourg,

the Netherlands, Austria, Portugal and

Finland. Greece adopted the euro in January 2002.

5

The paper

is organised as follows. Section 2 reviews the case for simple policy rules in

macroeconomic analysis looking at key developments in the area during the last few decades. Section

3 describes the specification of the simple partial-adjustment forward-looking policy models used in

the study. Section 4 presents the ready-for-estimation version of the policy rules and describes other

estimation details. Section 5 contains the analysis and interpretation of the results. It first discusses

the empirical relevance of the estimated rules. Then it identifies the pre-EMU policy regime. Next it

briefly characterises the behaviour of the exogenous component of policy during the pre-EMU period.

Section 6 compares the pre-EMU policy behaviour with the one prescribed by EMU. Finally, section

7 contains some concluding remarks.

2.

THE CASE FOR SIMPLE RULES

The view that policy making should be based on simple behavioural rules is not new, although its

normative and empirical relevance have not been established until recently. The view dates back to at

least the 1950s, when several proposals centred around money growth were suggested. The most well

known of them is the fixed money growth rate rule put forward in Friedman (1959). Friedman´s rule

was based on the idea that long and variable lags of the effects of monetary policy could destabilise

rather than stabilise the economy. Accordingly, his proposal conveyed two separate arguments: First,

policy should follow a rule, and, second, it should favour a simple non-activist rule.

That rules are better than discretion is by now a widely accepted theoretical principle. The normative

relevance of following rules rather than discretion was initially established by the pioneering work of

Kydland and Prescott (1977). These authors formalised the notion of time inconsistency of optimal

policy under discretion, showing how incentives to push output above potential will tend to create an

inflationary bias under discretion. More recently, Clarida, Galí, and Gertler2 (1999) have shown that

the time inconsistency problem is relevant in a more realistic framework, where the policy authority

does not necessarily have a preference to push output above potential. They claim that all that is

needed to obtain gains from commitment to a policy rule is that current price setting be dependent on

future expectations about economic conditions. In such a framework, current inflation is a forward-

looking variable that depends on expected inflation. Therefore, a credible policy commitment to

respond to future inflationary shocks will reduce expected inflation and will improve the short-run

output/inflation trade-off, lowering inflation for any given output gap.

The time inconsistency argument provides normative support for rules but not for simple non-activist

rules,

the relevance, empirical or normative, has never been established. In fact,

the recent

2 CGG later on.

6

proliferation of the analysis of simple policy rules has its origin in Taylor (1993) proposal to use a

simple activist rule as a guideline for monetary policy. Taylor's specific proposal was to use the

following interest rate rule:

R

*
t

=

a

+

b

p
(

t

1

p

*

)

+

g

x

t

;

b

> g
,1

>

0

(1)

where “*” represents target values, R is the short run nominal interest rate,p

is the quarter on

quarter yearly inflation rate, x is the output gap expressed as a percent of target potential output,

a

and

+= r

*p

interest rate.

is the long run target nominal interest rate, with r representing the steady state real

Rule (1) takes the short-run nominal interest rate as the monetary policy instrument and calls for an

active policy that adjusts the nominal rate upwards (downwards) when inflation and output are above

(below) target values. At the time, Taylor defended the normative relevance of this type of rule on the

basis of simulation results obtained with (mainly) rational expectations econometric models. These

models suggested that rules with direct focus on inflation and output targets tended to deliver more

price and output stability than rules with focus on money supply or exchange rate targets. Besides, he

claimed that the rule was empirically relevant for the US by informally setting the values:

b

=

,5.1

g

=

,5.0

r

=

,2

p

* =

2

(2)

and showing that during the period 1987-92 the implied targeted interest rate was remarkably closed

to the actual rate.

New research has recently reinforced the relevance of simple feedback rules of type (1). On the

normative side, Taylor (1999) has collected simulation evidence from a wide range of dynamic

stochastic general equilibrium models (small and large, closed and open, with and without rational

expectations, with different degrees of microeconomic foundations, estimated and calibrated) with

some form of temporary nominal rigidities. One of his conclusions is that, in terms of the variance of

output and inflation around targets, simple rules like (1) tend to perform better across models than

specific optimal rules, which tend to be very model dependent.

Also in the normative side, CGG (1999) have analysed monetary policy in a stylised broad

macroeconomic framework with temporary nominal price rigidities, where the monetary authority sets

the interest rate as to minimise a quadratic loss function on inflation and output deviations from

targets. In the list of general optimality principles obtained by these authors are the two characteristics

embedded in rule (1), namely, that the interest rate has to adjust more than one-for-one with inflation

7

-
-
1>b

(

) and that it has to respond to output gap (as opposed to output level), so supply shocks (e.g.

productivity shocks) that affect both potential and actual output must be accommodated (i.e. call for

no action) whereas demand shocks that affect the output gap call for counter-cyclical actions (

0>g

).

CGG (2000) have in addition made the point that the value of the parameter measuring the degree of

response to inflation deviations from target in policy rules of type (1) may be crucial for output and

inflation stability. Specifically, they show that in their sticky-price theoretical framework, equilibrium

is unique when the monetary rule embeds the optimality principle

1>b

, but it is indeterminate, and

so potentially more unstable, with

b

1£

. They estimate the rule for the US and find that b

is lower

than 1 for a sample period before 1979. However, the estimation of the coefficient of inflation is

greater than one for the post-1979 sample. As this latter period is characterised by higher

macroeconomic stability, CGG (2000) conclude that the clear anti-inflationary policy of that period

has been a significant stability factor3.

In another paper (CGG, 1998) Clarida, Galí and Gertler have reassessed the empirical relevance of

simple interest rules by specifying and formally estimating a forward-looking generalisation of rule

(1)4 for a set of major economies5. Their results confirm that Taylor´s informal setting in (2) is

reasonable, and show that the estimated target rates perform well in tracking the actual rates set by the

respective central banks during the 1980s and early 90s.

Overall, the literature reviewed above, and the references therein, have contributed to create what by

now seems a wide consensus around the virtues of thinking about policy making in terms of simple

rules of type (1). It should be noted, however, that the discussion in the literature has almost

exclusively focused on monetary policy, with relatively much less attention to fiscal policy, specially

in the area of establishing empirical relevance6 of simple rules. To our knowledge, the only exceptions

are Bohn (1998) and some informal work in Taylor (2001), both for the US.

3.

SPECIFICATION OF THE FISCAL AND MONETARY POLICY RULES

A characteristic of rule (1) is the assumption that the monetary authority looks at lagged inflation in

setting its policy instrument. The rationale for the above mentioned forward-looking generalisation of

the Taylor rule recently proposed by CGG (1998 and 2000) is that although policy makers have in

3 Section 5 will elaborate more on this issue.
4 This generalisation is described in the next section.
5 US, Japan, Germany, France, UK, and Italy.
6

In section 5 we will refer to the recent fiscal theory of the price level, which emphasises both monetary and
fiscal rules from a theoretical perspective.

8

effect simple rules in mind, they generally look forward, not backward, using sophisticated methods

to forecast their target objectives. As a consequence, target instruments are set according to a rule that

focuses on expectations about deviations from target objectives rather than on past economic

performance. Besides, inertia is omnipresent in policy making, implying that instruments will adjust

slowly to their target values. This justifies the use of a partial adjustment mechanism to relate actual

and target instruments.

CCG (1998 and 2000) use this partial-adjustment forward-looking model to characterise monetary

policy behaviour, but its principles are general enough to apply to fiscal policy behaviour as well.

Thus, in this section we use such a type of models as the common framework to specify both fiscal

and monetary policy rules.

Fiscal policy rules

Our fiscal rule specification takes the government primary surplus as the policy instrument and

assumes that the fiscal authority sets its target for that instrument as a function of two economic

indicators: the deviation of the inherited public debt from target and the expected output gap for the

current year. Formally, we have:

=

a

s

*
t

F

+

d

(

d

F

t

1

d

*

)

+

g

xE
(

t

F

/

)

Ft

(3)

where “*” represents target values, s and d are primary surplus and debt, respectively, both relative

to the output level, E is the expectation operator, x is the output gap as a percent of potential output,

and

Ft

is the information set at the beginning of period t, when the fiscal authority sets its target.

There are theoretical arguments that can be used to justify specification (3). For instance, Bohn

(1998) rationalises a similar equation by resorting to Barro (1979) tax smoothing model. According to

this latter model, debt and cyclical variability of output play a role in optimal tax setting. Although in

a different theoretical framework, a calibrated dynamic stochastic model, Leeper (1993) and Andrés,

Ballabriga and Vallés (2000, 2001) also use rules like (3) and show that they are helpful

in

eliminating equilibrium indeterminacy. However, these arguments notwithstanding, our favoured

justification for (3) is plausibility. It is plausible because it provides a formal stylised way of

explaining fiscal behaviour by focusing on two key dimensions of government concern, namely

government solvency and output stabilisation.

It is true, on the other hand, that, although plausible, the rule may be seen as a too stylised

representation. As mentioned above, policy processes tend to have a strong inertia. In the case of

fiscal policy, inertia is to a large extend explained by the political difficulty of changing past spending

9

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commitments and carrying out regular and recurrent drastic adjustments in tax codes. Besides, policy

consists not only of endogenous reactions to economic developments, as (3) suggests, but also of

unexpected actions. Neither of these features (inertia and shocks) is captured by (3). This is why it

may often turn out to be too simple to provide a good description of the actual variability of the policy

instrument.

Thus, in order to gain empirical relevance, we introduced inertia and shocks in our specification

through the following partial adjustment model:

=

1(

s

t

r

*)
s
t

F

+

r

s
tF

- 1

+

n

Ft

(4)

where

0

r

F

1

. According to (4), the current value of the fiscal policy instrument partially adjusts

from last period value towards the current government target by a fraction of

1(

r

)

F

. Besides, the

value of the instrument is affected by the shock

n

F

, which reflects the effect of non-systematic

actions. More specifically, F

n may incorporate variability stemming from the imperfect control of the

fiscal process (e.g. “political” shocks), as well as true fiscal policy actions or, in other words, genuine

non-systematic, discretionary policy shocks. Expressions (3) and (4) define our model of fiscal policy

behaviour.

Monetary policy rules

CGG (1998) have documented how the leadership exerted by the Bundesbank in the European

monetary policy process translates into a significant empirical relevance of the German interest rate

for the evolution of the interest rates in other European economies. The monetary rule specification

that we consider here takes this asymmetry directly into account. Thus, the rule takes the short run

nominal interest rate as the policy instrument and assumes that, in the case of Germany, the monetary

authority sets the target for that instrument as a function of expected deviations from inflation and

output targets. The rest of the EU countries looks in addition to the German rate when setting their

instrument target. Formally, for Germany:

=

a

R

*
t

+

b

E

p
(

M

M

+
kt

p

*

/

+

g

)

Mt

(
xE

t

/

M

)

Mt

and for the rest of the EU countries:

=

a

R

*
t

+

b

E

p
(

M

M

+
kt

p

*

/

+

g

)

Mt

(
xE

t

/

M

+

l

)

D

R
tM

Mt

(5)

(6)

10

-
£
£
-
W
W
-
W
W
-
where R is the short run nominal interest rate,

kt+p

is the inflation rate k periods ahead -which is the

relevant horizon for the monetary authority-,

DR is the German short run nominal rate, and as above

“*” represents target values, x is the output gap, and expectations are conditional on the information

set available at the beginning of period t, when target rates are set.

The empirical and theoretical rationale for this kind of interest rate rule has already been documented

in section 2. As in the case of fiscal policy, these monetary target rules are generally too stylised, as

they lack inertia and the effect of exogenous disturbances. In the case of monetary policy, inertia is

often justified by the observed tendency of central banks to smooth interest rate changes7. On the

other hand, once inertia is taken into account, differences between actual interest rates and those

implied by (5) or (6) may be the consequence of failures to follow the rule (e.g. political pressure on

the central bank) or the result of true discretionary monetary policy actions. As with fiscal policy, we

introduce these two features, inertia and policy shocks, into the analysis at once through the following

partial adjustment equation:

R

t

=

1(

r

)

R

*
t

M

+

r

R
tM

- 1

+

n

Mt

(7)

where

0

r

M

1

measures the degree of smoothing and M

n

is the exogenous component of policy,

thereby reflecting failures to follow the rule and/or genuine discretionary actions. Expressions (5), (6),

and (7) define our model of monetary policy behaviour.

4.

ESTIMATION

In order to obtain ready-for-estimation versions of the fiscal and monetary policy rules we need to

apply some simple algebraic transformations to the models described in section 3.

Where fiscal policy is concerned, we add and subtract the output gap term

tF xg

to the right hand side

of equation (3), then let the unobserved target level debt

*d

be part of the constant term, and

rearrange to get:

s

*
t

=

~
a

F

+

d

d
tF

1

+

g

(

(
xE

t

/

F

)

Ft

+

g

x

t

)

x
tF

(8)

where

~
a

F

=

a

F

d

*

dF

. Next we substitute (8) in the partial adjustment model (4) to obtain:

7 Explanations for this observed tendency include fears of financial disruption (Goodfriend, 1991) and

uncertainty about policy effects due to model uncertainty (CGG, 1999).

11

-
£
£
-
W
-
-
-=
1(

s

t

r

~)
a

F

F

-+
1(

r

d
)

F

d
tF

1

-+
1(

r

g
)

F

x
tF

+

r

s
tF

1

+

e

Ft

(9)

with

e

Ft

-=

1(

r

g
)

F

(

x

t

F

(
xE

t

/

+

n

))

Ft

Ft

Therefore, the error term in (9) is the sum of the exogenous component of fiscal policy

n

F

and a term

involving the error of forecasting the output gap. We assume that policy shocks are zero mean i.i.d.

stochastic process,

Similar transformations can be applied to the monetary policy model. Specifically, in (5) and (6) we

add and subtract

b

+p

ktM

g

and

tM x

to the right hand side, then we place the unobserved target for

inflation in the constant term, and rearrange. In the case of Germany we get:

*
R
t

=

~
a
M

+

b

(

E

p
(

M

/

+
kt

)

Mt

p

+

g

)

+
kt

(

(
xE

t

/

M

)

Mt

x

t

)

+

b

p
ktM

+

+

g

x
tM

(10)

and for the remaining EU countries:

*
R
t

=

~
a
M

+

b

p
((
E

M

/

+
kt

)

Mt

p

+

g

)

+
kt

((
xE
t

/

M

)

Mt

+

b

x
t

)

p
+
ktM

+

g

x
tM

+

l

D

R
tM

(11)

where

~
a
M

=

a

M

b

p

*

M

. Next we substitute (10) and (11) in equation (7) and rearrange to obtain

the following expressions for Germany and the rest of the EU, respectively:

R
t

=

1(

r

~)
a

M

M

-+
1(

r

b

)

p

F

M

+
kt

-+
1(

r

g
)

x
tM

M

+

r

R
tM

1

+

e

Mt

(12)

and

R
t

-=
1(

r

~)
a

M

M

-+
1(

r

b

)

p

F

M

+
kt

-+
1(

r

g
)

M

x
tM

-+
1(

r

l
)

D

R
tM

M

+

r

R
tM

1

+

e

Mt

(13)

with

e

Mt

-=

1(

[
b
)

r

M

p
(

M

+
kt

E

p
(

/

+
kt

+

g

))

Mt

(

x

t

M

(
xE

t

/

))

Mt

]

+

n

Mt

Consequently, as in the fiscal case, the error term is a combination of forecasting errors and an

exogenous policy shock M

n

, which we assume to zero mean i.i.d.

In sum, the models described in section 3 boil down to equation (9) for fiscal policy and to equations

(12)-(13) for monetary policy. The corresponding equations express policy instruments (primary

balances, nominal interest rates) in terms of observed variables (inflation rates, output gaps, debt

stocks, lagged variables) plus a random error. The equations are non-linear because policy inertia

reduces the effect of objective variables on policy instruments. More importantly, their error terms are

correlated with the explanatory variables, since the former contain the forecasting errors of the latter.

12

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-
-
-
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-
W
-
W
-
W
-
-
-
-
W
-
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-
-
We therefore need to apply non-linear instrumental variable estimation methods, while standard errors

would ideally be calculated using heteroskedastic and autocorrelation-consistent methods. As in CGG

(1998), we apply non-linear GMM8. Reasonable instruments for estimation in this context are

variables useful for forecasting the objective variables (inflation and output gap), which are not

observable at the beginning of period t. Such instrumental variables would belong to the information

set of the policy authority when it sets it target for the corresponding policy instrument. Additionally,
instrumental variables have to be uncorrelated withe , so that the moment conditions needed for

unbiased estimation are satisfied:

tZE
(

e

)

t

=

0

where

tZ

t

is the vector of instrumental variables.

The policy equations are estimated for the sample period 1979-19989. We use annual data for fiscal

policy and quarterly data for monetary policy. Such time frames reflect reasonably well those of

actual policy choices in each branch of macro policy making. We assume that the monetary authority

looks at one year ahead expectations for inflation when assessing deviations from target, so we set
4=k

. Following CGG (1998)10, the set of instruments for monetary policy includes four lags of all

the variables in equations (12)-(13), four lags of the effective real exchange rate and the commodity

prices, and, in some cases, four lags of money supply (M3). By comparing models including and

excluding money growth, we are in a position to assess the role of money as an instrumental variable.

Similarly, the set of instruments for fiscal policy includes one lag of all the variables in equation (9)

plus one lag of the short run nominal interest rate, the effective real exchange rate, and the commodity

price indicator11. In both cases, fiscal and monetary, the dimension of the vector of instruments

exceeds the dimension of the vector of parameters, thereby testing for over-identification provides a

way to assess the empirical relevance of the models.

8 See the Statistical appendix for further details.

9 See the Statistical appendix for details concerning sample period exceptions.

10 They use monthly data, however.

11 The effective real exchange rate, the commodity price indicator and money supply are included as annual
quarter-on-quarter growth rates in the monetary rule. The effective real exchange rate and the commodity
price indicators are included in annual growth rates in the fiscal rule. See the statistical appendix for the
details.

13

W
˛
5. ANALYSIS AND INTERPRETATION OF THE RESULTS

5.1.

5.1.1.

The empirical relevance of the rules

Fiscal rules

A look at Table 1 reveals the satisfactory statistical properties of the fiscal model. On one side, in

terms of the overall specification, the value of the J-statistic implies in all countries that the model is

not rejected by the data at conventional significance levels. On other side, in terms of the statistical

significance of the coefficients, note first that the partial adjustment coefficient is significant for most

countries (the exceptions are Austria, France, the Netherlands, and Portugal) and is in the range [0.47,

0.86], implying a considerable degree of policy inertia. The inertia seems specially high in Ireland

(0.86) and the UK (0.84).

Table 1: Fiscal policy rules, 1979-1998 (a)

Belgium

Denmark

Germany

Spain

France

Ireland(h)

Italy

The Netherlands

Austria

Portugal

Finland

Sweden

United Kingdom

F (b)

0.47
(0.13)*
0.49
(0.10)*
0.54
(0.16)*
0.50
(0.14)*

0.87
(0.08)*
0.58
(0.10)*

0.47
(0.06)*
0.62
(0.06)*
0.84
(0.05)*

~
a

cF
)(

-12.8
(1.66)*
-0.75
(0.99)
-2.01
(1.34)
-4.90
(0.95)*
-0.17
(0.32)
-31.0
(17.0)
-14.5
(1.85)*
-3.69
(0.58)*
-1.29
(0.67)*
-20.0
(2.40)*
2.19
(0.42)*
-0.86
(4.02)*
-49.6
(18.8)*

F (d)

F (e)

(f)

0.14
(0.02)*
0.10
(0.02)*
0.08
(0.04)*
0.09
(0.02)*
0.02
(0.01)*
0.38
(0.20)
0.16
(0.02)*
0.08
(0.01)*
0.04
(0.01)*
0.35
(0.04)*
0.04
(0.02)*
0.08
(0.07)
1.04
(0.39)*

0.34
(0.12)*
1.14
(0.15)*
-0.09
(0.12)
0.33
(0.10)*
0.26
(0.04)*
0.20
(0.55)
0.06
(0.13)
0.24
(0.09)*
0.24
(0.04)*
0.05
(0.02)*
0.92
(0.08)*
1.46
(0.21)*
1.05
(0.63)

1.04

1.32

0.90

0.91

0.52

1.17

1.13

1.00

0.78

1.40

1.04

1.67

1.04

J (g)

3.68
[0.24]
6.03
[0.11]
6.32
[0.10]
3.69
[0.30]
4.53
[0.34]
2.70
[0.44]
1.08
[0.78]
1.43
[0.84]
2.44
[0.66]
3.81
[0.43]
1.99
[0.58]
6.05
[0.11]
6.49
[0.09]

Standard errors in parentheses; ‘*’ significant at 5%.
(a) Except for Portugal, where the sample period is 1982-1998.
(b) Coefficient of (fiscal) policy inertia; see equation (4).
(c) Intercept of the fiscal rule; see equations (3) and (8).
(d) Fiscal response to the stock of debt at the beginning of the period; see equation (3).
(e) Fiscal response to the contemporaneous output gap; see equation (3).
(f) Standard error of the regression.
(g) Test for over-identifying restrictions (Chi-square with 3 degrees of freedom); p-values in brackets.
(h) The p-values associated to a F and d F are 0.07.

14

(cid:1)
(cid:1)
(cid:1)
(cid:1)
(cid:2)
The rest of the coefficients are also statistically significant in most cases. Specifically, all countries

except Sweden respond to the accumulation of debt by increasing its primary surplus. Although the

samples are not directly comparable, the estimated response of the primary surplus to the stock of

debt is in most cases within the 95% confidence values based on estimates in tables I and III of Bohn

(1998). Leaving aside Sweden, the most outstanding exceptions are the UK and Ireland, where the

estimated coefficients are very large, although in this latter country the p-value associated to the

coefficient is 0.07. The estimated response to the output gap is also mostly significant (Germany,

Ireland, Italy, and UK are the exceptions) and has the expected positive sign, implying that fiscal

policy behaviour is counter-cyclical. Finally, it is worth mentioning the generally negative (except

Finland) and significant (except
~
a

according to our specification

F

in Germany, France, and Sweden) constant

term. Recall

that

=

a

F

d

*

dF

, where

a

F

represents the long term primary surplus

target or, in other words, the desired surplus when both debt and output gap are at their target values

(see expression (3)). Thus, if we reasonably assume that

actual debt ratios, we would expect a negative

a

0»

*d is correlated with
a~ higher in absolute value for high-debt countries.

and target debt

F

F

Such an absolute value should also be higher in countries with a larger response of the primary

surplus to debt (

d

F

). This turns out to be the case in Table 1. For low estimated values of

d

a~

F

,

F

is

overall higher for countries with higher average debt ratios during the sample period analysed, while

it is also very high in Ireland, Portugal, and the UK, where the responses to government debt are the

largest in the panel of countries.

Additional evidence regarding the relevance of the estimated rule to describe actual fiscal behaviour

can be obtained by making the standard comparison between the actual and model-implied target

values for the primary surplus, (see expression (3)), which provides a test of the empirical “tracking”

ability of the estimated target rule for the policy instrument. This is done in Figure 1. As can be seen,

except in the cases of Ireland and the UK, the target equation traces reasonably well the evolution of

the actual surplus, although some temporary deviations occur. In particular, the German deviation

from the target in 1990, the year after reunification, is clearly visible, as are its fiscal difficulties in the

mid 90s. Worth to mention is also the consolidation effort in most Member States during 1997 and

1998, the pre-selection period for participation in EMU, when the surplus was trending upward across

the EU. However, if we naturally measure the effort in terms of the difference between the actual

surplus and that required by the target rule, we can clearly see that fiscal consolidation was

particularly strong in a number of future EMU members, such as Belgium, Ireland, Italy, the

Netherlands or Austria. In contrast, during the same period, the implied target surplus was above

actual in those countries (Denmark, Sweden or the UK) that, for one reason or another, had already

decided not to adopt the single currency.

15

-
Figure 1: Actual and Target Government Primary Surplus (% of GDP)

____

Actual

- - - -

Target

Belgium

Denmark

18

15

12

9

6

3

0

-3

-6

-9

-12

-15

-18

18

15

12

9

6

3

0

-3

-6

-9

-12

-15

-18

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

Germany

Spain

18

15

12

9

6

3

0

-3

-6

-9

-12

-15

-18

18

15

12

9

6

3

0

-3

-6

-9

-12

-15

-18

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

France

Ireland

18

15

12

9

6

3

0

-3

-6

-9

-12

-15

-18

18

15

12

9

6

3

0

-3

-6

-9

-12

-15

-18

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

Italy

The Netherlands

18

15

12

9

6

3

0

-3

-6

-9

-12

-15

-18

18

15

12

9

6

3

0

-3

-6

-9

-12

-15

-18

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

16

Figure 1 (Continued)

18

15

12

9

6

3

0

-3

-6

-9

-12

-15

-18

Austria

Portugal

18

15

12

9

6

3

0

-3

-6

-9

-12

-15

-18

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

Finland

Sweden

18

15

12

9

6

3

0

-3

-6

-9

-12

-15

-18

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

18

15

12

9

6

3

0

-3

-6

-9

-12

-15

-18

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

United Kingdom

18

15

12

9

6

3

0

-3

-6

-9

-12

-15

-18

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

A last and specific mention is needed for Ireland and UK. In both cases the evolution of the estimated

target instrument turns out to be mostly driven by the accumulation of debt, that varies a lot through

the sample and to which they respond relatively strongly12, as highlighted above. This fact in

combination with their high policy inertia coefficient imply that the deviations between actual and

target instrument values tend to be large in both countries.

12 Specially UK with a point estimate of 1.04, but also IRL with 0.3 (the associated p-value is 7% in this case).

17

The cyclical response of fiscal policy deserves a more detailed discussion. As we have pointed out,

most countries in our panel appear to behave counter-cyclically. More specifically, we can split our

panel in three groups. First, the group of Nordic countries (Denmark, Finland, and Sweden) with a

relatively strong response to the output gap. Second, a group with a significant but relatively weaker

response (Austria, Belgium, Spain, France, the Netherlands, and Portugal). Finally, a third group with

non-significant response to the evolution of the output gap (Germany, Ireland, Italy, and UK).

Since it is a widely accepted proposition that fiscal policy should be counter-cyclical, an interesting

question is whether the non-significant response of the third group may be the consequence of a pro-

cyclical discretionary fiscal policy that offsets the counter-cyclical effects of automatic stabilisation.

To answer this question we estimated our model replacing the primary surplus by the cyclically

adjusted primary surplus as dependent variable13.

The results of the exercise are reported in Table 2, which suggests a number of comments. First, the

discretionary policy response to the output gap is statistically non-significant in most countries. The

only exceptions to this rule are Denmark, Germany, Austria and Sweden. Germany is the only

country, where discretionary fiscal policy seems to be significantly pro-cyclical during the period

analysed. Second, the comparison with Table 1 shows that the coefficient of debt is basically

unaffected by the change of dependent variable, which indicates that

the response to debt

accumulation is a purely discretionary response. Third, accordingly, the intercept of the equation in

Table 2 is pretty close to that of Table 1, while, leaving aside France and the Netherlands, much the

same can be said of the estimates of fiscal inertia. As a consequence, the difference between F

g

in

Table 1 and that in Table 2 gives a rough measure of the size of automatic stabilisers in each country.

Interestingly, in most countries with significant response to the output gap, that difference implies that

primary surpluses change on average between 0.25 and 0.5 percentage points of GDP per percentage

point change in the output gap. This is quite comparable to recent estimates of the cyclical sensitivity

of the primary surplus to the output gap (see, for instance, van den Noord, 2002). Yet, some countries

are situated outside this general norm. While Austria and Portugal exhibit a relatively low cyclical

sensitivity, the size of automatic stabilisers in Finland is the largest in our panel of countries.

13

It should be emphasised that we interpret this exercise as a way of learning about the behaviour of the
discretionary component of fiscal policy. We do not consider the estimated equation as a policy rule, since we
do not view the adjusted primary surplus as the policy instrument of fiscal authorities.

18

Table 2: Discretionary fiscal policy, 1979-1998 (a)

Belgium

Denmark

Germany

Spain

France

Ireland

Italy

The Netherlands

Austria

Portugal

Finland

Sweden

United Kingdom

r F (b)

0.63
(0.13)*
0.47
(0.16)*
0.61
(0.06)*
0.40
(0.20)*
0.23
(0.10)*
0.90
(0.08)*
0.63
(0.09)*
0.63
(0.13)*

0.52
(0.13)*
0.60
(0.06)*
0.81
(0.09)*

~
a

)(
cF
-16.6
(4.34)*
-0.25
(2.28)
-0.62
(1.12)
-4.14
(0.73)*
-0.84
(0.56)
-42.8
(27.3)
-15.2
(2.47)*
-3.54
(2.18)
-2.72
(0.092)*
-17.8
(1.32)*
1.85
(1.09)
-0.86
(4.02)
-26.5
(16.4)

d F (d)

0.17
(0.04)*
0.10
(0.04)*
0.06
(0.03)
0.08
(0.02)*
0.04
(0.01)*
0.53
(0.34)
0.17
(0.03)*
0.08
(0.04)*
0.06
(0.02)*
0.33
(0.02)*
0.04
(0.02)
0.08
(0.07)
0.57
(0.34)

g F (e)

-0.05
(0.29)
0.70
(0.21)*
-0.58
(0.17)*
0.08
(0.13)
-0.07
(0.07)
-0.29
(0.40)
-0.14
(0.15)
-0.32
(0.31)
0.22
(0.06)*
0.02
(0.02)
0.08
(0.10)
0.97
(0.19)*
0.58
(0.65)

=(f)

1.64

1.62

0.99

0.90

0.58

1.42

1.20

1.28

0.95

1.12

1.30

1.69

1.31

J (g)

3.48
[0.32]
2.15
[0.54]
5.56
[0.13]
2.87
[0.41]
4.12
[0.25]
2.92
[0.40]
1.92
[0.59]
1.54
[0.67]
2.05
[0.73]
6.23
[0.18]
3.95
[0.27]
7.45
[0.06]
6.67
[0.08]

Standard errors in parentheses; ‘*’ significant at 5%.
(a) Except for Portugal, where the sample period is 1982-1998.
(b) Coefficient of (fiscal) policy inertia; see equation (4).
(c) Intercept of the fiscal rule; see equations (3) and (8).
(d) Fiscal response to the stock of debt at the beginning of the period; see equation (3).
(e) Fiscal response to the contemporaneous output gap; see equation (3).
(f) Standard error of the regression.
(g) Test for over-identifying restrictions (Chi-square with 3 degrees of freedom); p-value in brackets.

5.1.2.

Monetary Rule

Turning now to the results obtained for the monetary rule (see Table 3), a first general point to

emphasise is that they reproduce for our extended sample period and panel of EU countries the overall

results reported in CGG (1998) for the four largest European economies (Germany, France, UK, and

Italy)14.

14 Roughly, their estimates are for the 1980s in the case of France, UK, and Italy, and extend up to 1993 for

Germany.

19

s
Table 3: Monetary policy rules, 1979Q1-1998Q4 (a)

Belgium (i)

Denmark (i)

Germany (i) , (k)

Spain (i)

France (i)

Ireland (i)

Italy (j)

Netherlands (j)

Austria (j)

Portugal (j)

Finland (j)

Sweden (i)

United Kingdom (j)

r M (b)

0.74
(0.04)*
0.75
(0.05)*
0.87
(0.02)*
0.82
(0.05)*

0.88
(0.03)*
0.65
(0.05)*
0.92
(0.03)*
0.55
(0.03)*
0.62
(0.08)*
0.77
(0.05)*
0.93
(0.02)*
0.53
(0.09)*
0.85
(0.03)*

~
a

)(
cM
0.65
(0.41)
-2.91
(1.26)*
2.53
(0.43)*
2.77
(1.56)
[0.07]
1.46
(1.37)
3.11
(0.78)*
-1.67
(3.30)
0.23
(0.30)
0.87
(0.34)*
-0.43
(1.35)
2.56
(2.98)
2.73
(0.89)*
1.29
(1.24)

b M (d)

0.47
(0.16)*
0.68
(0.20)*
1.29
(0.16)*
0.62
(0.20)*

0.52
(0.16)*
0.53
(0.09)*
0.60
(0.23)*
-0.07
(0.08)
0.21
(0.14)
0.22
(0.08)*
1.63
(0.58)*
0.08
(0.09)
0.52
(0.21)*

g F (e)

0.16
(0.11)
0.93
(0.27)*
1.00
(0.21)*
0.79
(0.40)*

1.54
(0.64)*
0.35
(0.11)*
0.85
(0.66)
0.48
(0.09)*
0.33
(0.10)*
0.03
(0.05)
-0.53
(0.71)
0.33
(0.10)*
1.20
(0.36)*

l M (f)

0.79
(0.11)*
1.54
(0.28)*

0.67
(0.28)*

0.65
(0.26)*
0.66
(0.14)*
1.37
(0.58)*
1.0
(0.05)*
0.76
(0.08)*
1.52
(0.27)*
-0.23
(0.73)
1.05
(0.15)*
0.86
(0.26)*

=(g)

0.65

1.75

0.46

1.91

0.89

2.20

0.94

0.64

0.54

1.77

1.11

1.73

1.20

J (h)

23.9
[0.46]
20.0
[0.70]
19.6
[0.55]
22.9
[0.53]

19.1
[0.75]
16.9
[0.85]
19.0
[0.52]
22.0
[0.34]
21.0
[0.40]
15.2
[0.76]
10.7
[0.95]
21.0
[0.58]
25.3
[0.19]

Standard errors in parenthesis; ‘*’ significant at 5%.
(a) The sample size is 80, except in Belgium (size 68; period 1982Q1-1998Q4), Ireland (76; 1980Q1-1998Q4) and Portugal
(68; 1982Q1-1998Q4).
(b) Coefficient of (monetary) policy inertia; see equation (7).
(c) Intercept of the monetary rule; see equations (5)-(6) and (10)-(11).
(d) Monetary response to expected inflation; see equations (5)-(6).
(e) Monetary response to the contemporaneous output gap; see equations (5) and (6).
(f) Reaction to the German interest rate; see equation (6).
(g) Standard error of the regression.
(h) Test for over-identifying restrictions (Chi-square with 24 degrees of freedom in countries type (j), 20 in countries type (k)
and 21 in Germany); p-value in brackets.
(i) Long enough series of money growth are available and they enter the set of instruments.
(j) Long enough series of money growth are not available and, consequently, they do not enter the set of instruments.
(k) The policy instrument equation only includes expected inflation and the output gap; see equation (5).

The rule seems to provide a satisfactory description of monetary policy behaviour, with its

specification being accepted for all the countries analysed according to the J-test at conventional

significance levels. As for the statistical significance of the coefficients, the degree of policy inertia is

high, ranging in the interval [0.53, 0.93]. The monetary authority responds significantly to expected

deviations from target for domestic inflation by increasing rates in most countries (except in Austria,

the Netherlands, and Sweden), with coefficient value of 1.29 for Germany and in the interval [0.22,

0.68] for the rest of the countries (except in Finland with 1.63).

20

s
Besides, the external constraint imposed by the evolution of the German rate is clearly reflected by its

pervasive significant positive effect on the rates of the rest of the EU countries, except Finland. This

gives formal empirical support to the conventional view regarding the leadership exerted by Germany

in the setting of European monetary policy during the 80s and 90s. Finally, in terms of the tracking

ability of the target interest rates, the estimated model performs reasonably well, as shown in Figure

2. The only exceptions are Finland and the first half of the sample in Italy. In the case of Italy, the

high inflation variability of the 80s combines with a relatively high degree of interest rate smoothing

to induce large deviations between the actual and estimated target rates. A similar argument applies in

Finland, where in addition the specially turbulent episodes of

the early 90s (Soviet block

disintegration and financial crisis) operate to generate large deviations also in the second part of the

sample. Leaving aside these cases, some particular temporary deviations are certainly visible, like, for

instance, that observed in the UK by the exceptionally large inflationary spike of 1980.

Other aspects of the monetary rule results provide contrasting evidence with earlier literature and

deserve especial attention.

First, on the basis of figure 2, it appears that the rule tends to provide a better description of policy

behaviour during the 1990s, a decade characterised by lower inflation variability. One plausible

interpretation of this fact is obtained by applying the argument used above for Finland and Italy,

namely, that policy inertia combined with the higher macroeconomic turbulence of the 1980s to

generate larger deviations between actual and target rates. In the 1990s, the so-called Maastrict effect,

which has been extensively documented in the literature in the case of fiscal behaviour15, reduced

policy-induced turbulence by constraining the behaviour of central bankers. The Maastricht criteria,

specially those referring to inflation and interest rates, by establishing clear targets to the central

banks, introduced an additional factor of monetary discipline.

15 See, for instance, von Hagen, Hughes Hallet, and Strauch (2002).

21

Figure 2: Actual and Target Short Term Interest Rates

____

Actual

- - - -

Target

Belgium

Denmark

36

32

28

24

20

16

12

8

4

0

36

32

28

24

20

16

12

8

4

0

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

Germany

Spain

36

32

28

24

20

16

12

8

4

0

36

32

28

24

20

16

12

8

4

0

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

France

Ireland

36

32

28

24

20

16

12

8

4

0

36

32

28

24

20

16

12

8

4

0

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

Italy

The Netherlands

36

32

28

24

20

16

12

8

4

0

36

32

28

24

20

16

12

8

4

0

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

22

Figure 2 (Continued)

Austria

Portugal

36

32

28

24

20

16

12

8

4

0

36

32

28

24

20

16

12

8

4

0

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

Finland

Sweden

36

32

28

24

20

16

12

8

4

0

36

32

28

24

20

16

12

8

4

0

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

United Kingdom

36

32

28

24

20

16

12

8

4

0

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

Second, the addition of the German interest rate to the equations of the rest of the EU countries is of

key importance to obtain rules that provide a good description of monetary policy behaviour.

Dropping the variable from the rule does not have much impact on the fit of the model, but reduces

dramatically the tracking ability of the estimated target rates. As an illustration of this effect, figure 3

contains the actual and estimated target rates using the same model as in table 3, but without including

the German interest rate. Although the relevance of the German rate in the monetary rules across the

EU is evident from the figure, unsurprisingly, cases like Belgium and The Netherlands provide the

most clear examples of the German leadership in the setting of monetary policy in Europe.

23

Figure 3: Actual and Target Short Term Interest Rates (model excluding German interest

rates)

____

Actual

- - - -

Target

Belgium

Denmark

36

30

24

18

12

6

0

-6

-12

-18

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

36

30

24

18

12

6

0

-6

-12

-18

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

Spain

France

36

30

24

18

12

6

0

-6

-12

-18

79-Q1

80-Q1

36

30

24

18

12

6

0

-6

-12

-18

79-Q1

80-Q1

36

30

24

18

12

6

0

-6

-12

-18

36

30

24

18

12

6

0

-6

-12

-18

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

Italy

36

30

24

18

12

6

0

-6

-12

-18

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

Ireland

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

The Netherlands

Austria

36

30

24

18

12

6

0

-6

-12

-18

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

24

Figure 3 (Continued)

Portugal

Finland

36

30

24

18

12

6

0

-6

-12

-18

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

36

30

24

18

12

6

0

-6

-12

-18

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

Sweden

United Kingdom

36

30

24

18

12

6

0

-6

-12

-18

36

30

24

18

12

6

0

-6

-12

-18

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

Third, the coefficient of the output gap is positive and significant in most countries (except in

Belgium, Finland, Italy, and Portugal), and its estimated value ranges between [0.33,1.63]. This result

implies that monetary policy is generally counter-cyclical and, taking standard errors into account, it

suggests that the response of the monetary authority to expected output fluctuations seems to be

stronger on average than reported in CGG (1998)16.

Finally, a word on the role of money. The two-pillar strategy of the ECB assigns to the monetary

aggregate M3 the role of a prominent indicator for the evolution of prices (first pillar) and pools a set

of additional demand and supply indicators as a second pillar. This special role for money has been a

source of controversy because there seems to be no solid rationale for it on either theoretical or

empirical grounds17. In fact, even the inclusion of money in the pool of the second pillar has been

questioned.

A piece of empirical evidence on this issue can be naturally obtained in our analysis by modifying the

set of instrumental variables used in the estimation of the monetary rules. More specifically, in the

forward-looking monetary rule that we consider, the potential instrumental variables play a role in the

setting of the monetary policy instrument only to the extent that their informational content helps

policy makers to forecast policy objectives, in particular inflation. Thus, as a way to assess the

informational content of money, we can estimate our model both with and without money in the set of

16 CGG (1998) find a positive significant response to the output gap only for Germany and UK, with coefficient

value around 0.25 and standard error around 0.03.

17 See for example Galí (2001).

25

instruments, and then check whether the specification that includes money is rejected by the data. We

have performed this exercise for the countries where M3 data was available for the full sample

period18. A formal test based on the difference between the J-statistics of the models including and

excluding money is presented in Table 4. The result is that the inclusion of money is not rejected and,

therefore, it was legitimately added to the set of instruments when available. However, it should be

pointed out that the performance of the estimated rule as a descriptive tool of policy behaviour was

basically unaffected by the inclusion of money. Besides, the statistical effects of including/excluding

other instrumental variables (e.g. commodity prices) were similar, suggesting that their relative

informational content may also be similar. Thus, a fair conclusion out of this evidence could be that

money may legitimately belong to the second pillar, but its relative informational content does not

seem to justify a first pillar.

Table 4: Test of the informational content of money

Belgium

Denmark

Germany

Spain

France

Ireland

Sweden

(a)

23.9

20.0

19.6

23.0

19.1

16.9

21.0

(b)

17.5

15.5

18.6

20.5

18.2

13.9

18.3

(c) = (a) – (c)

6.4

4.5

1.0

2.5

0.9

3.0

2.7

(a) Model including money in the set of instruments. See table 3. The degrees of freedom of the Chi-square are

21 in Germany and 24 in the rest of the countries.

(b) Model in table 3 excluding money from the set of instruments. The degrees of freedom are 17 in Germany

and 20 in the rest.

(c) Difference between (a) and (b) distributed as a Chi-square with 4 degrees of freedom, with a critical value of

9.49 at 5%.

5.2.

The policy regime during the 20 pre-EMU years

A policy regime is defined by a specific combination of fiscal and monetary policy behaviour. The

need to look simultaneously at both branches of macro policy in order to correctly characterise a

policy regime is often recognised in public debates, as for instance in the debates about EMU. This

stands in sharp contrast with traditional economic analysis, which, with few exceptions19, has studied

them separately. Since monetary and fiscal policy are in fact closely connected, any positive or

18 This was not the case for Austria, Italy, the Netherlands, Finland, Portugal, and Sweden. See footnotes in

table 3 and the statistical appendix.

19 The classical reference is Sargent and Wallace (1981)

26

normative conclusion about one branch of policy depends on assumptions about the behaviour of the

other branch. When both are analysed separately those assumptions are not explicitly spelled out,

thereby giving a misleading sense of the generality of the conclusions and making it difficult to

identify the specific policy regime under scrutiny.

Recently, a holistic approach to macroeconomic policy analysis has been proposed in the literature

that represents a challenge to traditional economic analysis and views about the role of monetary and

fiscal policies. It is known as the Fiscal Theory of the Price Level (FTPL) and was originally

proposed by Leeper (1991), Sims (1994), and Woodford (1994)20. FTPL models look simultaneously

at fiscal and monetary behaviour combining a traditional monetary sector with the explicit

formulation of the long run solvency condition for the fiscal sector, which requires that the current

stock of debt equals the discounted flow of future primary surpluses. A key question in these models

is how fiscal solvency is achieved. The fiscal authority itself may guarantee solvency by setting the

primary surplus sequence in accordance with the solvency condition. In such a case, fiscal policy is

said to be “passive” or “Ricardian”. Alternatively, fiscal behaviour may lack discipline and set a

sequence of primary surpluses which is incompatible with solvency. In this case, fiscal policy is said

to be “active” or “non-Ricardian, and the endogenous adjustment of the price level is required to

guarantee fiscal solvency. A similar terminology is used for monetary policy. It is called “active”

when the monetary authority effectively counteracts inflation by implementing a policy that induces

an increase in the real interest rate when inflationary pressures increase, and vice versa. Otherwise,

monetary policy is termed “passive”.

The discussion under the FTPL framework has been helpful to identify and analyse different policy

regimes. A specific policy regime is explicitly defined as a combination of fiscal and monetary

behaviour that delivers a unique stable equilibrium. The two most widely discussed regimes are the so

called “monetary dominance” (MD) and “fiscal dominance” (FD) regimes. The MD regime is

identified by a combination of an active monetary policy and a passive fiscal policy, whereas the FD

regime combines a passive monetary policy with an active fiscal policy. Interestingly, this analysis of

policy regimes has often been done with models where policy is represented using simple feedback

rules of the type we have estimated, in which different parameter value combinations define different

regimes. As shown below, such a conceptual framework provides a way to characterise empirically

the policy regime that has prevailed in our panel of EU countries during the sample period analysed in

this paper.

20 Woodford (2000) provides a recent survey of this literature.

27

As the FTPL literature has pointed out21, the empirical discrimination among policy regimes, and in

particular between MD and FD regimes, is not straightforward. The reason is that simply designing a

test for fiscal solvency, as it might first come to mind, will not lead to conclusive results. As we have

mentioned, the violation of the solvency condition is not what characterises an FD regime. In

equilibrium, the fiscal solvency condition holds under both MD and FD. The difference between both

regimes lies in how solvency is achieved: Through endogenous price adjustment under FD and

through endogenous primary surplus adjustment under MD.

However, as Woodford (1999, 2000) has argued, empirical evidence on monetary and fiscal indicators

may be reasonably interpreted as being generated by a specific policy regime if one looks at the joint

structural behaviour of fiscal and monetary policy, as the FTPL framework suitably allows. As we

have just mentioned, policy analysis in FTPL models has used the same type of structural policy rules

that we have specified22 to investigate the sets of parameter combinations that deliver a unique stable

equilibrium23 and, therefore, lead to clear-cut predictions regarding policy effects. Each of such sets

of parameter combinations identifies a policy regime. More specifically, using a broad underlying

macroeconomic framework, this line of research has spotted out the response of monetary policy to

inflation deviations from target ( M

b

) and the response of the fiscal authority to the stock of debt

d

(

F

) as the key parameters to obtain unique stable equilibria24. In particular, an active monetary

policy (

b

M

1>

) in combination with a passive fiscal policy (

1

d

F

<

1

) delivers uniqueness,

defining an MD regime, whereas a passive monetary policy (

b

M

1<

) combined with an active fiscal

policy (

1

d

F

>

1

) defines an FD regime25.

The immediate interesting question at this point is whether we can identify a policy regime for the

countries in our panel on the basis of the estimated policy rules. Focus first on the monetary rule:

Does it implies that monetary policy has been active? Certainly yes for the case of Germany, where

the inflation coefficient is clearly greater than one. The same can be said with respect to Finland.

However, the answer is less straightforward for the rest of the countries in the panel. The dominant

21 See for example Cochrane (1998).

22 See for example Leeper (1993) and Andrés et al. (2000, 2001).

23 As opposed to indeterminacy or non-existence.

24 The wide consensus about the key role for stability of these two parameters has recently received some
criticisms. Benhabib et al. (2001) point out that considering potential effects of monetary policy on the supply
side may affect the stability regions. From a different perspective, Leeper and Zha (2001a) argue that stability
may depend on a broader set of parameters when the highly stylised macroeconomic framework that typically
underlies the stability analysis is replaced by a less restricted one.

25 For simplicity, all these parameter ranges assume a time-preference factor equal to one.

28

-
-
role of Germany during our sample period has imposed a strong external constraint to the monetary

policy of these countries, implying that the empirical specification of their monetary rules does not

conform with the theoretical analysis of stability. Thus, the fact that their estimated coefficients for

domestic inflation are less than one is not sufficient to infer that monetary policy has been passive,

because the evolution of the German rate also exerted influence on the setting of nominal interest

rates across the European central banks.

To get around of this problem, we perform a counterfactual experiment inspired by CGG (1998).

Specifically, we ask whether during the two decades of our sample the rest of EU countries

implemented a monetary policy as active as a German type of rule would have implied. Thus, for each

country, we drop the German interest rate in the target rule (6) and set the inflation coefficient equal

to the value estimated for Germany (1.29). However, we keep their respective estimates of the

intercept and the response to output gap, as they depend on the specific structural features of the

country. On the basis of this hypothetical monetary rule we simulate the implied interest rate for the

series of inflation and output gap actually observed in the country. In doing so, we build a benchmark

active rule, which can be compared with the policy behaviour actually observed over the sample

period. Figure 4 plots the difference between the interest rates actually observed in each country and

those implied by the benchmark active rule. A positive difference between both rates indicates that the

actual monetary policy in the country has been tighter than it would have been in case of having

applied the benchmark rule, in which interest rates react to inflation as they do in Germany. As can be

seen, in all countries and on average over the sample, actual monetary policy, as represented by the

observed interest rates, has been similar or even tighter than that implied by the benchmark active

rule. It is worth noting that the stress of the European Monetary System (EMS) crisis in the early 90s

is clearly visible. We can therefore conclude that monetary policy has been active in all EU countries.

Given an active monetary policy, and assuming that one favours the interpretation of the evidence in

Table 3 as representing a unique stable equilibrium in each country, we could infer that fiscal policy

must have been passive during our sample period. In fact, this is what our estimation results for the

fiscal rule suggest. According to table 1, the response to debt accumulation is significantly different

from zero (except in Sweden), and lies in all cases within the theoretical interval

1

d

F

<

1

, which

places the economies in the MD region of stability. As Bohn (1998) has shown, a greater than zero

response to debt accumulation is a sufficient condition for solvency, independently of the relative

evolution of interest rates and output growth.

We can therefore conclude that policy discipline is omnipresent in our sample. Overall, the empirical

evidence presented so far seems to support the prevalence of a monetary dominance policy regime

during the two pre-EMU decades.

29

-
Figure 4: Difference Between Actual and Counterfactual Short Term Interest Rates

Belgium

Denmark

30
25
20
15
10
5
0
-5
-10
-15
-20
-25
-30
79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

30
25
20
15
10
5
0
-5
-10
-15
-20
-25
-30
79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

Spain

France

30
25
20
15
10
5
0
-5
-10
-15
-20
-25
-30
79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

30
25
20
15
10
5
0
-5
-10
-15
-20
-25
-30
79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

Ireland

Italy

30
25
20
15
10
5
0
-5
-10
-15
-20
-25
-30
79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

30
25
20
15
10
5
0
-5
-10
-15
-20
-25
-30
79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

30

Figure 4. (Continued)

The Nederlands

Austria

30
25
20
15
10
5
0
-5
-10
-15
-20
-25
-30
79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

30
25
20
15
10
5
0
-5
-10
-15
-20
-25
-30
79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

Portugal

Finland

30
25
20
15
10
5
0
-5
-10
-15
-20
-25
-30
79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

30
25
20
15
10
5
0
-5
-10
-15
-20
-25
-30
79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

Sweden

United Kingdom

30
25
20
15
10
5
0
-5
-10
-15
-20
-25
-30
79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

30
25
20
15
10
5
0
-5
-10
-15
-20
-25
-30
79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

5.3.

Policy shocks during the 20 pre-EMU years

Our characterisation of policy behaviour has two basic components. One is the systematic component,

which is represented by the part of the rule that describes the elements of inertia and the endogenous

response of the policy authority to past (debt) or expected (inflation, output gap) economic variables.

The other one is the set of non-systematic actions represented by the random component of the policy

rule. So far we have focused on the systematic behaviour of policy. In this section we look at some

empirical characteristics of the non-systematic policy actions.

31

As we argued in sections 3 and 4, and formally reflected in expressions (9), (12), and (13), the random

component of our estimated rules is a mixture of sources of variability stemming from (a) errors in

forecasting the policy target variables, (b) the imperfect control of the policy process, and (c) true

discretionary policy actions. Thus, interpreting this component of the rule as reflecting discretionary

policy shocks requires caution. One could argue that the contribution of forecasting errors may be

negligible because they are buffered by the high policy inertia and because offsetting effects between

errors of different sign may occur. Moreover, we can reasonably assume that shocks arising from an

imperfect control of the policy process source may be exceptional and, in any case, exhibit a relatively

low variability. Consequently, one could think of the non-systematic component as mainly reflecting

genuine discretionary policy actions.

With these caveats in mind, we have used the residuals of estimated policy rules to compute26 the

contemporaneous correlation between monetary and fiscal policy shocks within and across countries.

Some of the correlation coefficients are presented in table 5. We have also computed standard

deviations of such estimated policy-rule residuals for the whole sample, for the 1980s, and for the

1990s to measure non-systematic variability and its changes over the sample period (Table 6).

Table 5: Correlations across policy shocks (a)

Within country
Between fiscal and
monetary policy
shocks.
-0.068
0.237
0.308
0.252
0.246
-0.103
0.055
-0.336
0.247
0.253
-0.017
0.211
0.354

Belgium
Denmark
Germany
Spain
France
Ireland
Italy
The Netherlands
Austria
Portugal
Finland
Sweden
United Kingdom

Between Germany and each country

Fiscal policy
shocks

Monetary policy
shocks

-0.050
-0.026

-0.092
0.050
-0.074
0.015
-0.169
0.110
0.204
0.018
0.010
-0.091

0.469*
0.045

-0.185
0.653*
-0.055
-0.058
0.621*
0.262
-0.100
0.171
0.113
0.239

(a) Correlation coefficients based on the residuals from models in tables 1 and 3. Quarterly residuals in the
monetary rules have been annualised by taking arithmetic averages over the year.
* Significant at 5%
Critical value at 5% 2x(17)-1/2=0.49 for a sample size of 17, and 2x(20)-1/2=0.45 for sample sizes of 20.

26 Yearly monetary policy residuals have been obtained as averages of quarterly residuals.

32

Table 6: Standard deviations of policy shocks (a)

Whole
Sample
(79-98)
0.952
1.203
0.795
0.832
0.472
1.066
1.039
0.940
0.738
1.263
0.939
1.529
0.956

Fiscal

1980s
(79-89)

1990s
(90-98)

0.892
0.991
0.775
0.867
0.568
1.084
0.978
0.728
0.496
1.629
1.209
1.713
0.906

1.029
1.487
0.823
0.833
0.345
1.093
1.154
1.132
0.992
0.849
0.499
1.313
0.954

Whole
Sample
(79-98)
0.377
0.821
0.282
0.904
0.433
1.481
0.425
0.407
0.365
0.671
0.540
1.110
0.516

Monetary

1980s
(79-89)

1990s
(90-98)

0.404
1.053
0.329
1.110
0.489
1.207
0.261
0.409
0.443
0.866
0.614
0.944
0.569

0.289
0.414
0.176
0.540
0.278
1.686
0.542
0.187
0.167
0.468
0.457
0.933
0.397

Belgium
Denmark
Germany
Spain
France
Ireland
Italy
The Netherlands
Austria
Portugal
Finland
Sweden
United Kingdom

(a) Standard deviations based on the residuals from models in tables 1 and 3. Quarterly residuals in the monetary
rules have been annualised by taking arithmetic averages over the year.

To the extend that our residuals can be interpreted as mainly representing discretionary policy actions,

the following empirical facts regarding non-systematic policy behaviour arise form the tables:

[1] Fiscal and monetary policy shocks are uncorrelated within each country (Table 5).

[2] Fiscal shocks are uncorrelated across countries (Table 5)

[3] Monetary policy shocks are also uncorrelated across countries (Table 5), except for some

relatively high correlation not only among countries traditionally included in the former

Deutschmark area, particularly Belgium and the Netherlands27, but also between France and

Germany.

[4] Fiscal policy shocks display significantly higher variability than monetary shocks. The exceptions

are Ireland, where it is lower, and in Spain and France, where it is similar (Table 6).

[5] Relative to the 1980s, the volatility of monetary policy shocks generally decreased in the 1990s

(Italy, Ireland, and Sweden are the exceptions), whereas no clear pattern arises for fiscal shocks

between both sub-periods (Table 6).

27 Pairwise correlation between other countries of the former Deutschmark enlarged with France, such as
Belgium-Austria or France-Netherlands, are also statistically significant. Overall, correlation coefficients
between Belgium, Germany, France, Netherlands and Austria tend to be relatively high, compared with the
rest of the simple correlation coefficients in the panel. Full results are available on request from the authors.

33

These facts signal two characteristics of the non-systematic component of economic policy during the

pre-EMU period that deserve to be emphasised. First, [1] to [3] suggest that co-ordination of fiscal

and monetary policy measures was absent, both within and across countries. Thus, each policy seems

to have acted as an independent stabiliser and as a potential source of asymmetric macroeconomic

variability. Second, while it is probably true that [5] is explained by the policy constraints imposed

during the 90s by the Maastricht criteria for participation in the third stage of EMU28, [4] suggests

that, over the sample period, non-systematic actions have been taken much more frequently by fiscal

authorities than by the central banks.

As we argue below, EMU might bring a policy shift by introducing effective constraints to the

variability of non-systematic fiscal policy, which seems to have been the most active independent

discretionary policy tool in the pre-EMU period.

6.

TO WHAT EXTENT IS THE EMU MACRO POLICY FRAMEWORK “NEW”?

The macroeconomic institutional architecture of EMU has two basic pieces. On the one side, a single

independent central bank, the ECB, is in charge of conducting monetary policy with the strong

mandate of preserving price stability, explicitly defined as an inflation rate below 2% over the

medium term. On the other side, the Stability and Growth Pact (SGP) constraints the behaviour of the

various independent national governments in conducting fiscal policy. The SGP calls for ‘close to

balance or in surplus’ medium term budgetary positions, and requires that, leaving aside exceptional

circumstances, national budget deficits never go above the explicit upper limit of 3% of GDP. The

SGP is a guarantee for sound public finances in EMU, which provides a fiscal environment in which

the ECB can effectively preserve price stability.

The usual way to refer to this institutional macroeconomic architecture is to say that it represents a

unique historical development that brings a genuine policy regime change for macroeconomic policy.

There is a question to ask to what extent the empirical evidence presented here is consistent with this

interpretation of the institutional setting of EMU. In a first approximation, we would say that the

change might be more apparent than real. In any case, on the basis of the results presented here, the

policy shift seems less drastic than anticipated at the outset of stage 3 of EMU.

Indeed, such assertions need additional explanations and some qualifications. It may be useful to start

by redefining the institutional setting of EMU in terms of the policy-rule framework applied in this

paper.

28

In particular, interest rates convergence.

34

With regard to monetary policy, the ECB mandate calls for an effective counteraction against

inflationary pressures. This implies that when the ECB expects inflation to deviate from target it must

adjust its target policy instrument (the nominal interest rate) strongly enough to affect the real interest

rate in the appropriate direction. Therefore, according to section 5.2, we can say that the ECB pursues

an “active” monetary policy. As for fiscal policy, the SGP objective is that fiscal discipline prevails

or, in other words, that governments guarantee their own solvency. The close-to-balance-or-in-surplus

clause, albeit not necessary, is a sufficient condition to keep the stock of debt under control in the

medium run. Applying again the conceptual framework of section 5.2, the Stability and Growth Pact

calls for fiscal policy to be “passive” in Member States. As we have pointed out, the combination of

an active monetary policy and a passive fiscal policy identifies a “monetary dominance” policy

regime, which therefore provides an accurate description of the EMU regime. Interestingly, this is

precisely the regime that we claim has prevailed during the 20 pre-EMU years. Since in both cases the

system of fiscal and monetary rules can be classified as monetary dominance, pre-EMU and EMU

policy regimes seem to be alike. This suggests that

the key characteristics of the systematic

component of macroeconomic policy in EMU may not be different from what they used to be.

Although fiscal solvency seems to be guaranteed in both regimes, there is a clear difference as regards

the way solvency is ensured. While the SGP puts a brake to debt accumulation by explicitly limiting

the variability of the deficit, the rules applied by fiscal authorities in the past basically relied on the

systematic responses to debt accumulation. Where fiscal behaviour under EMU is concerned, this can

make a significant difference. On the basis of historical series of total deficits in the different Member

States, pre-EMU fiscal behaviour seems to be in conflict with the two requirements of the Pact. Pre-

EMU fiscal behaviour cannot be characterised as ensuring close-to-balance positions in the medium

term, while deficits above 3% have not been unusual.

But how will EMU affect fiscal behaviour? The answer does not seem straightforward. The reason is

that the two requirements of the SGP are compatible with a wide range of “passive” fiscal rules.

However, we can take our pre-EMU fiscal specification as the benchmark for comparison and look at

what type of modifications could make it compatible with the requirements of the Pact. In this sense,

one should bear in mind that, according to our results, the estimated fiscal reaction (primary surplus

adjustments)

to the output gap basically represents the response associated with automatic

stabilisation. This seems to be consistent with the spirit of the Pact, which implicitly favours the use

of automatic stabilisers in order to maintain close-to-balance positions in the medium term. Therefore,

35

we can rather safely consider that the output gap component of systematic fiscal policy will not

change significantly in EMU29.

This leaves us with potential for modification in two other elements of fiscal behaviour: The response

to the stock of debt and the variability of fiscal policy shocks. A likely scenario is that the SGP forces

a modification of both elements. A stronger response to debt will accelerate the consolidation efforts

needed during the transition period to a close-to-balance position. At the same time, a reduction in the

variability of, according to pre-EMU evidence, the most volatile non-systematic policy tool may be

needed in order to respect the 3% constraint during the transition to a close-to-balance position. Once

this position is reached, the variability of fiscal-policy shocks should remain lower than in the pre-

EMU period if a strict interpretation of the Pact calling for just automatic stabilisation and no

discretionary actions prevails. Yet, a larger response to the stock of debt would certainly shift the

historical rule, but still leave the economy in an MD regime. Therefore, as mentioned above, there

will be no policy shift in the context of the conceptual setting o section 5.2.

With regard to fiscal shocks, a reduction of their volatility will imply a change in the variance of the

non-systematic component of fiscal policy. However, as Leeper and Zha (2001b) point out, where

policy analyses are concerned, the relevance of a change in the variance of the random component of

policy depends on the extend to which anticipated or unanticipated changes are important for

macroeconomic variability. If, as New Keynesian macroeconomics suggests, anticipated policy

changes are a main source of macroeconomic variability, a change in the properties of the

unanticipated component of policy may be largely irrelevant. Thus, even if it were permanent, a

reduction in the variance of the non-systematic component of fiscal policy brought by EMU may turn

out to be a policy shift of minor importance30.

7. CONCLUDING REMARKS

An interesting question in connection with EMU is to what extent we can rely on pre-EMU

macroeconomic variability to analyse EMU macroeconomic interactions. We tackle this question by

assessing the evidence of a policy shift between the pre-EMU and EMU periods.

We have carried out such an assessment in two steps. First we have characterised policy behaviour

during the 20 pre-EMU years through the estimation and analysis of

forward-looking fiscal and

monetary policy rules for EU countries. Then we have asked whether the resulting rules and the

29

Indeed, we assume no EMU-induced changes in the size of automatic stabilisers.

30 We should stress that our focus here is on the relevance of the shift for macroeconomic analysis. A different

matter is the political feasibility of the reduction in variance and so of the fiscal architecture of EMU.

36

policy regime they identify are different from the ones brought by the EMU policy framework. Our

conclusion is that the pre-EMU and EMU policy regimes look similar. Although the fiscal response to

the stock of debt might be larger in EMU than it was in the pre-EMU period, one should not expect

significant changes in the output gap component of systematic fiscal policy. All in all, the EMU

economic-policy setting will still be characterised as a monetary dominance regime. However, a

potential source of policy shift may be the reduction of the variability in the random component of

fiscal policy imposed by the Stability and Growth Pact. This shift might be temporary or, if

permanent, of relatively less importance for macroeconomic analysis.

In addition, several by-products follow from our analysis:

1. Our results support the empirical relevance of the simple forward-looking rules that we have

considered, in the sense that they provide a reasonable description of actual policy behaviour. In

particular:

• The fiscal rule characterises governments as generally reactive to debt accumulation and

applying a counter-cyclical fiscal policy.

• As for the monetary rule, it reproduces for our extended sample period and panel of EU

countries the overall results obtained in previous literature for the major economies.

• The leading role of Germany in the setting of European monetary policy during the 80s and

90s has been corroborated.

•

•

In addition, we find that the counter-cyclical activity of monetary policy looks stronger than

previously reported.

In connection with the two pillar strategy of the ECB, we present a piece of evidence

suggesting that money may legitimately belong to the second pillar, but

its relative

informational content may not justify the existence of a first pillar.

2.

In the light of the holistic view to macroeconomic policy analysis provided by the recently

proposed Fiscal Theory of the Price level (FTPL), we look jointly at the estimated fiscal and

monetary policy rules as a test to identify the policy regime prevalent during the pre-EMU period.

We claim that evidence can be reasonably interpreted as pointing to a “monetary dominance”

regime.

3. Finally, our results regarding non-systematic policy suggest that co-ordination has been absent at

the level of discretionary shocks. While monetary and fiscal variability seem uncorrelated both

37

within and across31 countries, non-systematic fiscal policy appears as a more active policy tool

than non-systematic monetary policy.

31 Except for the monetary correlation coefficients among the former Deutschmark area countries and France.

38

STATISTICAL ANNEX

1.

LIST OF COUNTRIES

Our panel of countries includes 13 EU Member States (Belgium, Denmark, Germany, Spain,

France, Ireland, Italy, the Netherlands, Austria, Portugal, Finland, Sweden and the UK).

Greece and Luxembourg have been excluded because of the lack of data.

2.

LIST OF VARIABLES AND INSTRUMENTS

2.1.

List of policy instruments

The nominal interest rate, which is the policy instrument in the monetary rule, is a quarterly

money market rate (3-month) in percentage points taken from the IMF (IFS). The plots of the

series can be found in figure 2.

The annual primary surplus, the policy instrument in the fiscal rule, has been obtained from

AMECO (a Commission, DG ECFIN, macroeconomic databank) and is expressed as a

percentage of GDP. The graphs for these series are in figure 1. The cyclically-adjusted

primary surplus (from the same source) has been used in the estimation of the discretionary

fiscal policy responses to debt and output gap.

2.2.

List of policy targets

The inflation rate, a policy target in the monetary rule, has been calculated as quarter-on-

quarter annual growth rates of the quarterly consumer price index taken from the OECD

(MEI). The graphs for these series are presented in figure A1 at the end of the paper.

The output gap, which enters both monetary and fiscal rules, has been obtained on the basis

of the quarterly series of the industrial production index taken from the IMF (IFS). Such raw

series have been de-trended by using the H-P filter (l =1200) over the sample period 1968Q1

to 2000Q4, common to all the countries, in order to reduce as much as possible the end-point

bias (only the period 1979Q1-1998Q4 has been included in the sample period). The

quarterly output gap has been calculated as the difference between the actual and de-

trended series, expressed in percentage points of the de-trended levels. The series are included

in figure A2. In the case of fiscal rules, the annual output gap has been calculated by first

annualising the quarterly series of the industrial production index and then applying the H-P

(l =100) over the period 1968-2000. The annual output gap is also expressed as a percentage

of the de-trended levels. The resulting series can be seen in figure A3.

39

The annual government stock of debt, a policy target in the fiscal rule, has been obtained

from AMECO (DG ECFIN) and is expressed as a percentage of GDP. Since AMECO

provides the series of debt calculated at the end of the year, the series enter the fiscal rule

with a lag. Figure A4 shows the series used in this paper.

2.3.

List of instrumental variables

The real exchange rate has been included in the set of instrumental variables for the

monetary rule as the quarter-on-quarter annual percentage change of the quarterly real

exchange rate index taken from the Commission Services (DG ECFIN). The same series

annualised as arithmetic averages within the natural year have been used to calculate year-on-

year percentage changes in the annual real exchange rate.

The international commodity-price inflation rate has been included in the set of

instrumental variables for the monetary rule as the quarter-on-quarter annual percentage

change of the quarterly international commodity-price index taken from the Commodity

Research Bureau (CRB). The same series annualised as arithmetic averages within the natural

year have been used to calculate year-on-year percentage changes

in the annual

international commodity-price. The series are common to all the countries.

The monetary growth rate has been included in the set of instrumental variables for the

monetary rule as the quarter-on-quarter annual percentage change of the quarterly M3 index

taken from Eurostat for Belgium, Germany, France, Ireland, and Spain, and from the OECD

(MEI) for Denmark, and Sweden. The same series annualised as arithmetic averages within

the natural year have been used to calculate year-on-year percentage changes in the annual

M3 index. The original raw M3 indices are not available at all, or the series are too short, in

Italy, the Netherlands, Austria, Portugal, Finland and the UK.

The nominal interest rate series annualised taking arithmetic averages within natural years

have been used as instrumental variable for the fiscal rules.

3.

ESTIMATION

Models in Tables 1 to 3 have been estimated with the GMM routine of TSP (non-linear

estimation). Standard errors have been calculated using a heteroskedastic (robust White) and

autocorrelation consistent covariance matrix (Barlett –see Newey and West, 1987) over the

sample period, which is 1979Q1-1998Q4 for the monetary rule and 1979-1998 for the fiscal

rule. As shown in Tables 1 to 3, the exceptions to these sample sizes are, for the fiscal rule,

40

Portugal (the annual interest rate is only available since1981), and, for the monetary rule,

Belgium (quarterly money growth rates are only available since 1981Q1), Ireland (quarterly

money growth rates are only available since 1979Q1)32, and Portugal (the quarterly interest

rates are only available since 1981Q1).

Several dummy variables have been included:

3.1.

Fiscal rule

Germany: A dummy with value 1 between 1990 and 1994 was included to improve the

explanatory power of the model. The estimated coefficient in the equation of the primary

balance was –1.79 (standard error: 0.95), with a p-value of 6%. In the case of the cyclically-

adjusted primary balance, the estimate was –2.91, clearly significant with a standard error of

1.03.

France: A dummy with value 1 between 1992 and 1995 was included to improve the

explanatory power of the model. The estimated coefficient in the equation of the primary

balance was –1.86 (standard error: 0.27), significant at 5%. In the case of the cyclically-

adjusted primary balance, the estimate was –2.61 (0.25), significant at 5%.

Portugal: A dummy with value 1 between 1983 and 1987 was included to alleviate the

pervasive effects of odd values of the output gap on the explanatory power of the model. The

estimated coefficient in the equation of the primary balance was –1.34 (standard error: 0.50),

significant at 5%. In the case of the cyclically-adjusted primary balance, the estimate was

0.25, clearly non-significant with and standard error of 0.45.

3.2.

Monetary rule

Ireland: A dummy taking value 1 between 1992Q4 and 1993Q1 was included to deal with the

effects of the disturbances of the EMS crisis on the Irish interest rate. The estimated

coefficient was 22.4 (standard error: 6.68), significant at 5%.

Portugal: A dummy taking value 1 between 1983Q1 and 1987Q4 was included to alleviate

the pervasive effects of odd values of the output gap on the explanatory power of the model.

The estimated coefficient was 5.57 (standard error: 1.41), significant at 5%.

32 This represents a lost of 4 observations when introducing lags in this variable

41

Sweden: A dummy taking value 1 in 1992Q3 was included to control for the effects of the

disturbances of the EMS crisis on the Swedish interest rate. The estimated coefficient was

47.4 (standard error: 9.61), significant at 5%.

42

REFERENCES

Andrés, J., Ballabriga, F., Vallés, J., 2000. Monetary Policy and Exchange Rate Behaviour in the
Fiscal Theory of the Price Level. Bank of Spain, Research Department, WP series n° 0004.

Andrés, J., Ballabriga, F., Vallés, J., 2001. Non-Ricardian Fiscal Policies in an Open Monetary
Union. Mimeo.

Barro, R., 1979. On the Determination of Public Debt. Journal of Political Economy, 87, pp. 940-971.

Benhabib, J., Schmitt-Grohé, S., Uribe, M., 2001. Monetary Policy and Multiple Equilibria. American
Economic Review, 91(1), pp. 167-186.

Bohn, H., 1998. The Behavior of US Public Debt and Deficits. The Quarterly Journal of Economics,
113, pp. 949-963.

Clarida, R., Galí, J., Gertler, M., 1998. Monetary Policy Rules in Practice: Some International
Evidence. European Economic Review, 42, pp. 1033-1067.

Clarida, R., Galí, J., Gertler, M., 1999. The Science of Monetary Policy: A New Keynesian
Perspective. Journal of Economic Literature, 37, pp. 1661-1707.

Clarida, R., Galí, J., Gertler, M., 2000. Monetary Policy Rules and Macroeconomic Stability:
Evidence and Some Theory. The Quarterly Journal of Economics, 115 (1), pp. 147-180.

Cochrane, J., 1999. A Frictionless View of the US Inflation. In Bernanke and Rotemberg, (eds.):
NBER Macroeconomic Annual, Cambridge, MA, MIT Press, pp. 323-384.

Friedman, M., 1959. A Program for Monetary Stability. Fordham University Press, New York.

Galí, J., 2001. Monetary Policy in the Early Years of EMU. Mimeo.

Goodfriend, M.,1991. Interest Rate and the Conduct of Monetary Policy. Carnegie-Rochester
conference Series on Public Policy, 34, pp. 7-30.

Hagen, von, J., Hughes Hallett, A., and Strauch, R., 2002. Quality and Success of Budgetary
Consolidations. In M. Buti, J. von Hagen and C. Martinez-Mongay (eds): The Behavior of Fiscal
Authorities: Stabilisation, Growth and Institutions, chapter 2, Palgrave, London.

Kidland , F., Prescott, E., 1977. Rules Rather Than Discretion: The Inconsistency of Optimal Plans.
Journal of Political Economy, 85, pp. 473-491.

Leeper, E., 1991. Equilibria Under “Active” and “Passive” Monetary and Fiscal Policies. Journal of
Monetary Economics, 27, pp. 129-147.

Leeper, E., 1993. The Policy Tango: Toward a Holistic View of Monetary and Fiscal Effects.
Economic Review, Federal Reserve Bank of Atlanta, 78 (4), pp. 1-27.

Leeper, E., Zha, T., 2001a. Assessing Simple Policy Rules: A View from a Complete Macroeconomic
Model. Economic Review, Federal Reserve Bank of St. Louis, July/August, pp. 83-110.

Leeper, E., and Zha, T., 2001b. Toward a Theory of Modest Policy Interventions. Mimeo

43

Newey, W. K., and West K. D., 1987. A Simple Positive Semi-Definite Heteroskedasticity and
Autocorrelation Consistent Covariance Matrix. Econometrica, 55, 703-708.

Sargent, T., Wallace, N., 1981. Some Unpleasant Monetarist Arithmetic. Quarterly Review, Federal
Reserve Bank of Minneapolis, Fall, pp. 1-17.

Sims, C., 1994. A Simple Model for the Study of the Determination of the Price Level and the
Interaction of Monetary and Fiscal Policy. Economic Theory, 4(3), pp. 381-399.

Taylor, J., 1993. Discretion versus Policy Rules in Practice. Carnegie-Rochester Series on Public
Policy, 39, pp. 195-214.

Taylor, J., 1999. Monetary Policy Rules. University of Chicago Press, Chicago.

Taylor, J., 2001. Reassessing Discretionary Fiscal Policy. Mimeo.

Van den Noord, P., 2002. Automatic Stabilisers in the 1990s and beyond. In M. Buti, J. von Hagen
and C. Martinez-Mongay (eds): The Behavior of Fiscal Authorities: Stabilisation, Growth and
Institutions, chapter 2, Palgrave, London.

Woodford, M., 1994. Monetary Policy and Price Level Determinacy in a Cash-in-Advance Economy.
Economic Theory, 4(3), pp. 345-380.

Woodford, M., 1999. Comment to “A Frictionless View of the US Inflation” in J. Cochrane. In
Bernanke and Rotemberg (eds): NBER Macroeconomic Annual, Cambridge, MA, MIT Press, pp. 390-
418.

Woodford, M., 2000. Fiscal Requirements for Price Stability. Mimeo.

44

Figure A1: Quarterly inflation rate

Belgium

Denmark

33

30

27

24

21

18

15

12

9

6

3

0

-3

33

30

27

24

21

18

15

12

9

6

3

0

-3

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

Germany

Spain

33

30

27

24

21

18

15

12

9

6

3

0

-3

33

30

27

24

21

18

15

12

9

6

3

0

-3

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

France

Ireland

33

30

27

24

21

18

15

12

9

6

3

0

-3

33

30

27

24

21

18

15

12

9

6

3

0

-3

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

Italy

The Netherlands

33

30

27

24

21

18

15

12

9

6

3

0

-3

33

30

27

24

21

18

15

12

9

6

3

0

-3

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

45

Figure A1 (Continued)

Austria

Portugal

33

30

27

24

21

18

15

12

9

6

3

0

-3

33

30

27

24

21

18

15

12

9

6

3

0

-3

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

Finland

Sweden

33

30

27

24

21

18

15

12

9

6

3

0

-3

33

30

27

24

21

18

15

12

9

6

3

0

-3

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

United Kingdom

33

30

27

24

21

18

15

12

9

6

3

0

-3

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

46

Figure A2: Quarterly output gap

Belgium

Denmark

14

7

0

-7

-14

14

7

0

-7

-14

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

Germany

Spain

14

7

0

-7

-14

14

7

0

-7

-14

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

France

Ireland

14

7

0

-7

-14

14

7

0

-7

-14

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

Italy

The Netherlands

14

7

0

-7

-14

14

7

0

-7

-14

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

47

Figure A2 (continued)

Austria

Portugal

14

7

0

-7

-14

30

25

20

15

10

5

0

-5

-10

-15

-20

-25

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

Finland

Sweden

14

7

0

-7

-14

14

7

0

-7

-14

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

United Kingdom

14

7

0

-7

-14

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

79-Q1

80-Q1

81-Q1

82-Q1

83-Q1

84-Q1

85-Q1

86-Q1

87-Q1

88-Q1

89-Q1

90-Q1

91-Q1

92-Q1

93-Q1

94-Q1

95-Q1

96-Q1

97-Q1

98-Q1

48

Figure A3: Annual output gap

Belgium

Denmark

14

7

0

-7

-14

14

7

0

-7

-14

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

Germany

Spain

14

7

0

-7

-14

14

7

0

-7

-14

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

France

Ireland

14

7

0

-7

-14

14

7

0

-7

-14

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

Italy

The Netherlands

14

7

0

-7

-14

14

7

0

-7

-14

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

49

Figure A3 (continued)

Austria

Portugal

14

7

0

-7

-14

35

30

25

20

15

10

5

0

-5

-10

-15

-20

-25

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

Finland

Sweden

14

7

0

-7

-14

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

United Kingdom

14

7

0

-7

-14

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

14

7

0

-7

-14

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

50

Figure A4: Public Debt as a Percentage of GDP.

Belgium

Denmark

150

125

100

75

50

25

0

150

125

100

75

50

25

0

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

Germany

Spain

150

125

100

75

50

25

0

150

125

100

75

50

25

0

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

France

Ireland

150

125

100

75

50

25

0

150

125

100

75

50

25

0

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

Italy

The Netherlands

150

125

100

75

50

25

0

150

125

100

75

50

25

0

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

51

1990

1991

1992

1993

1994

1995

1996

1997

1998

Figure A4 (Continued)

Austria

Portugal

150

125

100

75

50

25

0

150

125

100

75

50

25

0

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

Finland

Sweden

150

125

100

75

50

25

0

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

United Kingdom

150

125

100

75

50

25

0

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

150

125

100

75

50

25

0

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

52