Fiscal rules, fiscal space and procyclical fiscal policy. No 1872 / December 2015.
Date: 2016-02-26
Institutions: European Central Bank
Subjects: budget policy, budgetary equilibrium, debt, econometrics, economic model, fiscal policy, incomes policy, public economy, public expenditure

Carolin Nerlich and Wolf Heinrich Reuter  

Working Paper Series 

Fiscal rules, fiscal space and 
procyclical fiscal policy 

No 1872 / December 2015 

Note: This Working Paper should not be reported as representing the views of the European Central Bank (ECB). 
The views expressed are those of the authors and do not necessarily reflect those of the ECB 

  
 
Abstract

In this paper we analyse the interaction of ﬁscal rules and ﬁscal space.
We ﬁnd strong evidence for ﬁscal rules being associated with higher ﬁscal
space. Furthermore, the analysis shows that countries with more ﬁscal
space tend to have higher discretionary expenditures, but that this eﬀect
is signiﬁcantly reduced if ﬁscal rules are in place. A similar eﬀect can be
observed for the procyclicality of ﬁscal policy, which is signiﬁcantly higher
in an environment of ample ﬁscal space, while this diﬀerence is reduced
with ﬁscal rules. Regarding the diﬀerent types of ﬁscal rules, we ﬁnd the
strongest results for expenditure rules and to a lesser extent for balanced
budget rules, but none for debt rules.

JEL-Classiﬁcation: E61, E62, H60
Keywords: Fiscal Space, Fiscal Rules, Discretionary Fiscal Policy, Procyclicality

ECB Working Paper 1872, December 20151Non-technical summary

In response to the economic and ﬁnancial crisis, many EU countries have strength-
ened their ﬁscal governance frameworks by introducing ﬁscal rules. Although it
is widely acknowledged that ﬁscal rules, which constrain ﬁscal policy through
numerical limits on ﬁscal aggregates, are essential for limiting the deﬁcit bias,
they are sometimes criticised for increasing the procyclicality of ﬁscal policy, in
particular if deﬁned in nominal terms. More precisely, it is argued that during a
boom phase ﬁscal rules do not prevent ﬁscal policy from turning expansionary,
while at times of a recession ﬁscal policy is potentially restrictive as govern-
ments need to comply with the rules’ requirements. This eﬀect is assumed to
be particularly pronounced in periods of limited ﬁscal space, while it might be
less obvious in an environment of high ﬁscal space.
In the paper we address the question whether ﬁscal rules are indeed procycli-
cal and whether the countries’ available ﬁscal space matters in this respect.
Concretely, we test the hypothesis whether ﬁscal rules in interaction with the
countries’ ﬁscal space would be less procyclical. In doing this we ﬁrst estimate
the impact of ﬁscal rules on ﬁscal space. We deﬁne ﬁscal space in line with the
methodology by Ghosh et al. (2013) as the diﬀerence between a debt limit and
the actual debt, with the debt limit being calculated by the reaction function
of the primary balance to past debt levels. For ﬁscal rules we use an updated
version of the dataset set up in Nerlich and Reuter (2013) to account for the
latest improvements of national ﬁscal frameworks in the EU countries.
In a
second step we examine how the interaction of ﬁscal rules and ﬁscal space is
aﬀecting the responsiveness of discretionary ﬁscal policy. Concretely, we anal-
yse whether ﬁscal rules help to lower the increase in discretionary measures at
times of high ﬁscal space. Furthermore, our hypothesis is that if ﬁscal rules help
to limit discretionary ﬁscal policy and discretionary expenditures and revenues
move with the cycle, ﬁscal rules would make ﬁscal policy less procyclical.
We ﬁnd strong evidence for ﬁscal rules being associated with higher ﬁscal space,
i.e. the ﬁscal room for manoeuvre is higher in those countries which have estab-
lished ﬁscal rules. This may not be surprising as ﬁscal rules are implemented
to keep primary balances under control and by fostering credibility they are
expected to reduce the country’s interest expenditure. Both would help to keep
the actual debt level under control and lift the debt limit, beyond which debt
turns unsustainable, which in turn should raise the ﬁscal space of a country.
Furthermore, our analysis shows that higher ﬁscal space is correlated with in-
creased discretionary expenditures/ lower discretionary revenues, but that this
eﬀect is signiﬁcantly reduced if ﬁscal rules are in place. This could be inter-
preted such that ﬁscal space allows ﬁscal policy to be more procyclical while
ﬁscal rules seem to counteract this procyclicality by reducing the responsive-
ness of discretionary expenditures and discretionary revenues. When splitting
the results by diﬀerent types of ﬁscal rules, we ﬁnd signiﬁcant coeﬃcients for
expenditure and, to a lesser extent, balanced budget rules, but none for debt
rules.

ECB Working Paper 1872, December 201521

Introduction

This paper analyses the impact of ﬁscal rules on the countries’ available ﬁscal
space and how their interaction determines the procyclicality of ﬁscal policy.
Although it is widely acknowledged that ﬁscal rules - by constraining ﬁscal policy
through numerical limits on budgetary aggregates - are essential for limiting
the deﬁcit bias, they are sometimes criticised for increasing the procyclicality
of ﬁscal policy, in particular if deﬁned in nominal terms. More precisely, it is
argued that during a boom phase ﬁscal rules do not prevent ﬁscal policy to turn
expansionary, while at times of a recession ﬁscal policy is potentially restrictive
as governments need to comply with the rules’ requirements. This eﬀect is
assumed to be particularly pronounced in periods of limited ﬁscal space, while
it might be less obvious in an environment of high ﬁscal space.
Our paper ﬁrst estimates the relationship between ﬁscal rules and ﬁscal space.
Thereby, we follow Ghosh et al. (2013) and deﬁne ﬁscal space as the diﬀerence
between a so-called debt limit, beyond which (without extraordinary measures)
debt would be unsustainable, and the current debt level. Several papers have
shown that ﬁscal rules help to keep primary balances under control and by
fostering credibility reduce a country’s interest expenditure. This, in turn, would
support the view that ﬁscal space would be higher in countries with credible
ﬁscal rules, as they help to reduce the actual debt level and lift the debt limit.
In a second step we examine the link between the interaction of ﬁscal rules
and ﬁscal space with discretionary ﬁscal policy. Among others, it is tested
whether ﬁscal rules limit the responsiveness of discretionary ﬁscal policy to
changes in ﬁscal space and whether ﬁscal rules help to lower the increase in
discretionary expenditures/ decrease in discretionary revenues in times of high
ﬁscal space. We then analyse the interaction of ﬁscal rules and ﬁscal space with
the procyclicality of ﬁscal policy. Our hypothesis is that if ﬁscal rules help to
limit discretionary ﬁscal policy and if discretionary expenditures and revenues
move with the cycle, this would support the view that ﬁscal rules would help to
reduce the cyclicality of ﬁscal policy rather than to increase it. We also try to
address the question whether it matters which kind of ﬁscal rules are in place.
Thus, we estimate diﬀerent settings for diﬀerent kinds of ﬁscal rules.
We use an updated version of the dataset set up in Nerlich and Reuter (2013)
to account for the latest improvements of national ﬁscal frameworks in the EU
countries. For ﬁscal rules we diﬀerentiate between diﬀerent kinds of ﬁscal rules,
namely balanced budget, debt and expenditure rules. We calculate ﬁscal space
using the methodology by Ghosh et al. (2013) for the period 1990 to 2014. To
obtain ﬁscal space the debt limit is calculated by the reaction function of the
primary balance to past debt levels and compared with the actual debt level.
Thereby, we account for the fact that ﬁscal space can vary over time, for example
due to interest rate changes or institutional settings such as the introduction of
ﬁscal rules.
While the (budgetary) impact of ﬁscal rules is widely discussed in the litera-
ture, to our knowledge the relation between ﬁscal rules, ﬁscal space and the
interaction of the two with ﬁscal policy making has not yet been analysed so

ECB Working Paper 1872, December 20153far.
The paper ﬁnds that ﬁscal rules are strongly correlated with higher ﬁscal space,
i.e. the ﬁscal room for manoeuvre seems to be higher in those countries that
have ﬁscal rules in place. Furthermore, the analysis shows that more ﬁscal space
is associated with increased discretionary ﬁscal policy, but that this eﬀect is
signiﬁcantly reduced if ﬁscal rules are in place. Regarding the diﬀerent types of
ﬁscal rules, we ﬁnd particularly strong coeﬃcients for expenditure rules, possibly
reﬂecting the fact that expenditure rules are easier to monitor and are thereby
more credible. Furthermore, we ﬁnd that ﬁscal rules in an environment of ﬁscal
space tend to occur together with less procyclical ﬁscal policy.
The paper is organised as follows. Section 2 describes the data used, i.e. the
calculation of the ﬁscal space and the update of the ﬁscal framework database.
Section 3 estimates the relationship between ﬁscal rules and ﬁscal space.
In
section 4 the link between ﬁscal rules and discretionary ﬁscal policy is analysed,
with a particular view on the available ﬁscal space. Section 5 looks at how ﬁscal
rules and ﬁscal space interact with the procyclicality of ﬁscal policy.

2 Data

2.1 The deﬁnition of ﬁscal space

Fiscal space, which is a relatively new concept, tries to quantify a country’s
room for manoeuvre for ﬁscal policy. The literature oﬀers various ways on
how to deﬁne and calculate the ﬁscal space of a country, which range from the
reaction of the primary balance to changes of the debt level, (potential) tax
revenues to implicit liabilities.
A ﬁrst attempt to calculate ﬁscal space goes back to Bohn (1998, 2008) who
analysed the dynamics of US debt-to-GDP data. In this approach ﬁscal space
can either be zero or inﬁnite, depending on the reaction of the primary ﬁscal
balance to public debt in the past (controlling for other determinants of the
primary balance). It is inﬁnite if the reaction of the primary balance is suﬃ-
ciently strong and zero otherwise, assuming a linear relationship for any amount
of debt. This deﬁnition of ﬁscal space has been extended by Ostry et al. (2010)
and Ghosh et al. (2013)1, by taking into account the work of Abiad and Ostry
(2005), and Mendoza and Ostry (2008), who propose to use squared and cubic
debt terms when calculating the response term.
Others have chosen a diﬀerent approach by calculating the ﬁscal space on the
basis of various measures of tax revenues (including potential, maximum or
structural tax revenues). Aizenman and Jinjarak (2010) deﬁne ﬁscal space as
the number of years of tax revenues that are necessary to repay a country’s
debt, i.e. the public debt divided by the de facto tax base of a country. Brun
et al. (2006) calculate ﬁscal space as the ratio of the current level of revenues to
potential tax revenues, based on structural indicators such as GDP per capita

1This deﬁnition of ﬁscal space has been applied e.g. by Zandi et al. (2011) and Hajnovic

and Zeman (2012).

ECB Working Paper 1872, December 20154and income sectors. Similarly, Bi (2012) uses a general equilibrium model to
derive dynamic Laﬀer curves of taxation and create country speciﬁc (depending
on size and degree of countercyclical policy responses) stochastic ﬁscal limits as
a measure of the ability and willingness of governments to service their debts.
Park (2012) employs a (standard neoclassical) model to generate a Laﬀer curve
of public revenues. He deﬁnes ﬁscal space as the distance between current tax
the maximum tax revenues
revenues and the peak of the Laﬀer curve (i.e.
possible) and investigates how population aging trends aﬀect ﬁscal space.
A third stream of the literature links ﬁscal space to implicit liabilities, such as
aging costs. Mario (2013) uses the S1 indicator2, which captures the required ﬁs-
cal adjustment to reach a debt level of 60% of GDP by 2030. A more short-term
deﬁnition of ﬁscal space is given by Schick (2009, 2012). He deﬁnes ﬁscal space
as the ﬁnancial resources available to the government for ﬁscal policy, namely
growth-enhancing investment in physical and human capital that governments
can ﬁnance with borrowed funds without prejudicing the long-run sustainability
of its ﬁscal position.
This paper does not aim to contribute to the discussion about the various deﬁ-
nitions of ﬁscal space, but relies on the approach used in Ghosh et al. (2013) to
calculate a time and country dependent variable. Thus we follow the estimation
settings and data selection in Ghosh et al. (2013) as closely as possible. Fiscal
space is deﬁned as the diﬀerence between the debt limit and the current debt
level. The debt limit is estimated using historical, but marginal decreasing,
responses of the primary balance to increases in debt and by taking various
levels of interest-rate growth diﬀerentials into account. The debt limit is the
point beyond which either extraordinary (i.e. more than historical) eﬀorts are
necessary or a country defaults. Appendix A.4 gives a more detailed description
of the concept and details of the calculations performed in this paper.
We calculate the ﬁscal space for the EU27 countries3 covering the period 1990
to 2014. We account for the fact that ﬁscal space can vary over time, as can
be seen in Figure 1 which shows the development of ﬁscal space of the EU27
average (country composition varies depending on data availability).
Figure 3 in Appendix A.3 shows the country speciﬁc ﬁscal space, which is diﬀer-
ent across countries, as well as over time. In particular, some countries (Belgium,
Denmark, Finland, France, Italy, the Netherlands, Sweden) had episodes of very
low or no ﬁscal space during the mid-1990s, which in most cases recovered in the
run-up to EMU. In fact, the steep decline in interest rates in the run-up to EMU
are likely to have contributed to the improvement in ﬁscal space in the countries
joining the Euro Area. With the ﬁnancial and sovereign debt crisis unfolding,
the ﬁscal space diminished in many countries, in some of them sharply, from
2007 onwards. Seven countries (Cyprus, Spain, Greece, Italy, Ireland, Portugal,
Slovenia) had very low or no ﬁscal space in 2014. Moreover, Italy stands out
as the only country which had no or very low ﬁscal space throughout the whole
sample period. In turn, in a number of countries, such as Austria, Germany,

2For the deﬁnition of the S1 indicator see European Commission (2012b).
3Due to data availability we do not calculate the ﬁscal space for Croatia.

ECB Working Paper 1872, December 20155Figure 1: Average ﬁscal space (as % of GDP) for EU27 from 1990 to 2014 (coun-
try composition per year changes due to data availability, see Figure 3 in
Appendix A.3)

Estonia, Luxembourg, Malta, the Netherlands, Sweden and Slovakia, the ﬁs-
cal space remained relatively stable at a high level throughout the full period,
possibly also reﬂecting the fact that these countries were less aﬀected by the
sovereign debt crisis.

2.2 Update of the ﬁscal rules dataset

We update the dataset on ﬁscal rules of Nerlich and Reuter (2013) to account
for the latest changes in the ﬁscal frameworks of the EU27. Under ﬁscal rules
we subsume numerical limits on budgetary aggregates which pose a permanent
constrain on ﬁscal policy to ensure ﬁscal sustainability. The dataset contains
information about various characteristics of national numerical ﬁscal rules and
national ﬁscal councils in the EU27 from 1990 to 2014. It combines data from
the European Commission (2012a), the OECD (2003, 2008), the IMF (2013)
and an ESCB-internal dataset on national ﬁscal frameworks (2011, 2012, 2014).
Appendix A.2 shows the updated full dataset of national numerical ﬁscal rules.
The updated dataset conﬁrms that the number of ﬁscal rules, including those in
law or constitutions, continued to increase in recent years (see Figure 2). While
in 1990 only six out of the 27 EU countries had some kind of ﬁscal rule in place,
the number increased to 25 countries in 2014. By now, most countries anchored

ECB Working Paper 1872, December 20156Figure 2: Number of countries having speciﬁc kinds of ﬁscal rules in 1990, 2000, 2010

and 2014

their ﬁscal rules in law or constitution and in more and more countries are
the ﬁscal rules linked to a sanction or automatic correction mechanism. This
is likely to foster the credibility of the ﬁscal rules. Moreover, most countries
have diﬀerent kind of ﬁscal rules in place. In particular, balanced budget rules,
debt rules and expenditure rules covering the general or central government are
wide-spread, while revenue rules continue to be of marginal importance.

3 Fiscal Rules and Fiscal Space

We investigate whether ﬁscal rules and ﬁscal space are closely linked with each
other, in the sense that the room for manoeuvre would be higher in countries
with ﬁscal rules. There are two main arguments supporting this view: First,
ﬁscal rules, by fostering ﬁscal discipline, help to decrease public deﬁcits and
debt levels (e.g. Debrun et al., 2008). By widening the diﬀerence between the
actual debt level and the debt limit this would increase the ﬁscal space of a
country. Second, ﬁscal rules help fostering the trust of investors and ﬁnancial
markets in the soundness of a country’s public ﬁnances (e.g. Iara and Wolﬀ,
2014). This should have a decreasing impact on the risk premia and interest
rates of government bonds, which lifts the debt limit, lowers the actual debt
and thereby would increase ﬁscal space.
We test the eﬀect of ﬁscal rules on ﬁscal space in a simple econometric framework
(Equation 1) for the EU27 countries covering the period 1990-2013:

Si,t = β1Fi,t + X (cid:2)

i,tγ + μi + ηt + (cid:5)i,t

(1)

where Si,t is the average ﬁscal space over the past ten years of country i at
time t and Fi,t is the share of the past 10 years where a (speciﬁc) ﬁscal rule
was in place. Xi,t captures a set of control variables (also expressed in ten year
averages) which could potentially inﬂuence ﬁscal space. These include economic
(GDP per capita, ﬁnancial openness, and trade openness), political (the frag-
mentation of government, an election year dummy, the ideological position of the

ECB Working Paper 1872, December 20157government, the ideological range of government) and demographic (population,
current and future age dependency) variables, as well as three EU/EMU/IMF
dummy variables (dummies for EU and EMU membership and a dummy for
IMF arrangements). Important macroeconomic variables, such as interest rates
or the debt level, have not been used as control variables in this setting as
they have been already directly included in the calculation of the ﬁscal space
measure. The political control variables capture the potential simultaneous im-
pact of voter preferences on ﬁscal space and ﬁscal rules and thus should reduce
endogeneity through a potential omitted variable bias. The data sources and
deﬁnitions of the variables can be found in Appendix A.1.
Furthermore, we include time (ηt) and country (μi) ﬁxed eﬀects and (cid:5)i,t is the
error term. We report standard errors which are robust to heteroskedasticity,
panel-speciﬁc autocorrelation and contemporaneous cross-sectional dependence
(i.e. Parks-Kmenta panel corrected standard errors as proposed in Beck and
Katz, 1995). Furthermore, we perform unit root/ stationarity tests on the vari-
ables included in the various estimations and take ﬁrst diﬀerences of the variables
where the null hypothesis of stationarity was rejected. We use ten year averages,
as newly established or strengthened ﬁscal rules might need some time to have
a signiﬁcant eﬀect on the credibility of public ﬁnances or the actual debt level.
We also did robustness checks using averages over shorter time periods which
however do not change the overall results (see Table A4 in Appendix A.5). The
coeﬃcient of the ﬁscal rule variable becomes smaller for averages with less years.
Moreover, shorter time period averages are driven by short-term factors like the
business cycle or macroeconomic shocks.
As shown in Table 1, ﬁscal rules seem to be strongly correlated with the size
of the available ﬁscal space of a country. If a country had a ﬁscal rule in place
for the past ten years the average ﬁscal space for those years is around 22% of
GDP higher. The coeﬃcient is proportional to the number of years in which
a ﬁscal rule has been in place. The coeﬃcients of the control variables are
in line with general expectations.
In fact, ﬁscal space seems to be higher in
countries that are more open and more conservative, have less fragmented and
more politically stable governments. Financial openness is associated with lower
ﬁscal space, which might be the case because governments are e.g. less able to
use tools of ”ﬁnancial repression” (see e.g. Reinhart, 2012).
The causality between ﬁscal rules and ﬁscal space could in principle work in both
directions. A country with either low or high ﬁscal space might have introduced
ﬁscal rules in order to either increase the ﬁscal space in the future or preserve
the good conditions. Nevertheless, the following two reasons let us suggest that
the causality is going from ﬁscal rules to ﬁscal space. First, there is usually a
signiﬁcant lag of several years between the politician’s decision to introduce a
ﬁscal rule and the rule entering into force. The same is true, when strengthening
ﬁscal rules. Like in other studies (e.g. de Haan et al., 2012) with annual data we
thus assume the endogeneity bias to be relatively small. Second, the estimated
coeﬃcients remain qualitatively the same when accounting for the potential
reverse causality of ﬁscal rules as demonstrated by e.g. Debrun et al. (2008)
using an instrumental variable estimation framework or Yeter and Heinemann

ECB Working Paper 1872, December 20158Table 1: Regression results - Determinants of Fiscal Space (10 year averages)

Fiscal Rule

Δ GDP per Capita

Δ Financial Openness

Trade Openness

Population

Age dependency

Future age dependency

Election Years

Ideology

Ideological Range

Government Fragmentation −1.70∗∗∗

IMF Arrangement

EU Membership

Eurozone Membership

N
Groups
R2

(0.34)
−0.13
(0.09)
−0.10
(0.07)
0.08∗
(0.04)

482
26
0.97

(1)
All
Rules
22.17∗∗∗
(3.19)
−0.07
(0.12)
−0.19∗∗∗
(0.05)
4.35∗∗∗
(1.34)
0.02∗∗
(0.01)
−0.04
(0.75)
1.12
(0.87)
−5.31
(4.37)
2.06∗∗∗
(0.73)
8.39∗∗∗
(1.07)

(2)
Balanced Budget
Rules
6.91∗∗
(3.02)
−0.13
(0.12)
−0.23∗∗∗
(0.05)
4.27∗∗∗
(1.34)
0.01
(0.01)
−0.23
(0.75)
0.95
(0.78)
−4.22
(4.31)
1.77∗∗
(0.71)
8.31∗∗∗
(1.16)
−1.44∗∗∗
(0.34)
−0.14
(0.09)
−0.10
(0.07)
0.04
(0.04)

482
26
0.97

(3)
Debt
Rules

−3.13
(5.47)
−0.16
(0.12)
−0.24∗∗∗
(0.05)
4.34∗∗∗
(1.35)
0.01
(0.01)
−0.19
(0.72)
0.74
(0.76)
−4.22
(4.40)
1.90∗∗∗
(0.70)
8.57∗∗∗
(1.15)
−1.42∗∗∗
(0.35)
−0.15
(0.09)
−0.09
(0.07)
0.02
(0.04)

482
26
0.97

(4)
Expenditure
Rules
43.27∗∗∗
(3.90)
−0.15
(0.10)
−0.15∗∗∗
(0.06)
4.39∗∗∗
(1.42)
0.02∗∗
(0.01)
−0.12
(0.73)
1.18
(0.69)
−4.99
(4.64)
1.98∗∗∗
(0.71)
8.22∗∗∗
(1.26)
−2.08∗∗∗
(0.34)
−0.11
(0.09)
−0.09∗
(0.06)
0.07∗
(0.04)

482
26
0.98

Notes: Dependent Variable is 10 year average of fiscal space. All variables are rolling averages of past 10 years.
Columns indicate different definitions of ”Fiscal Rule” variable. All regressions include time and country fixed
effects. Standard errors which are robust to heteroskedasticity, panel-specific autocorrelation and contempora-
neous cross-sectional dependence (i.e. Parks-Kmenta panel corrected standard errors as proposed in Beck and
Katz, 1995) are in parentheses. * indicate significance at 10% level, ** at 5% level and *** at 1% level.

(2014) using unexpected shocks as identiﬁcation strategy.
Moreover, the analysis shows that the coeﬃcient of ﬁscal rules also depends on
the type of ﬁscal rules in place. The strongest relationship can be attributed
to expenditure rules, followed by balanced budget rules, while debt rules seem
to be insigniﬁcant. Previous studies (e.g. Debrun et al. 2008 or Nerlich and
Reuter 2013) already highlighted the signiﬁcant eﬀect of balanced budget rules

ECB Working Paper 1872, December 20159Table 2: Regression results - Determinants of the Components of Fiscal Space

(Expenditure Rules, 10 year averages)

Fiscal Rule (Expenditure Rules)

Δ GDP per Capita

Δ Financial Openness

Trade Openness

Population

Age dependency

Future age dependency

Election Years

Ideology

Ideological Range

Government Fragmentation

IMF Arrangement

EU Membership

Eurozone Membership

N
Groups
R2

(3)
Debt
Level

(2)
(1)
Primary
Fiscal
Balance
Space
1.38∗∗∗ −10.62∗∗∗
43.27∗∗∗
(0.30)
(1.74)
(3.90)
−0.03∗∗∗ −0.06∗
−0.15
(0.03)
(0.01)
(0.10)
0.01∗∗∗
−0.15∗∗∗
0.02
(0.02)
(0.00)
(0.06)
0.02∗∗∗ −0.12∗∗
4.39∗∗∗
(0.05)
(1.42)
(0.01)
5.28∗
0.02∗∗ −0.57
(2.75)
(0.55)
(0.01)
0.00∗∗
0.00
−0.12
(0.00)
(0.00)
(0.73)
1.53∗∗∗
0.12∗∗∗
1.18
(0.27)
(0.05)
(0.69)
−0.65∗
−4.99
0.87
(1.60)
(0.34)
(4.64)
1.98∗∗∗
−0.39
0.04
(0.24)
(0.04)
(0.71)
−0.74∗
8.22∗∗∗
0.14∗
(0.44)
(0.08)
(1.26)
0.39∗∗∗
−2.08∗∗∗ −0.02∗∗
(0.07)
(0.01)
(0.34)
0.09∗∗
0.01∗
−0.11
(0.04)
(0.01)
(0.09)
0.07∗∗∗
0.02∗∗∗
−0.09∗
(0.00)
(0.06)
(0.02)
0.01∗∗∗ −0.03∗
0.07∗
(0.02)
(0.00)
(0.04)

(4)
Interest-
Growth-Diﬀ.
−1.41∗∗∗
(0.20)
−0.01
(0.01)
0.00
(0.01)
−6.08∗∗∗
(0.91)
2.22∗∗∗
(0.49)
0.00∗∗∗
(0.00)
−0.15∗∗∗
(0.05)
0.30
(0.34)
−0.12∗∗
(0.05)
−0.19∗∗∗
(0.07)
0.05∗∗
(0.02)
−0.02∗∗∗
(0.01)
0.02∗∗∗
(0.00)
0.00
(0.00)

482
26
0.98

548
26
0.54

550
26
0.94

405
26
0.92

Notes: Dependent Variable is 10 year average of variable indicated in top row. All variables are rolling averages
of past 10 years. The ”Fiscal Rule” variable is the Expenditure Rule variable. All regressions include time and
country fixed effects. Standard errors which are robust to heteroskedasticity, panel-specific autocorrelation and
contemporaneous cross-sectional dependence (i.e. Parks-Kmenta panel corrected standard errors as proposed
in Beck and Katz, 1995) are in parentheses. * indicate significance at 10% level, ** at 5% level and *** at 1%
level.

(and to a lesser extent debt rules) on public ﬁnances. Yet, they did not ﬁnd
signiﬁcant eﬀects for expenditure rules on public deﬁcits. This suggests that
while the positive association of balanced budget rules with ﬁscal space could
be mainly driven by their inﬂuence on the public balance, the link between ex-
penditure rules and ﬁscal space might be mainly due to higher credibility (as

ECB Working Paper 1872, December 201510usually expenditure ceilings are easier to monitor) and thereby lower interest
rate expenditures. To investigate this further, we look at the correlation of ex-
penditure rules with the diﬀerent components of ﬁscal space. The measure of
ﬁscal space is inﬂuenced by three main variables: the primary balance, the cur-
rent debt level and the interest-rate-growth-diﬀerential. To see how expenditure
rules are linked to ﬁscal space we perform the same regressions as in Equation
1 on the various components of ﬁscal space separately. As Table 2 shows, ex-
penditure rules seem on the one hand to be associated with a higher primary
balance and a lower (average) current debt level and on the other hand with a
lower (average) interest-rate-growth-diﬀerential. The latter could be assumed
to be driven by lower interest rates because of more trust and credibility of
ﬁscal policy. With respect to the relative importance of the three components
making up ﬁscal space, the strongest impact is likely to come from interest-
rate-growth-diﬀerentials. The reasoning behind is that the mean level of the
interest-rate-growth-diﬀerential is lower than that of the primary balance and
debt level. Thus in relative terms to the mean level the eﬀect of expenditure
rules seems to be strongest on the interest-rate-growth-diﬀerential.

4 Fiscal Rules, Fiscal Space and Discretionary

Fiscal Policy

After we found support for our assumption that ﬁscal rules are, in the long
run, linked to higher ﬁscal space of a country, we are in a next step interested
in the relationship of ﬁscal rules and discretionary ﬁscal policy variables in an
environment of high or low ﬁscal space. Both, ﬁscal space and ﬁscal rules are
often mentioned in relation to discretionary ﬁscal policy, as low ﬁscal space or
stringent ﬁscal rules should both set boundaries to the use of discretionary ﬁscal
policy.
To investigate the interplay of ﬁscal rules and ﬁscal space with the size of dis-
cretionary ﬁscal policy we estimate Equation (2) for the EU27 from 2004-2013:

EDisc

i,t = β1Si,t + β2Fi,t + β3Si,t · Fi,t + X (cid:2)

i,tγ + μi + ηt + (cid:5)i,t

(2)

We estimate the eﬀect of ﬁscal space Si,t, ﬁscal rules Fi,t, and the interaction
between the two Si,t · Fi,t, on various measures of discretionary ﬁscal policy
EDisc
of country i at time t. The latter include discretionary current expendi-
i,t
tures, discretionary capital expenditures and discretionary current revenues as
published in the AMECO database of the European Commission. Furthermore
we look at the aggregated discretionary ﬁscal eﬀort measure as published by
Carnot and de Castro (2015).4 We also include time (ηt) and country (μi) ﬁxed

4Carnot and de Castro (2015) use a ‘narrative’, bottom-up approach to determine the
discretionary revenues which are not associated with the business cycle (new tax measures)
and use a top-down approach to calculate discretionary expenditures, by adjusting the tradi-
tional structural balance for removing items that are out of government’s control in the short
term and using a smoother deﬁnition of potential growth. Both, discretionary revenues and
expenditures, calculated in this way, taken together represent the ”discretionary ﬁscal eﬀort”.

ECB Working Paper 1872, December 201511eﬀects and calculate errors (cid:5)i,t which are robust to heteroskedasticity, panel-
speciﬁc autocorrelation and contemporaneous cross-sectional dependence (i.e.
Parks-Kmenta panel corrected standard errors as proposed in Beck and Katz,
1995).
The set of control variables Xi,t is composed of standard determinants in the
literature on ﬁscal reaction functions. Additionally to the political, demographic
and dummy variables5 already used in Equation 1 in Section 3, we include
several economic variables (the debt level of the previous period, the output
gap of the previous period, and the unemployment rate of the previous period)
to capture annual changes in the data. The data sources and deﬁnitions of the
variables can be found in Appendix A.1.
The estimation results of Equation (2) are presented in Table 3. The main re-
sults are overall in line with intuition: Countries with more ﬁscal space tend to
have higher current discretionary expenditures, less discretionary revenues and
thus overall a lower discretionary ﬁscal eﬀort. Current discretionary expendi-
tures are by 0.91 % of GDP higher if the ﬁscal space of a country were to be
increased by 100 percentage points. However, if governments have ﬁscal rules in
place, the results suggest that governments can no longer fully use their ﬁscal
space and (on average) are even forced to reduce their current expenditures or
increase their revenues. Likewise for the ﬁscal eﬀort, the results show a signif-
icant relationship. We do not ﬁnd any signiﬁcant link of ﬁscal rules and ﬁscal
space with discretionary capital expenditures.
If the ﬁscal space is zero, for
example following a sharp increase in actual debt or a conﬁdence crisis lowering
the debt limit, then countries with ﬁscal rules would tend to have higher discre-
tionary current expenditures and lower revenues compared to countries without
ﬁscal rules. But as we have in our sample almost no observations with ﬁscal
space that is zero, this is only a theoretical consideration.
As in Section 3 an endogeneity bias can not be excluded, as causality could also
run from discretionary public expenditures (revenues) to either ﬁscal rules or
ﬁscal space. Again, for the reasons mentioned in Section 3 above, we assume
the bias to be relatively small regarding ﬁscal rules. Regarding ﬁscal space, we
recognise that there could be reverse causality, as lower discretionary expendi-
tures (higher discretionary revenues) might lead to higher ﬁscal space. Thus
our results need to be interpreted with caution. Nevertheless, our ﬁscal space
variable is deﬁned in a way that the expenditures (revenues) of one year do only
have a very minor impact on the level of the ﬁscal space variable. In our case,
ﬁscal space is rather determined by averages of growth and interest rates, the
reaction of ﬁscal policy to debt levels, etc. over a longer time period.
To check the robustness of our main ﬁndings we perform several additional
exercises, some of which are presented in Table A5 in Appendix A.6. Overall
the results stay qualitatively the same. For example, we do robustness checks
without any control variables, or without ﬁxed eﬀects. When looking at the
diﬀerent types of ﬁscal rules the strongest association with discretionary ﬁscal

5We do not use a EU or EMU membership dummy anymore, as those are constant for

most countries over the shorter sample period (2004-2013).

ECB Working Paper 1872, December 201512Table 3: Regression results (Dependent variable: measures of discretionary ﬁscal

policy)

(1)

Fiscal
Eﬀort
−3.39∗∗∗
(0.42)
−4.50∗∗∗
(1.12)
1.28∗∗∗
(0.37)
−0.22
(1.35)
0.07
(0.04)
−0.04
(0.05)
0.13
(0.28)
0.15∗∗
(0.07)
−0.01
(0.11)
−0.17
(0.16)
0.09∗∗
(0.05)
−0.19∗∗
(0.08)
4.52
(3.49)
1.47∗∗∗
(0.40)

246
27
0.46

Fiscal Space

Fiscal Rule

Fiscal Space x Fiscal Rule

Debt (-1)

Output Gap (-1)

Unemployment (-1)

Population

Age dependency

Future age dependency

Election Year

Ideology

Ideological Range

Government Fragmentation

IMF Arrangement

N
Groups
R2

(3)
Discr.
Capital

(2)
Discr.
Current

(4)
Discr.
Current
Expenditures Expenditures Revenues
−1.34∗∗∗
(0.44)
−2.77∗∗
(1.10)
0.77∗
(0.43)
1.62∗∗
(0.82)
0.06∗
(0.03)
0.00
(0.03)
0.36
(0.22)
0.02
(0.07)
0.11∗
(0.06)
−0.15∗
(0.08)
0.00
(0.02)
0.00
(0.06)
2.45
(1.81)
0.61∗
(0.35)

0.91∗∗
(0.43)
3.13∗∗∗
(1.00)
−1.27∗∗∗
(0.40)
−0.28
(0.87)
0.01
(0.03)
−0.06∗∗
(0.02)
−0.53∗∗
(0.25)
−0.12
(0.07)
−0.16∗∗∗
(0.04)
0.20∗∗
(0.08)
−0.01
(0.04)
0.02
(0.08)
−1.71
(2.15)
−1.14∗∗∗
(0.35)

−2.01
(0.01)
0.10
(2.05)
0.20
(1.16)
−9.65
(7.16)
−0.02
(0.05)
0.07
(0.11)
0.92
(0.59)
−0.12
(0.18)
0.43∗∗
(0.21)
−0.20
(0.31)
−0.14
(0.10)
0.37
(0.25)
−7.51∗
(4.43)
−0.30
(1.03)

162
27
0.72

162
27
0.23

162
27
0.68

Notes: Dependent Variable is discretionary fiscal effort from Carnot and de Castro (2015) (Column 1), dis-
cretionary current expenditures (Column 2), capital expenditures (Column 3) and revenues (Column 4) in
percentage of GDP. Fiscal Rule variable refers to all fiscal rules. All regressions include time and country fixed
effects. Standard errors which are robust to heteroskedasticity, panel-specific autocorrelation and contempora-
neous cross-sectional dependence (i.e. Parks-Kmenta panel corrected standard errors as proposed in Beck and
Katz, 1995) are in parentheses. * indicate significance at 10% level, ** at 5% level and *** at 1% level.

policy can be attributed to balanced budget rules, followed by expenditure rules
(this also underlines that the strong link of expenditure rules with ﬁscal space
found in Section 3 can be attributed mainly to the eﬀect on trust, credibility
and lower interest rates). Yet, debt rules again do not seem to yield a signiﬁcant

ECB Working Paper 1872, December 201513coeﬃcient.
As further robustness checks, we performed several tests including squared or
cubic versions of the ﬁscal space variable, but the additions were neither sig-
niﬁcant nor did they change the baseline results.6 Moreover, we replicated the
exercise with diﬀerent thresholds of ﬁscal space and split the ﬁscal space vari-
able at various levels. Table A6 in the Appendix shows some of the results for
the ﬁscal space and ﬁscal rule coeﬃcients using the variables split at diﬀerent
ﬁscal space thresholds. In fact this conﬁrms our main results, as we can see that
the correlation with ﬁscal space becomes stronger the less ﬁscal space a country
has and the correlation with ﬁscal rules is more signiﬁcant the higher the ﬁscal
space variable is.

5 Fiscal Rules, Fiscal Space and Procyclicality

of Fiscal Policy

In the following section we aim to contribute to the question whether ﬁscal rules
and ﬁscal space are procyclical. Our results so far showed that discretionary
expenditures are associated with higher ﬁscal space, but that this positive link is
reduced if ﬁscal rules are in place. This could be interpreted as ﬁscal rules having
a dampening impact on discretionary expenditures, which, if those expenditures
are used with the cycle, is an indication that they might help to limit the
procyclicality of ﬁscal policy. Therefore, we investigate this further by analysing
the relation between ﬁscal rules and ﬁscal space with the procyclicality of ﬁscal
policy.
To test this in a controlled environment we estimate the following Equation 3:

ˆσi,t = β1Si,t + β2Fi,t + β3Si,t · Fi,t + X (cid:2)

i,tγ + μi + ηt + εi,t

(3)

where the dependent variable (ˆσi,t) is a measure of the procyclicality of ﬁscal
policy, explained below in Equation (4), in a ten-year rolling window, Si,t the
average ﬁscal space over the same period and Fi,t the percentage of years in
which a ﬁscal rule is in place during the last ten years. Furthermore, we include
the interaction between ﬁscal space and ﬁscal rules to test for the dampening
eﬀect of ﬁscal rules in a combination of both. A set of control variables Xi,t is in-
cluded, as well as time (ηt) and country (μi) ﬁxed eﬀect. The standard errors (cid:5)i,t
are robust to heteroskedasticity, panel-speciﬁc autocorrelation and contempora-
neous cross-sectional dependence (i.e. Parks-Kmenta panel corrected standard
errors as proposed in Beck and Katz, 1995).
The control variables Xi,t, all expressed in ten-year averages, are in line with
those used in the literature. They consist of the economic, demographic, polit-
ical and dummy variables already used in Equation 1 in Section 3. The data
sources and deﬁnitions of the variables can be found in Appendix A.1.

6The results are not reported here, but can be obtained from the authors upon request.

ECB Working Paper 1872, December 201514Table 4: Regression results - Procyclicality of ﬁscal policy (10 year rolling window)

Population

Fiscal Rule

Fiscal Space

Trade Openness

Δ GDP per Capita

Δ Financial Openness

Fiscal Space x Fiscal Rule

(1)
All
Rules
0.30∗∗∗
(0.09)
0.03∗∗∗
(0.01)
−0.27∗∗∗
(0.09)
−0.13∗∗
(0.05)
−0.01
(0.20)
0.14∗∗∗
(0.03)
−0.15
(0.20)
−0.33∗∗∗
(0.13)
−0.29
(0.22)
−0.03
(0.02)
0.16
(0.11)
0.30
(0.32)
Government Fragmentation −1.10
(0.79)
0.05
(0.13)
−0.09
(0.14)
−0.13
(0.10)

Future age dependency

Eurozone Membership

IMF Arrangement

Ideological Range

Age dependency

EU Membership

Election Years

Ideology

(2)
Balanced
Budget Rules
0.22∗∗
(0.09)
0.03∗∗
(0.01)
−0.14∗∗
(0.06)
−0.12∗∗
(0.06)
−0.01
(0.20)
0.15∗∗∗
(0.03)
−0.18
(0.22)
−0.27∗∗
(0.13)
−0.19
(0.21)
−0.03
(0.02)
0.11
(0.11)
0.15
(0.30)
−1.27
(0.80)
0.10
(0.14)
−0.09
(0.14)
−0.11
(0.09)

N
Groups
R2

374
26
0.352

374
26
0.343

(3)
Debt
Rules
0.16∗∗
(0.07)
−0.02
(0.03)
0.01
(0.15)
−0.13∗∗
(0.06)
−0.01
(0.20)
0.15∗∗∗
(0.03)
−0.05
(0.19)
−0.31∗∗
(0.13)
−0.17
(0.21)
−0.03
(0.02)
0.14
(0.11)
0.23
(0.34)
−1.13
(0.78)
0.04
(0.16)
−0.09
(0.15)
−0.10
(0.10)

374
26
0.335

(4)
Expenditure
Rules
0.24∗∗
(0.11)
0.04∗∗∗
(0.01)
−0.30∗∗∗
(0.11)
−0.12∗∗
(0.06)
0.02
(0.20)
0.15∗∗∗
(0.03)
−0.27
(0.19)
−0.33∗∗∗
(0.12)
−0.27
(0.22)
−0.03
(0.02)
0.14
(0.11)
0.15
(0.31)
−1.28
(0.79)
0.10
(0.14)
−0.13
(0.14)
−0.10
(0.09)

374
26
0.348

Notes: Dependent Variable is procyclicality of fiscal policy. Columns indicate different definitions of ”Fiscal
Rule” variable. Standard errors which are robust to heteroskedasticity, panel-specific autocorrelation and
contemporaneous cross-sectional dependence (i.e. Parks-Kmenta panel corrected standard errors as proposed
in Beck and Katz, 1995) are in parentheses. All regressions include time and country fixed effects. * indicate
significance at 10% level, ** at 5% level and *** at 1% level.

To calculate the procyclicality of ﬁscal policy we rely on a framework similar to
the one used in Fat´as and Mihov (2003), Alesina et al. (2002) and Blanchard

ECB Working Paper 1872, December 201515and Perotti (2002):

log(G)i,t = αi + σiΔlog(Yi,t) +ψ ilog(Gi,t−1) +δ iWi,t + νi,t

(4)

where Gi,t are the real general government total expenditures, Yi,t the real
GDP, and Wi,t includes several control variables (current and lagged oil price,
current inﬂation rate and linear time trend). The current real output growth is
instrumented by past values of output growth to avoid the potential endogeneity.
The estimates of σi represent the procyclicality of ﬁscal policy.
The results for estimating Equation (3) are presented in Table 4: the regression
results for our measure of procyclicality (ˆσi,t in Equation 3) show that an in-
crease in ﬁscal space indeed seems to be associated with ﬁscal policy being more
procyclical. Yet if ﬁscal rules are in place, this positive link seems to be signiﬁ-
cantly smaller. Moreover, we estimated Equation (3) for diﬀerent kinds of ﬁscal
rules, with the results shown in the columns (2) to (4) of Table 4. We ﬁnd that
both, balanced budget rules (Column 2) and expenditure rules (Column 4), are
correlated with a lower coeﬃcient for ﬁscal space on procyclicality. This is in
line with our ﬁndings above that expenditure rules might restrict discretionary
expenditures. We do not ﬁnd signiﬁcant results for debt rules.
To check the robustness of our ﬁndings we conducted various robustness checks,
such as estimating Equation (3) without control variables (see Table A7 in Ap-
pendix A.8), excluding country and time ﬁxed eﬀects, and using 15-year instead
of 10-year averages. Overall we ﬁnd qualitatively the same results independently
of the econometric setting used.

6 Conclusions

This paper analyses the interaction of ﬁscal rules and ﬁscal space. We calculate
the ﬁscal space, based on the deﬁnition of Ghosh et al. (2013), for 27 EU member
states for the period 1990-2014. In diﬀerent econometric settings we estimate
the link between ﬁscal rules and ﬁscal space as well as their interaction with
discretionary ﬁscal policy and its procyclicality.
We ﬁnd that ﬁscal rules are signiﬁcantly linked to higher ﬁscal space, which
suggests that ﬁscal rules help to increase ﬁscal space. Furthermore, the analysis
shows that high ﬁscal space is associated with increased discretionary expen-
ditures, but that this positive link is signiﬁcantly reduced if ﬁscal rules are in
place. This could be interpreted such that ﬁscal space makes ﬁscal policy more
procyclical while ﬁscal rules seem to counteract this procyclicality. The results
indeed suggest that the link between ﬁscal space and procyclical ﬁscal policy
is lower if ﬁscal rules are in place. Regarding the diﬀerent types of ﬁscal rules,
we ﬁnd strong results for expenditure rules and to a lesser extent for balanced
budget rules, but none for debt rules.
This paper should be seen as a start of a more in-depth investigation into the
interplay of ﬁscal space and ﬁscal rules. Further research could concentrate on
the various channels driving our overall results and a more detailed analysis of
the speciﬁcs of ﬁscal rules which drive these results. Another potential avenue

ECB Working Paper 1872, December 201516of future research could be to estimate the uncertainty around the ﬁscal space
measure, as demonstrated in Ghosh et al. (2013), and how this would aﬀect the
overall results.

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ECB Working Paper 1872, December 201519A Appendix

A.1 Data Sources

Variable Name

Age dependency

Debt
Discr. capital expenditures
Discr. current expenditures
Discr. current revenues
Election Year
EU Membership
Eurozone Membership

Financial Openness

Fiscal eﬀort

Fiscal Rule

Future age dependency

GDP per Capita

Gov. expenditure gap

Government Fragmentation

Ideology

Table A1: Data Sources

Description

Source

UN (dependency ratio,
Ratio of population below 15 plus population above 64
medium variant)
to population between 15 and 64
AMECO (UDGGL)
General government gross debt
AMECO (UDMGKE)
Discretionary measures capital expenditure
AMECO (UDMGCE)
Discretionary measures current expenditure
AMECO (UDMGCR)
Discretionary measures current revenue
1 if there was election of legislative in respective year
DPI (legelec)
1 if country is member state of the EU in respective year Authors input
Authors input
1 if country is member state of the Eurozone in respective
year
Chinn-Ito index measuring capital account openness

Discretionary measures (expenditures and revenues)

1 if ﬁscal rule of speciﬁc type was in place in respective
year
Same as age dependency, but projections for 20 years
ahead
Ratio of nominal GDP to population

Diﬀerence between actual real government consumption
and potential (calculation using HP ﬁlter)
probability that two randomly picked members of gov-
ernment are of diﬀerent parties
Sum of two main parties in government: 4 points for
right party, 2 points for middle party and 0 for left

Chinn and Ito (2006),
updated version
Carnot and de Castro
(2015)
Authors database, Ta-
ble A2
UN (dependency ratio,
medium variant)
AMECO
NPTN)
Author calculations us-
ing AMECO (UCTG0)
DPI (govfrac)

(UVGD,

calculations
(gov1rlc,

calculations
(gov1rlc,

Author
using DPI
gov2rlc)
Author
using DPI
gov2rlc, gov3rlc)
IMF History of Lend-
ing
Arrangements
database
Author calculations us-
ing AMECO (ZCPIN)
IMF Primary Com-
modity Prices
Author calculations us-
ing AMECO (OVGD)
AMECO (NPTN)
AMECO
DXGT, UVGD)

(DMGT,

Ideological Range

Coding as in ”Ideology” but diﬀerence between maxi-
mum and minimum score in government

IMF Arrangement

1 if country had IMF support program in given year

Inﬂation (Average)

Three year average of past inﬂation rates

Oil Price

Output Gap

Population
Trade Openness

Average of monthly oil price, only for oil exporters

Diﬀerence between actual real GDP and potential (cal-
culation using HP ﬁlter)
Total population
Share of exports plus imports to nominal GDP

Notes: AMECO: Annual macro-economic database of the European Commission, Vintage Autumn 2014; DPI: World Bank, Database
of Political Institutions, Beck et al. (2001); UN: United Nations Population Divisions, World Population Prospects.

ECB Working Paper 1872, December 201520A.2 Dataset on national numerical ﬁscal rules

Table A2: National numerical ﬁscal rules

Ctry Numerical Fiscal Rule

Ctry Numerical Fiscal Rule

Ctry Numerical Fiscal Rule

AT

BE

BBR, GG, LC, NSCM (08-10)
BBR, GG, LC, SCM (11-14)
BBR, CG, LC, NSCM (99-04)
BBR, CG, LC, SCM (05-12)
BBR, RLG, LC, NSCM (99-04)
BBR, RLG, LC, SCM (05-12)
DR, GG, LC, SCM (14)
ER, GG, LC, NSCM (09-14)
BBR, RLG, LC, NSCM (82-14)
DR, GG, PC, NSCM (14)
RR, CG, PC, NSCM (95-99)
ER, CG, PC, NSCM (93-98)

BG BBR, GG, LC, NSCM (12-14)

CY

BBR, GG, LC, NSCM (14)
BBR, GG, PC, NSCM (06-11)
DR, GG, LC, NSCM (03-14)
RR, GG, LC, NSCM (14)
ER, GG, LC, NSCM (12-14)
ER, GG, PC, NSCM (06-11)
ER, GG, LC, NSCM (14)
DR, GG, LC, NSCM (14)
BBR, GG, LC, NSCM (14)
ER, CG, LC, NSCM (05-14)
BBR, CG, LC, NSCM (69-10)
BBR, CG, LC, SCM (11-14)
BBR, GG, LC, SCM (13-14)
BBR, LRG, LC, SCM (90-14)
BBR, SS, LC, SCM (09-12)
ER, CG, PC, NSCM (82-12)
ER, RLG, PC, NSCM (82-12)
DK BBR, GG, PC, NSCM (92-13)

CZ
DE

EE

ES

BBR, GG, LC, NSCM (14)
RR, GG, PC, NSCM (01-11)
ER, GG, PC, NSCM (94-12)
ER, CG, LC, SCM (14)
BBR, GG, LC, NSCM (14)
BBR, GG, PC, NSCM (93-13)
DR, RLG, LC, NSCM (97-12)
DR, RLG, LC, SCM (13-14)
BBR, GG, LC, SCM (03-05)
BBR, GG, LC, NSCM (06-09)
BBR, GG, LC, SCM (10-14)
ER, CG, LC. NSCM (11-14)
ER, RLG, LC, NSCM (11-14)

FI

FR

HU

IE

IT

LT

LU

PT

NL

PL

BBR, RLG, LC, NSCM (95-13) LV
BBR, GG, LC, NSCM (14)
BBR, CG, PC, NSCM (99-13)
RR, CG, PC, NSCM (14)
DR, CG, PC, NSCM (95-07)
DR, CG, PC, NSCM (11-14)
ER, CG, PC, NSCM (03-14)
BBR, RLG, LC, NSCM (83-13)
BBR, GG, LC, SCM (13-14)
RR, CG, LC, NSCM (06-14)
DR, GG, LC, SCM (14)
DR, SS, LC, NSCM (08-12)
ER, CG, PC, NSCM (98-10)
ER, CG, LC, NSCM (11-14)
ER, SS, LC, NSCM (06-12)
ER, SS, PC, NSCM (97-05)
BBR, GG, LC, NSCM (04-09)
BBR, CG, LC, NSCM (10-11)
BBR, SS, LC, NSCM (10-11)
ER, CG, LC, NSCM (10-11)
ER, SS, LC, NSCM (10-11)
DR, GG, LC, NSCM (10-14)
DR, CG, LC, NSCM (09-11)
DR, SS, LC, NSCM (09-11)
BBR, RLG, PC, SCM (04-12)
BBR, GG, LC, SCM (13-14)
DR, GG, LC, SCM (13-14)
ER, GG, LC, SCM (14)
ER, CG, LC, NSCM (00-09)
ER, CG, LC, SCM (10-13)
BBR, RLG, LC, SCM (01-14)
BBR, GG, LC, NSCM (14)
DR, GG, LC, NSCM (14)
ER, CG, LC, SCM (01-07)
ER, GG, LC, NSCM (14)
ER, RLG, LC, SCM (99-14)
BBR, RLG, LC, SCM (90-12)
BBR, GG, LC, NSCM (14)
RR, CG, LC, SCM (08-12)
DR, CG, LC, NSCM (97-14)
ER, CG, LC, NSCM (08-14)
DR, GG, PC, NSCM (04-14)
ER, CG, PC, NSCM (90-14)

SE

SI

SK

RO BBR, GG, LC, NSCM (10-14)

BBR, GG, LC, NSCM (12)
BBR, GG, LC, SCM (13-14)
RR, CG, LC, NSCM (12-14)
DR, GG, LC, NSCM (12-14)
ER, GG, LC, NSCM (12-14)
RR, GG, PC, NSCM (94-14)
BBR, GG, LC, NSCM (14)
ER, GG, PC, NSCM (94-14)
BBR, CG, PC, SCM (06-07)
DR, GG, LC, SCM (97-14)
ER, GG, LC, NSCM (14)
ER, CG, LC, SCM (11-13)
BBR, GG, LC, NSCM (12-14)
BBR, CG, LC, NSCM (02-11)
BBR, RLG, LC, NSCM (03-06)
BBR, RLG, LC, SCM (07-11)
ER, CG, LC, NSCM (12-14)

DR, GG, LC, NSCM (14)
ER, GG, LC, SCM (10-14)
BBR, GG, LC, NSCM (07-14)
BBR, LRG, LC, NSCM (00-14)
BBR, GG, PC, NSCM (00-06)
ER, CG, LC, SCM (10-14)
ER, CG, PC, SCM (97-09)
ER, SS, LC, SCM (10-12)
ER, SS, PC, SCM (97-09)
DR, RLG, LC, NSCM (-90-14)
DR, GG, PC, NSCM (00-04)
BBR, GG, LC, NSCM (14)
ER, GG, LC, NSCM (11-14)
BBR, RLG, LC, SCM (02-08)
BBR, RLG, LC, NSCM (09-13)
BBR, GG, LC, NSCM (14)
DR, GG, LC, NSCM (12-14)
DR, RLG, LC, SCM (02-14)
ER, CG, LC, SCM (02-14)

UK BBR, GG, LC, SCM (97-08)

BBR, GG, LC, NSCM (10-14)
DR, GG, LC, SCM (97-08)
DR, GG, LC, NSCM (10-14)

GR None
MT None

Notes: BBR: Balanced Budget Rule, DR: Debt Rule, ER: Expenditure Rule, RR: Revenue Rule; GG: General
Government, CG: Central Government, RLG: Regional or Local Government, SS: Social Security; LC: Law or
Constitution, PC: Political or Coalitional Agreement; [N]SCM: [no] (possibility of) sanctions and/or automatic
correction mechanism. Years the rule has been in place are stated in brackets.

ECB Working Paper 1872, December 2015214
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ECB Working Paper 1872, December 201522A.4 Calculation of ﬁscal space

When calculating the ﬁscal space of a country we follow almost exactly the
approach described in Ghosh et al. (2013). As this paper should not be about
the deﬁnition of ﬁscal space, we refrain from changing the estimation setting or
data and try to replicate the calculations as closely as possible. For Ghosh et al.
(2013) ﬁscal space is deﬁned as the scope for further increases in public debt
without undermining the sustainability of debt. They calculate a debt limit
assuming that the public balance reacts to diﬀerent levels of debt diﬀerently.
Fiscal space is then the diﬀerence between the current debt level and the debt
limit. Ghosh et al. (2013) calculate the ﬁscal space for 23 advanced countries
for the year 2015.
As Ghosh et al. (2013) we ﬁrst estimate a ﬁscal reaction function for our sample
of 27 EU member states (1985-2013) of the following form:

P Bi,t = β1Di,t−1 + β2D2

i,t−1 + β3D3

i,t−1 + X (cid:2)

i,tγ + μi + (cid:5)i,t

(5)

where the primary balance P Bi,t of country i at time t is the dependent variable
and the main focus is to estimate the reaction of this primary balance on the
debt level of the previous period (Di,t−1). To allow for diﬀerent shapes of the
reaction curve also the squared and cubic terms are included, as well as country
ﬁxed eﬀect μi. The error term (cid:5)i,t is assumed to follow an AR(1) process.
To control for other inﬂuences on the primary balance the following set of con-
trol variables Xi,t is included: i) output gap; ii) government expenditure gap;
iii) trade openness; iv) inﬂation (as average over the past three years); v) age
dependency; vi) future age dependency; vii) oil price (only for oil exporters);
viii) political stability; ix) IMF arrangement and x) ﬁscal rules (as published in
the IMF data set and being one if country had at least any of the diﬀerent na-
tional rules7). The original study by the IMF (Ghosh et al., 2013) also included
nonfuel commodity price for non-oil commodities exporters, but exclude this
variable as the countries in our sample (EU27) are not big exporters of nonfuel
commodities and those exports do not make up a large share of tax revenues.
Table A3 shows the respective results (Column 1) and for comparison the results
published in Ghosh et al. (2013) (Column 3). Overall the signiﬁcance and size
of the coeﬃcients of various variables is comparable to the IMF estimations,
but diﬀerences emerge. In the IMF estimation the oil price is signiﬁcant and
future age dependency is not, which is the opposite in our case. The same is
true for the variables political stability and IMF arrangements. Furthermore,
the debt coeﬃcients have a higher signiﬁcance in our estimations, but the size
of the lagged debt squared variable decreased a bit. Overall our signiﬁcantly
higher R2 suggests that the estimation has a better ﬁt in our more homogenous
sample of EU27 countries.

7We do not use our data set of ﬁscal rules in this calculations to recreate the estimations of
(Ghosh et al., 2013) as closely as possible. Nevertheless, as a robustness check (see Column 2
in Table A3), we used our ﬁscal rules data instead of the IMF data and received quantitatively
almost exactly the same results.

ECB Working Paper 1872, December 201523Table A3: Regression results (Dependent variable: Primary balance to GDP)

(1)

(2)

(3)

Own estimation Own estimation Ghosh et al. (2013)

(1985-2013)
EU27

(1985-2013)
EU27

(1985-2007)
23 countries

Lagged debt

Lagged debt squared

Lagged debt cubic

Output Gap

Gov. Expenditure Gap

Trade Openness

Inﬂation (Average)

Age dependency

Future age dependency

Oil price (for oil exporters)

Political Stability

IMF arrangement

Fiscal Rules (IMF dataset)

Fiscal Rules (Own dataset)

Nonfuel Commodity price

−0.009
(0.042)
0.0012∗∗
(0.001)
−0.00001∗∗
(2.2e−06)
0.317∗∗∗
(0.022)
−0.354∗∗∗
(0.013)
0.011
(0.006)
−1.526
(3.660)
0.124∗∗
(0.060)
−0.218∗∗∗
(0.034)
0.003
(0.006)
3.847
(2.735)
−1.109∗∗∗
(0.328)
0.346
(0.290)

N
Groups
R2 (within)
AR(1) coeﬃcient

591
27
0.619
0.673

−0.005
(0.042)
0.0012∗∗
(0.001)
−0.00001∗∗
(2.2e−06)
0.320∗∗∗
(0.022)
−0.355∗∗∗
(0.013)
0.011
(0.008)
−1.881
(3.660)
0.124∗∗
(0.060)
−0.197∗∗∗
(0.036)
0.003
(0.006)
3.757
(2.735)
−1.103∗∗∗
(0.328)

0.305
(0.309)

591
27
0.618
0.672

−0.086
(0.070)
0.0017∗
(0.001)
−0.00001∗∗
(3.0e−06)
0.441∗∗∗
(0.053)
−0.183∗∗∗
(0.047)
0.146∗∗∗
(0.054)
4.620∗∗
(2.008)
−0.072
(0.101)
−0.015
(0.067)
9.529∗∗∗
(3.244)
0.068∗∗
(0.030)
−1.142
(0.999)
0.300
(0.347)

3.005
(8.362)

491
23
0.405
0.749

Notes: Dependent Variable is general government primary public balance in percentage of GDP. Country fixed
effects are included but not reported. Error term assumed to follow AR(1) process. Heteroscedasticity robust
standard errors are in parentheses. * indicate significance at 10% level, ** at 5% level and *** at 1% level.

After obtaining the coeﬃcients of the ﬁscal reaction function, we calculate the
interest rate-growth rate diﬀerentials for each of the countries and years. As in
one of the ”historical market approaches” by Ghosh et al. (2013) we calculate
the average of the implied nominal interest rate on government debt (share of

ECB Working Paper 1872, December 201524interest expenditures to debt at end of period), ii,t, and the average of the
growth rate of nominal GDP (over the past ten years), gi,t.
To calculate the debt limit, ¯Di,t, for each country i and time period t, we
calculate the largest root of the following equation:

(ii,t − gi,t) ¯Di,t = β1 ¯Di,t + β2 ¯D2

i,t + β3 ¯D3

i,t + φi

(6)

where β1, β2 and β3 are the coeﬃcients estimated by Equation 5. φi is the part
independent from the debt level and time (including the country ﬁxed constant)
for each country from Equation 5 assuming that the output gap and government
expenditure gap are closed.
Finally ﬁscal space Si,t for country i at time period t is deﬁned as the diﬀerence
between the debt limit at time t and the actual level of debt in the same time
period. If this diﬀerence is negative then ﬁscal space is assumed to be zero:

Si,t = max ( ¯Di,t − Di,t, 0)

(7)

Ghosh et al. (2013) also report estimates of ﬁscal space (based on the ”his-
torical market approach”) for the countries in their sample for the year 2015.
When comparing those values with the last observations of our ﬁscal space es-
timates (14 countries are included in both samples) we ﬁnd a convincingly high
correlation of 0.83 and an average absolute deviation of 22% of GDP.

ECB Working Paper 1872, December 201525A.5 Robustness: Fiscal Space and Fiscal Rules

Table A4: Regression results (All ﬁscal rules, Dependent variable: Fiscal Space)

Population

Age dependency

(0.04)
57.10∗∗∗
(14.22)

(0.03)
35.36∗∗∗
(12.16)

(4)
3 year
averages
14.00∗∗∗
(3.90)
0.18∗∗
(0.08)

(3)
5 year
averages
18.36∗∗∗
(4.58)
0.29∗∗∗
(0.09)

(2)
7 year
averages
22.86∗∗∗
(3.72)
0.30∗∗∗
(0.10)

Fiscal Rule

Δ GDP per Capita

Δ Financial Openness

Trade Openness

(1)
10 year
averages
22.17∗∗∗
(3.19)
−0.07
(0.12)
−0.19∗∗∗ −0.15∗∗∗ −0.16∗∗∗ −0.09∗∗∗
(0.05)
4.35∗∗∗
(1.34)
0.02∗∗
(0.01)
−0.04
(0.75)
1.12
(0.87)
−5.31
(4.37)
2.06∗∗∗
(0.73)
8.39∗∗∗
(1.07)

0.03∗∗∗
(0.01)
−1.43
(1.05)
1.52
(1.06)
−1.14
(3.16)
0.28
(0.44)
4.67∗∗∗
(0.81)
Government Fragmentation −1.70∗∗∗ −1.37∗∗∗ −0.53∗∗
(0.24)
−0.22∗∗∗ −0.23∗∗∗
(0.06)
−0.10
(0.071)
0.11∗∗
(0.05)

(0.04)
43.62∗∗∗
(7.26)
0.02∗∗∗
(0.01)
−0.61
(0.96)
−0.69
(0.86)
−4.72
(4.04)
1.35∗∗∗
(0.49)
6.63∗∗∗
(0.92)

0.03∗∗∗
(0.01)
−0.79
(1.13)
3.28∗∗
(1.33)
−1.73
(2.18)
−0.06
(0.39)
4.37∗∗∗
(0.68)
−0.09
(0.19)

(0.34)
−0.13
(0.09)
−0.10
(0.07)
0.08∗
(0.04)

(0.28)
−0.13∗
(0.07)
−0.11
(0.07)
0.03
(0.05)

(0.05)
−0.04
(0.07)
0.14∗∗∗
(0.05)

Future age dependency

Eurozone Membership

IMF Arrangement

Ideological Range

EU Membership

Election Years

Ideology

N
Groups
R2

482
26
0.97

482
26
0.96

482
26
0.93

482
26
0.91

Notes: Dependent Variable is fiscal space. All variables are rolling averages of past years as indicated on top of
columns. Fiscal Rule variable referes to all fiscal rules. All regressions include time and country fixed effects.
Standard errors which are robust to heteroskedasticity, panel-specific autocorrelation and contemporaneous
cross-sectional dependence (i.e. Parks-Kmenta panel corrected standard errors as proposed in Beck and Katz,
1995) are in parentheses. * indicate significance at 10% level, ** at 5% level and *** at 1% level.

ECB Working Paper 1872, December 201526A.6 Robustness: Fiscal Rules, Fiscal Space and Discre-

tionary Fiscal Policy

Table A5: Regression results (dependent variable: discretionary ﬁscal eﬀort)

Fiscal Space

Fiscal Rule

Fiscal Space x Fiscal Rule

Debt (-1)

Output Gap (-1)

Unemployment (-1)

Population

Age dependency

Future age dependency

Election Year

Ideology

Ideological Range

Government Fragmentation

IMF Arrangement

Balanced Debt Expenditure

(4)

(5)

(6)

Rules

(3)
No

(2)
No

(0.31)

(0.50)

(0.52)

(1.50)
1.07∗∗
(0.49)

controls ﬁxed eﬀects Budget R. Rules

(1)
All
Rules
−3.39∗∗∗ −2.96∗∗∗ −2.70∗∗∗ −3.09∗∗∗ −2.12∗∗∗ −3.03∗∗∗
(0.42)
−4.50∗∗∗ −3.97∗∗∗ −2.47∗∗∗ −3.49∗∗∗
(1.12)
1.28∗∗∗
(0.37)
−0.22
(1.35)
0.07
(0.04)
−0.04
(0.05)
0.13
(0.28)
0.15∗∗
(0.07)
−0.01
(0.11)
−0.17
(0.16)
0.09∗∗
(0.05)
−0.19∗∗
(0.08)
4.52
(3.49)
1.47∗∗∗
(0.40)

(0.34)
0.21
(1.02)
(0.96)
(0.89)
1.67∗∗∗ −0.35
0.92∗∗
(0.36)
(0.42)
(0.40)
−2.45∗∗
−1.06
0.35
(1.33)
(1.67)
(1.14)
0.05
0.08
−0.02
(0.06)
(0.06)
(0.03)
−0.02
0.02
0.02
(0.06)
(0.07)
(0.03)
0.01∗∗∗
0.18
0.22
(0.26)
(0.27)
(0.00)
0.10
0.07
0.03
(0.08)
(0.08)
(0.03)
0.03
0.04
−0.03
(0.11)
(0.10)
(0.02)
−0.14
−0.16
−0.08
(0.17)
(0.18)
(0.15)
0.09∗
0.11∗∗
0.07∗∗
(0.05)
(0.03)
(0.05)
−0.20∗∗
−0.21∗∗∗ −0.15∗
(0.08)
(0.08)
(0.07)
−8.55∗∗∗
4.56
2.37
(3.59)
(2.78)
(1.27)
1.74∗∗∗
1.67∗∗∗
2.29∗∗∗
(0.35)
(0.28)
(0.32)

(0.49)
−2.20∗
(1.20)
1.07∗
(0.55)
−0.63
(1.42)
0.08
(0.06)
−0.01
(0.07)
0.05
(0.31)
0.13
(0.10)
0.05
(0.10)
−0.14
(0.20)
0.11∗∗
(0.05)
−0.16∗
(0.09)
2.82
(3.51)
1.94∗∗∗
(0.35)

Time ﬁxed eﬀects
Country ﬁxed eﬀects

N
Groups
R2

Yes
Yes

246
27
0.46

Yes
Yes

247
27
0.41

No
No

246
27
0.28

Yes
Yes

246
27
0.47

Yes
Yes

246
27
0.44

Yes
Yes

246
27
0.46

Notes: Dependent Variable is discretionary effort from Carnot and de Castro (2015). Columns indicate different settings
regarding control variables and fixed effects, as well as different types fiscal rules (if not otherwise mentioned the fiscal rule
variable refers to all fiscal rules). Regressions include time and country fixed effects according to rows. Standard errors
which are robust to heteroskedasticity, panel-specific autocorrelation and contemporaneous cross-sectional dependence
(i.e. Parks-Kmenta panel corrected standard errors as proposed in Beck and Katz, 1995) are in parentheses. * indicate
significance at 10% level, ** at 5% level and *** at 1% level.

ECB Working Paper 1872, December 201527A.7 Robustness: Thresholds, Fiscal Rules, Fiscal Space

and Discretionary Fiscal Policy

Table A6: Regression results - thresholds of ﬁscal space (dependent variable:

discretionary eﬀort)

Fiscal Rule

Fiscal Space < 50%

Fiscal Space < 50% x Fiscal Rule

Fiscal Space >= 50% < 150%

Fiscal Space >= 50% < 150% x Fiscal Rule

Fiscal Space >= 150%

Fiscal Space >= 150% x Fiscal Rule

N
Groups
R2

(1)
−7.539∗∗∗
(2.856)
−16.910∗∗
(6.911)
1.146
(7.317)
−7.726∗∗∗
(1.755)
5.678∗∗∗
(1.849)
−5.007∗∗∗
(1.113)
2.736∗∗∗
(0.938)

236
27
0.515

Notes: Dependent Variable is discretionary effort from Carnot and de Castro (2015). All regressions include
control variables, time and country fixed effects. Fiscal Rule variable refers to all fiscal rules. Standard er-
rors which are robust to heteroskedasticity, panel-specific autocorrelation and contemporaneous cross-sectional
dependence (i.e. Parks-Kmenta panel corrected standard errors as proposed in Beck and Katz, 1995) are in
parentheses. * indicate significance at 10% level, ** at 5% level and *** at 1% level.

ECB Working Paper 1872, December 201528A.8 Robustness: Fiscal Rules, Fiscal Space and Procycli-

cality of Fiscal Policy

Table A7: Regression results (rolling window, dependent variable: procyclicality of ﬁscal policy)

Population

Fiscal Rule

Fiscal Space

Trade Openness

Δ GDP per Capita

Δ Financial Openness

Fiscal Space x Fiscal Rule

(3)
(2)
(1)
15-year
No
All
averages
controls
Rules
0.32∗∗
0.41∗∗∗
0.30∗∗∗
(0.16)
(0.09)
(0.09)
0.05∗
0.05∗∗∗
0.03∗∗∗
(0.01)
(0.02)
(0.01)
−0.27∗∗∗ −0.29∗∗∗ −0.35∗∗
(0.09)
(0.17)
(0.09)
−0.13∗∗
−0.07
(0.05)
(0.07)
−0.56∗∗
−0.01
(0.28)
(0.20)
0.14∗∗∗
0.14∗∗∗
(0.03)
(0.03)
−0.06
−0.15
(0.20)
(0.18)
−0.29∗∗∗
−0.33∗∗∗
(0.10)
(0.13)
−0.39
−0.29
(0.22)
(0.30)
−0.01
−0.03
(0.03)
(0.02)
0.25
0.16
(0.19)
(0.11)
0.20
0.30
(0.48)
(0.32)
0.33
Government Fragmentation −1.10
(0.59)
(0.79)
0.03
0.05
(0.22)
(0.13)
0.19
−0.09
(0.13)
(0.14)
−0.11
−0.13
(0.12)
(0.10)

Future age dependency

Eurozone Membership

IMF Arrangement

Ideological Range

Age dependency

EU Membership

Election Years

Ideology

N
Groups
R2

374
26
0.352

389
27
0.195

260
26
0.369

Notes: Dependent Variable is procyclicality of fiscal policy. Columns indicate different settings definitions of ”Fiscal Rule”
variable. Standard errors which are robust to heteroskedasticity, panel-specific autocorrelation and contemporaneous cross-
sectional dependence (i.e. Parks-Kmenta panel corrected standard errors as proposed in Beck and Katz, 1995) are in parentheses.
All regressions include time and country fixed effects. * indicate significance at 10% level, ** at 5% level and *** at 1% level.

ECB Working Paper 1872, December 201529Acknowledgements 
We thank Nicolas Carnot and Francisco de Castro for providing their fiscal effort data. Furthermore, we want to thank Ekkehard Köhler, 
an anonymous referee and several seminar and conference participants (a.o. at the European Central Bank, the Central Bank of 
Croatia, the Walter Eucken Institut in Freiburg, or the EEA in Mannheim) for their valuable comments and suggestions. The views 
expressed in this paper are exclusively those of the authors and do not necessarily reflect those of the European Central Bank. 

Carolin Nerlich  
European Central Bank, Frankfurt am Main, Germany; 
e-mail: carolin.nerlich@ecb.int 

Wolf Heinrich Reuter 
Vienna University of Economics and Business, Vienna, Austria; 
e-mail: wolf.reuter@wu.ac.at  

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ISSN 
ISBN 
DOI 
EU catalogue No 

1725-2806 (online) 
978-92-899-1685-1 
10.2866/521587 
QB-AR-15-112-EN-N