National Numerical Fiscal Rules: Not Complied With, But Still Effective?

Transcription

1 National Numerical Fiscal Rules: Not Complied With, But Still Effective? Wolf Heinrich Reuter 1 1 Vienna University of Economics and Business, Department of Economics September, 2014 Abstract This paper investigates the effects of (non-)compliance with national numerical fiscal rules on fiscal policy in 11 EU member states with 23 fiscal rules in place from Introducing a new dataset of legal texts constituting the fiscal rules, allows a joint empirical analysis of different types and designs of numerical fiscal rules. In various empirical exercises the change in the difference between the exact variable constrained by the fiscal rule and its numerical limit is analysed. Statistics show that countries tend to comply with their fiscal rules only in about 50% of the years. Various econometric exercises demonstrate that the introduction of fiscal rules does significantly change the behaviour of fiscal policy. If countries do not comply with their fiscal rule in the year or forecast before, there is a strong downward tendency of the constrained variable towards the numerical limit. Furthermore fiscal rules significantly dampen the strong increase of fiscal variables from lower levels, i.e. if a country is in compliance with its fiscal rules. JEL-Classification: H60, H68, E02, E62 Keywords: National fiscal rules, Numerical limits, Budget forecasts, Fiscal policy The author would like to acknowledge very helpful comments from and discussions with Elisabeth Nindl, Julia Bachtrögler, Heiko Burret, Rupert Sausgruber, Harald Badinger, Jesus Crespo Cuaresma, Klaus Gugler, the support of Paul Schabl for great research assistance, the ECB fiscal policies division for providing the EU Comission AMECO data forecasts, and the translations and legal support of the native speakers and translators (found via odesk.com): Janet Alexandersson (SE), Elisa Alonso (ES), Akos Bartha (HU), Boryana Bobcheva (BG), Ursa Bratun (SI), Ivan Eckhardt (CZ), Simona Eftimie (RO), Sona Kopalova (SK), Karol Koziol (PL), Siddiq Mohammed (IE), Joao Pena (PT), Monika Sukyte (LT), Stefano Vignati (IT). Furthermore the author would like to thank the discussants and participants of several workshops and seminars, two anonymous referees, as well as the Wicksell Prize comittee for awarding this paper. Wolf Heinrich Reuter, Department of Economics, Vienna University of Economics and Business, Welthandelsplatz 1, 1020 Vienna, Austria, Tel.: , wolf.reuter@wu.ac.at. 1

2 1 Introduction In the aftermath of the financial crisis of 2007/2008 the EU (and in particular the Eurozone) slithered into a sovereign debt crisis, caused by high public deficits and uncertainty on the financial markets. As a consequence, several initiatives have been brought forward to strengthen the EU s fiscal governance and regain trust into the sustainability of public finances. Most notably the so called sixpack 1, fiscal compact 2 and two-pack 3 regulations amended and aligned fiscal governance at supranational and national level. Due to these regulations EU member countries have to introduce fiscal rules, independent fiscal councils and more stringent medium-term budgeting frameworks in national laws and constitutions. The aim of these new regulations is to counteract the deficit bias of governments 4, lead to balanced public finances and to assure the financial markets about the medium term fiscal goals. Numerical fiscal rules, as part of this strengthened fiscal governance frameworks, have been one of the most important components of the EU s response to the sovereign debt crisis. This paper investigates the effectiveness and impact of such national numerical fiscal rules. As more and more data on national fiscal rules has become available 5, several studies have been published, which analyse the general impact of the existence of fiscal rules on fiscal policy variables, like budget balance or debt levels. For the US, Poterba (1994), Alt and Lowry (1994), Roubini and Sachs (1989) find that more stringent fiscal rules are associated with a higher speed of reduction of unexpected deficits. With regard to the goal of achieving a lower overall budget deficit, there is supporting evidence for the US by Bohn and Inman (1996), Canova and Pappa (2006) and Alesina and Bayoumi (1996); for Canada by Imbeau and Tellier (2004); for Latin America by Alesina et al. (1999); for Switzerland by Feld and Kirchgässner (2006) and Krogstrup and Wälti (2008); for OECD countries by Perotti and Kontopoulos (2002), Dahan and Strawczynski (2010), and Guichard et al. (2007); for EU countries by Hallerberg and von Hagen (1999), Von Hagen and Harden (1994), De Haan et al. (1999), Deroose et al. (2006), Fabrizio and Mody (2006), Ayuso-i Casals et al. (2007), and Debrun et al. (2008). Most of these studies analysing the effect of fiscal rules on fiscal policy find a positive effect, i.e. more or stricter fiscal rules improve the public balances. Yet these existing empirical studies analyse the binary impact of the mere existence 1 The six-pack entered into force in December 2011 and consists of five regulations and one directive of the European Commission and Parliament, introducing stronger macroeconomic surveillance and a reform of the Stability and Growth Pact. 2 The inter-governmental Treaty on Stability, Coordination and Governance (TSCG or fiscal compact ) entered into force in January 2013 and introduced or strengthened numerical fiscal rules and independent monitoring institutions at the national level. 3 The two-pack consists of two regulations adding monitoring and surveillance procedures to the six-pack and stipulating some of the regulations in the fiscal compact into EU law. 4 See e.g. Calmfors and Wren-Lewis (2011) for an overview of the political economy literature regarding the deficit bias of governments. 5 For a discussion of the historic development of fiscal frameworks see e.g. Schaechter et al. (2012). 2

3 (combined with some key characteristics) of various types of numerical fiscal rules. They neglect their details of design, actual level of the imposed constraints and periods of compliance or non-compliance with the rules. The most recent studies (e.g. Debrun et al or Ayuso-i Casals et al. 2007) rely on the databases by the European Commission (2010) or the IMF (2012) and use composite indices to describe the national fiscal frameworks. The two databases provide information only about the existence and some key features of the fiscal rules in the respective countries. They ignore the substantial differences in the formulations of national numerical fiscal rules, which can have different effects with respect to the reaction of policy makers. The following are three compressed examples of such rules as defined in national law: Debt Rule in Poland (in force since 1999): The general government debt to GDP ratio must not exceed 50%. Article 45, Act of 26 November 1998 on Public Finances Balanced Budget Rule in Germany (in force from ):...Revenue obtained by borrowing shall not exceed the total of investment expenditures... Article 115 (1), Basic Law for the Federal Republic of Germany, after 20th Amendment, May 12, 1969 Expenditure Rule in Lithuania (in force since 2008):... where the average of the budget balance[...] for the past five [...] years [...] is a deficit [...], the annual growth rate in % of [expenditures] [...] for the corresponding year[...] may not exceed one half of the average annual growth rate in % of [...] revenues [...] for the past five [...] years. Article 3, Law on Fiscal Discipline, Nov All three rules differ in many aspects and additionally the full legal articles usually also include several exceptions and cumbersome instructions on how to calculate the constrained variables. Consequently, as numerical fiscal rules at the national level are very different from each other, they are not easy to compare and estimations ignoring the detailed design of the rules might misinterpret the real impact on fiscal policy. Some countries have rules which are very strict and others have rules which are very loose such that they are always complied with (e.g. the debt rule in Bulgaria). Some rules account for the current economic situation in the design of the numerical constraint, others do not. Previous studies were not able to take this into account and only classified the various fiscal rules according to important characteristics. The present paper analyses the compliance of countries with different national fiscal rules and its effect, which has not been done in the literature before. To fill this gap a new dataset is introduced which entails the 46 national numerical fiscal rules (mentioned in European Commission, 2010 or IMF, 2012) in the EU27 from , which are or were enacted in law or constitution and 3

4 cover the central or general government. The database contains the respective text passages from constitutional and legal documents of the EU countries that impose such fiscal rules. Furthermore, the database also contains information about the exceptions and calculation of the mentioned variables and limits. Based on this dataset the actual and forecast values of the variables constrained by the respective fiscal rules as well as the numerical limit, both chosen or calculated as stated in the legal documents and transformed into ratios of GDP, were calculated. Relying on this data allows a joint analysis with different types and different implementations of fiscal rules on the national level. Furthermore, it reduces the problems associated with the so far used composite indices, which are largely time invariant, do not consider the actual numerical target the various rules are setting and ignore the fiscal situation of a country with respect to this limit. Furthermore the estimations can shed some light on the role of increased budgetary transparency, monitoring of governments and awareness of the public. Usually these elements are strengthened simultaneously with the introduction of fiscal rules, which makes it difficult to use them together in an empirical exercise and identify the effects separately. The paper most closely related to this one is the study by Frankel and Schreger (2013), who analyse the forecasting behaviour of the Eurozone countries and their compliance with the supranational 3% deficit rule of the Stability and Growth Pact, as well as the effect of the existence of national numerical fiscal rules based on the data by the IMF (2012). They find that government forecasts (using the annual stability and convergence programmes submitted to the European Commission by the governments as database) are biased into the optimistic direction. National fiscal rules and national fiscal institutions however, reduce the optimistic bias and counteract unrealistic forecasts. Other papers looking at the behaviour of fiscal policy in the context of the existence of fiscal rules in connection with official forecasts are Pina and Venesi (2011) and Luechinger and Schaltegger (2013). The remainder of this paper is structured as follows: The structure and content of the employed dataset is explored in Section 2 and some descriptive statistics are presented in Section 3. Section 4 sets out the empirical setups which will be used in Section 5, where the results are presented. Section 6 concludes and the Appendix A provides additional data descriptions and robustness checks. 4

5 2 Data The European Commission (2010) and IMF (2012) databases together contain 46 different national numerical fiscal rules in the countries of the EU27, which are or were enacted in law or constitution and cover the central or general government. Together with native speakers and translators the respective legal documents and law paragraphs (plus related paragraphs) defining each of these fiscal rules were collected 6. Using those texts and the information provided in the European Commission (2010) and IMF (2012) databases the actual and forecast values of the numerical constraint (F R ), as well as the constrained variable (F) on which the fiscal rule is imposed on, were chosen or calculated relying on various vintages of the AMECO database of the European Commission. These constrained variables and numerical limits were also calculated for the years in which the rules were not in force (yet or anymore), assuming the respective fiscal rule would have been effective over the full sample period. This enables a comparison between the behavior of governments before and after the introduction of a fiscal rule. Of the total of 46 fiscal rules, some cannot be included in the empirical analysis of this paper: 10 rules are omitted because they turn out to be no fiscal rules in the sense of Kopits and Symanski (1998), but rather medium term budgeting (or expenditure) frameworks (MTBF). The numerical constraints imposed by these MTBF are changed and adjusted frequently, and not comparable to the other numerical fiscal rules. 10 rules cannot be included, because the exact data are not available or the rules are constraining only small fractions of the government. After the thorough study of the legal documents, 6 rules are, contrary to the information in European Commission (2010) and IMF (2012), found to be no numerical fiscal rules, not enshrined in law or constitution or will become enforced only in the future. The resulting 23 fiscal rules included in this paper are shown in Table 1 and the fiscal rules omitted (including the reasons to do so) are presented in Table 9 in Appendix A.2. Table 1 also shows simplified versions of the respective rules set out in the legal documents. The various national fiscal rules differ with regards to the variables chosen to be constrained and even if some are constraining the same variables, they are setting different numerical limits. For the calculations of the variables used in the empirical exercises, also the exceptions and escape clauses have been taken into account. Some vagueness still remains, as some rules are defined in an ambiguous way (probably to leave some room for interpretation for policy makers) and for some rules data were not available for all exceptions (mentioned in the legal documents). But if rules are included in the empirical part of this paper the data used represent at least 80% of the data mentioned in the rule and the missing data usually affects both the numerical limit and the constrained variable. 6 The full database of legal texts and translations is available online on the author s personal website. 5

6 Table 1: Numerical fiscal rules included in this paper Cty 1 Rule Time EC 2 IMF 3 Simplified Rule BG DR 03- x x if Dt Y >= 60% : Dt Y <= Dt 1 Y BG BBR x BBt Y => 2% BG ER x Et Y <= 40% DE BBR x 5 x BB t <= Inv t DE BBR x 7 x SBt+1 Y SBt Y <= (SB2010 Y 0.35)/4 ES BBR x x 8 BBt Y >= 0 ES BBR x x if δy t < 2%: BBt Y > 2%; if δy t > 3% : BBt Y > 0; else: BBt Y >= 0 ES BBR 10- x x if δy t < 2%: BBt Y > 1%; if δy t > 3% : BBt Y > 0; else: BBt Y >= 0 ES ER 11- x x δ(p E t UnempB t ) <= 3 δy t HU BBR x 10 x P B t > 0 HU BBR x BB t > BB t 1 HU ER P E t <= P E t 1 HU ER x δrp E t < 50%δRY t HU DR x 11 - Dt Y < Dt 1 Y LT ER 08- x x if 5 BB t < 0 : δe t <= 50% 5 δr t PL DR x 13 x Dt Y < 50% PL ER 11- x x δre t <= 1% PT BBR x - BB t >= 0 RO ER x if BB t < 0: δe t < δy t SE BBR 07- x x 14 SBt Y >= 1% SK DR x Dt Y <= 50% UK BBR x x CAB t + Inv t >= 0 UK DR x x Dt Y < 40% Notes: 1 Country name; 2 x if rule is included in European Commission (2010), deviations from European Commission (2010) in notes; 3 x if rule is included in IMF (2012), deviations from IMF (2012) in notes; 4 data is available only from 1991; 5 only since 1990; 6 transition period from new BBR; 7 until 2016; 8 from 2003; 9 transition period of new BBR during financial crisis; ; 11 since 2009; 12 50% where first automatic sanctions take effect, 13 since 1997; 14 since 2010; 15 50% where first automatic sanctions take effect; Abbreviations: BBR = Balanced Budget Rules, DR = Debt Rule, ER = Expenditure Rule; δ growth rate from t 1 to t, θ θ-year average, with Y always ratio of GDP, D Debt, BB Budget balance, P B Primary budget balance, SB Structural balance, CAB cyclically adjusted budget balance, E total expenditures, P E Primary expenditures, RE real expenditures, RP E real primary expenditures, UnempB expenditures for unemployment benefits, R total revenues, Inv public investments, Y gross domestic product, RY Real gross domestic product. The economic data (actual and forecasts) to calculate the limits and constrained variables are taken from various semi-annual vintages (autumn 1995 to spring 2013) of the AMECO database of the European Commission. This also implies that the forecast data used in this paper are the forecasts of the European Commission (as opposed to e.g. Frankel and Schreger, 2013 who use the own forecasts of the governments), which provides the advantage that the data (especially the forecasts) might be more resilient to the political influence of governments and national interest groups. The actual values for the years are taken from the spring 2013 vintage and all variables are in percentage of GDP (also 6

7 e.g. the difference in growth rates have afterwards been transformed into percentage of GDP values). If necessary, variables are multiplied by 1 to achieve a homogenous meaning with regards to the compliance with the fiscal rules, i.e. if the variable constrained is smaller than the numerical constraint, the country complies with the rule, otherwise it does not. Data on fiscal councils and medium term budgeting frameworks are taken from Nerlich and Reuter (2013). 2.1 Definition of variables To shorten the tables and figures in the sections below the following notations are introduced (Figure 1 shows a schematical representation of the defined variables). F i,j,t,τ represents the constrained variable (e.g. structural balance, growth rate of expenditures, debt to GDP ratio, etc.) for the year t of the numerical fiscal rule j of country i. The value of the variable for each year t is available at six different points in time: the actual value (taken from the spring 2013 vintage of the AMECO database; represented by τ = 0), the autumn forecast in the same year t (τ = 1), the spring forecast in the same year t (τ = 2), the autumn forecast of the previous year t 1 (τ = 3), the spring forecast of the previous year t 1 (τ = 4) and the autumn forecast of two years before t 2 (τ = 5). The meaning of the subindices remains the same, for Fi,j,t,τ R which represents the numerical limit imposed on the variable F i,j,t,τ by fiscal rule j in country i forecast in period τ (or the actual value if τ = 0) for the year t. Non-compliance Compliance Numerical constraint / limit set by fiscal rule Constrained variable Figure 1: Schematic diagram of variable definitions Furthermore the following differences are defined. Equation 1 represents the difference of the constrained variable from one forecast to the next (half a year 7

8 later). The difference in forecasts which are one semester apart can be quite large, e.g. the average change in GDP forecasts for our sample is -0.6%. The difference of actual values (τ = 0) between two consecutive years is represented in Equation 2. τ F i,j,t,τ := F i,j,t,τ F i,j,t,τ 1 (1) t F i,j,t,0 := F i,j,t,0 F i,j,t 1,0 (2) The difference between the value of the constrained variable and the numerical limit for the same time period and the same forecast is defined in Equation 3. This difference R F i,j,t,τ is negative if the country complies with the rule, i.e. the constrained variable is below the limit set by the fiscal rule, and positive otherwise. R F i,j,t,τ := F i,j,t,τ F R i,j,t,τ (3) Equations 4 and 5 represent two variations of the R difference. The first one R+ F i,j,t,τ being zero if the country complies with the rule (i.e. the difference R F i,j,t,τ is negative), and equal to the difference R F i,j,t,τ otherwise. The second equation defines exactly the opposite case. R+ F i,j,t,τ := R F i,j,t,τ := { R F i,j,t,τ if Fi,j,t,τ R < F i,j,t,τ 0 otherwise { R F i,j,t,τ if Fi,j,t,τ R > F i,j,t,τ 0 otherwise (4) (5) For the empirical analysis the definition of the dummy variable in Equation 6 will also be useful. B i,j,t,τ is one if the fiscal rule is binding, i.e. if the constrained variable is above its limit imposed by the fiscal rule, and zero otherwise. B i,j,t,τ := { 1 if F R i,j,t,τ < F i,j,t,τ 0 otherwise (6) To distinguish between years in which the respective fiscal rules are in force and years where they are not, the dummy variable R i,j,t is introduced. The variable is one if the fiscal rule j of country i is enshrined in law or constitution covering the central or general government and effective in year t, and zero otherwise. 8

9 3 Descriptive Statistics The 23 numerical fiscal rules used in the empirical part of this paper (described in Section 2) are or were enacted in 11 EU countries from 1990 to The first row of Table 2 shows that (if a fiscal rules was in place) approximately in half of the years the countries complied with their respective fiscal rules (i.e. the constrained variables were below the imposed numerical limit). Rows (2)-(4) of the same table present the percentage of years where countries changed between compliance and non-compliance with their fiscal rules or vice-versa from one, two or three years ahead. If a country did not comply with its fiscal rule in t 1 (t 2 and t 3) in 11.5% (21.3% and 29.7% respectively) of the cases it complied with it in year t. The other way around was less likely, as countries which complied with its fiscal rule in t 1 (t 2 and t 3), did not comply with it in 9.1% (14.1% and 22.0%) of the cases in year t. Table 2: Statistics on annual compliance with numerical fiscal rules in actual values Compliance Perc. (1) B i,j,t = % Change from non-compliance Perc. Change from compliance Perc. to compliance to non-compliance (2) B i,j,t 1 = 1 & B i,j,t = % B i,j,t 1 = 0 & B i,j,t = 1 9.1% (3) B i,j,t 2 = 1 & B i,j,t = % B i,j,t 2 = 0 & B i,j,t = % (4) B i,j,t 3 = 1 & B i,j,t = % B i,j,t 3 = 0 & B i,j,t = % Notes: First row shows percentage of years where countries did comply with their fiscal rules, i.e. the rules were not binding; Rows (2) to (4) show in the first column the percentage of years where countries did not comply with rule in the respective year (t 1, t 2, t 3), but did in year t, and the second column shows the opposite case where countries did comply with the rules in the respective year (t 1, t 2, t 3), but did not in year t. For annual changes Table 2 already showed that only in approximately half of the years the countries complied with their fiscal rules and that there is a weak tendency for governments to change their fiscal policy towards compliance with the fiscal rules. This also approximately holds true for statistics showing changes in the forecasts (Table 3). The average difference between the variables and their constraint (middle panel in Table 3) is around 2% of GDP with a trend away from the constraint the closer the forecasts get to the actual year. I.e. countries tend to be closer to compliance with their fiscal rules in the forecasts than they actually do at time t. The same pattern can be observed if the variable is split between positive and negative values. The statistics in the bottom panel of Table 3 show that in 14% of the observed years the countries did comply with their numerical fiscal rule in the forecasts two years ahead of the actual year, but did not comply in the actual numbers. One reason might be presented by Frankel and Schreger (2013), who find a systematic bias in the positive direction in the forecasts especially of Eurozone countries. They show this pattern for the Maastricht fiscal rules using the own forecasts of the governments published in 9

10 the annual stability and convergence programmes. Nevertheless, this bias seems to fade away the closer the forecasts get towards the actual year. Only in very exceptional cases (1% - 2% of the years) the forecasts in the same year still show compliance with the fiscal rule, when there is none in the actual numbers. The other way around, i.e. non-compliance in the forecasts but compliance in the actual numbers, is more common. This might be a first sign that governments do change the policy if they do not comply with their fiscal rules in the forecasts. Table 3: Statistics on compliance with numerical fiscal rules in forecasts τ = Forecast semester: autumn spring autumn spring autumn Forecast year: t 2 t 1 t 1 t t actual (1) Compliance (B i,j,t,τ = 0) 50% 45% 50% 54% 53% 49% (2) average R F i,j,t,τ (3) average R F i,j,t,τ (4) average R+ F i,j,t,τ (5) B i,j,t,τ = 0 & B i,j,t,0 = 1 14% 11% 8% 2% 1% (6) B i,j,t,τ = 1 & B i,j,t,0 = 0 14% 14% 10% 7% 6% Notes: First row shows percentage of years where countries did comply with their fiscal rules, i.e. the rules were not binding; Rows (2) to (4) average (over years and countries) difference between constrained variable and constraint; Row (5) shows percentage of years where countries did comply with rule in the respective forecast, but not in the actual numbers, and row (6) the opposite case where countries did not comply with the rules in the forecasts, but did in the actual data The same numbers for the forecast period two years ahead (τ = 5) and the actual value (τ = 0) are shown in Table 4 for different subgroups of countries respectively years. The upper panel shows the percentage of years in compliance with the fiscal rule split by the years where the country had a fiscal council (F C), a medium term budgeting framework (MT BF ) or both (F C & MT BF ). What stands out is that for years with a fiscal council the compliance in the forecasts is slightly higher and a medium term budgeting framework on the other hand seems to increase compliance in the forecasts, but decreases it in the actual numbers. This could be due to the fixed and inflexible nature of the MTBFs. At the time when the limits or goals of the MTBFs for the coming years are set, they comply with the fiscal rules. But then the economic situation changes from the two year ahead forecast to the actual number, however the goals in the MTBF remain the same, which leads to the fiscal rules being violated. This can also be seen in the lower part of the upper panel of Table 4. In two fifths of the years with MTBFs the rules were not binding in the forecasts, but they were in the actual number. The opposite was almost never the case. In terms of the lowest rate in changes of compliance from forecast to actual value, the combination of fiscal council and medium term budgeting framework seems to be the strongest. 10

11 Table 4: Detailed statistics of compliance with fiscal rules in forecasts for subsamples τ = FC MTBF FC & MTBF (1) B i,j,t,τ = 0 58% 58% 67% 33% 50% 50% (2) B i,j,t,τ = 0 & B i,j,t,0 = 1 16% 39% 10% (3) B i,j,t,τ = 1 & B i,j,t,0 = 0 22% 6% 10% BBR DR ER (4) B i,j,t,τ = 0 46% 35% 80% 81% 35% 73% (5) B i,j,t,τ = 0 & B i,j,t,0 = 1 17% 15% 0% (6) B i,j,t,τ = 1 & B i,j,t,0 = 0 8% 10% 47% Notes: Rows 1 and 4 shows percentage of years where countries did comply with rules, i.e. the rules were binding; Row 2 and 5 shows percentage of years where countries did comply with rule in the respective forecast, but not in the actual numbers, and row 3 and 6 the opposite case where countries did not comply with the rules in the forecasts, but did in the actual data; FC = Fiscal Council, MTBF = Medium Term Budgeting Framework, BBR = Balanced Budget Rules, DR = Debt Rule, ER = Expenditure Rule The empirical analysis in this paper relies on 11 Balanced Budget Rules (BBR), 5 Debt Rules (DR) and 7 Expenditure Rules (ER). The lower panel of Table 4 shows the compliance statistics split by these types of rules. Some interesting observations emerge. The compliance in the actual numbers is generally much higher with debt and expenditure rules than with balanced budget rules. Balanced budget rules are complied with more often in the forecasts than in the actual values, contrary to debt and expenditure rules. This is also confirmed by the statistics in the lower part of the lower panel. In approximately a fifth of the years balanced budget rules were complied with in the forecasts but not in the actual value. For expenditure rules this never occurred, whereas in almost half of the years a country did not comply with its fiscal rule in the forecast, this changed in the actual numbers. 4 Estimation Framework The empirical analysis of this paper relies on three different estimation frameworks using modified dependent variables. The first one analyses the impact of the difference between the constrained variable and numerical limit ( R F i,j,t,τ 1 ) on the same variable of the next period ( R F i,j,t,τ ), depending on the fact that the fiscal rule is in force or not (R i,j,t ). To distinguish between a more general behaviour of fiscal policy and the actual effect of introducing a fiscal rule in law or constitution, the difference between variable and constraint is calculated not only for the years a fiscal rule is in force in a country, but for the full sample period. This enables a comparison between the behavior of governments in periods when no fiscal rules are in force (are not effective) and periods where they 11

12 are. The setting of Equation 7 also allows to compare the results with related studies and investigate the persistence of (non-) compliance with fiscal rules. R F i,j,t,0 = β 0 + β 1 R i,j,t R F i,j,t 1,0 + β 2 R i,j,t + β 3 R F i,j,t 1,0 + x i,tγ + µ j + ν t + ɛ i,j,t (7) Rule fixed effects (µ j ) and time fixed effects (ν t ) are included, and ɛ i,j,t,τ represents the error term. Hausman tests on omitting the rule fixed effects were all rejected and robustness checks of leaving out the time fixed effects, which are quantitatively and qualitatively very similar, are shown in the Appendix. Furthermore a wide range of control variables (x i,t ) is included, which are common in this strand of literature. For a detailed description of the variables and the reason for including them see e.g. Nerlich and Reuter (2013) and Appendix A.1. The controls can be grouped into three categories: i) economic variables (lagged debt levels, lagged output gap, inflation rate, dependency ratio, population and openness), ii) political variables (ideology of government, ideological distance of parties in government, government size, fragmentation of government, closed vs. open list elections - also interacted with district magnitude -, district magnitude and election years), and iii) institutional variables (delegation or contract approach to governance - both also interacted with government fragmentation -, institutional quality, stability and growth pact and the run-up to the EMU). The variables are included to prevent an omitted variable bias, but in Appendix A.3 the results are also shown excluding the control variables and to be qualitatively the same. A series of robustness checks are executed which are partly reported in Appendix A.3. Among others, a dynamic equation with a lagged dependent variable is estimated, Arellano-Bond is used to control for potential serial correlation in the errors, and Kiviet s corrected least square dummy variable method is applied to correct for the bias of the standard fixed effects estimator in a dynamic model. Furthermore, different sample periods and combinations of fixed effects are used as well as weighting the rules by the number of years they were in force, including the level of the constrained variable and including the explanatory variable squared. Generally the tables in the main text show the results yielding the relatively lowest coefficients and lowest significance compared to alternative robustness checks, i.e. can be seen as lower bound of the actual effects and significance. While there might be endogeneity concerns regarding the estimation setting in Equation 7 where the dependent variable enters in levels, these should be diminished significantly when using differences between years and even more so when using differences between forecasts. And as will be shown the main results qualitatively stay the same among all the different settings. Concerns that countries introduce fiscal rules because of longer term non-compliance with the (fictional) rule (i.e. high levels of the constrained variable), are adressed by investigating the change of the variables. Furthermore there might be concerns about an omitted variable bias, i.e. that there could be reasons why fiscal 12

13 rules are in force in the same years where also the difference of the dependent variable is significantly altered (e.g. economic crisis, joining the EMU, change of government/ governance). Therefore time fixed effects and a wide range of control variables are introduced which should cover most of the possible reasons for such a simultaneity problem. In another variant of Equation 7 the variable R F i,j,t 1,0 on the right hand side is split into a positive ( R+ F i,j,t 1,0 ) and a negative part ( R F i,j,t 1,0 ), to uncover potentially opposing behavior of the constrained variable with respect to its position relative to the numerical limit. To investigate the policy reaction of government to (non-)compliance with the fiscal rules, also the difference is used as dependent variable in the same setting as in Equation 7. Furthermore not only the reaction to annual compliance is analyzed, but also changes from forecast to forecast. Thus Equation 8 measures the impact of the difference between the constrained variable and numerical limit ( R F i,j,t,τ 1 ) on the difference of that variable to the next forecast period ( τ ( R F i,j,t,τ )), depending on the fact that the fiscal rule is in force or not (R i,j,t ). I.e. the estimation investigates how policy makers adjust the constrained variables from forecast to forecast depending on the current distance between variable and numerical constraint. τ ( R F i,j,t,τ ) = β 0 + β 1 R i,j,t R F i,j,t,τ 1 + β 2 R i,j,t + β 3 R F i,j,t,τ 1 + x i,tγ + µ j + ν t + ɛ i,j,t,τ (8) Another variant of the estimation settings above is presented in Equation 9 where the change in the constrained variable from one year to the next or from one forecast to the next is regressed on the fact that the fiscal rule was binding in the earlier of the two years / forecasts (B i,j,t 1,0 / B i,j,t,τ 1 ), again depending on the fact that the fiscal rule is in force or not (R i,j,t ). τ F i,j,t,τ = β 0 + β 1 R i,j,t B i,j,t,τ 1 + β 2 R i,j,t + β 3 B i,j,t,τ 1 + x i,tγ + µ j + ν t + ɛ i,j,t,τ (9) 5 Results The first basic question in the context of this paper is whether fiscal rules achieve their main goal of keeping a variable (which can be different for each rule) below a certain numerical limit (also determined by each rule individually). As seen in Table 2 of Section 3 this is only the case in approximately half of the years. A secondary goal of fiscal rules would be to at least force governments to adjust their budgetary plans in such a way that the constrained variable is moving in the direction of the constraint, if it is violated. Therefore the following sections analyze the reaction of policy makers to (non-)compliance with their fiscal rules on an annual basis and regarding forecasts. 13

14 5.1 Determinants and policy reaction to annual (non-) compliance As already mentioned in the introduction there are several studies showing a constant effect of having a fiscal rule or not. To replicate their finding column (1) of Table 5 shows the estimation results of Equation 7 estimating the fiscal rule dummy (R t ) seperately. The result shows that the constrained variable of countries which have a fiscal rule in force in a specific year is 5.5 percentage points of GDP lower with respect to the numerical limit. This effect is much stronger than the one found in the literature so far, which might not be surprising as the other studies look at more general variables (like primary surplus or cyclically adjusted public balance) while this study concentrates on the measures which are actually constrained by the fiscal rules. This constant effect remains but becomes smaller when also the distance between constrained variable and constraint of the previous period is included. Column (2) of Table 5 shows that compliance or non-compliance with fiscal rules is highly persistent, i.e. if the constrained variable is above / violating the fiscal rule in one year the situation is likely to be the same in the following. In this setting there is also no significant difference if the fiscal rule is actually introduced in law or constitution or not, which means that the results show a more general behaviour of fiscal policy rather than the effect of fiscal rules. But this changes if we take into account on which side of the fiscal rule the variables are. Column (3) of Table 5 presents the results where the difference between constrained variable and numerical limit is split between positive (in non-compliance with rule) and negative (in compliance with rule) values. It also becomes clear why no significant effect of effective fiscal rules could be found with the aggregated variable (in Column (2)), as there are two opposing effects depending on which side of the numerical limit the variable is. Taken together the results show that non-compliance is much less persistent if a fiscal rule is in force and although compliance is not persistent without a fiscal rule being in force, it becomes so if one is. I.e. with a fiscal rule in force the governments also have an incentive to keep the constrained variables below the numerical limit. This behaviour will also be visible in the reaction of fiscal policy analysed below. Furthermore the constant level effect of introducing a fiscal rule is not significant anymore. This could mean that introducing a fiscal rule does not shift the mean of the constrained variables, but changes the reaction of fiscal policy to (non- )compliance with fiscal rules. 14

15 Table 5: Estimation results: Reaction to annual (non-)compliance (1) (2) (3) (4) (5) Dep. Var.: R F t,0 t ( R F t,0 ) R F t 1, (0.18) (0.18) R+ F t 1, (0.06) (0.07) R F t 1, (0.26) (0.24) R t R F t 1, (0.23) (0.23) R t R+ F t 1, (0.11) (0.11) R t R F t 1, (0.27) (0.26) R t (2.82) (0.93) (0.81) (0.93) (0.79) All Controls Yes Yes Yes Yes Yes Rule FE Yes Yes Yes Yes Yes Time FE Yes Yes Yes Yes Yes N R 2 (within) RMSE Notes: Estimation results for Equation 7; fixed effects included in regressions as stated in the middle panel; robust standard errors in parentheses; standard errors clustered by country, rule and year; dependent variable is the change in the difference of the constrained variable to its numerical constraint τ ( R F t ) or the change of the annual difference of the constrained variable to its numerical constraint ( t ( R F t,0 )) from one year to the next, explanatory variables are the same variable for the earlier of the years R F t 1,0, split into positive R+ F t 1,0 and negative R+ F t 1,0 values, and a dummy variable being one if the fiscal rule is in force in the respective years R t. Columns (4) and (5) of Table 5 present how fiscal policy changes depending on the distance to the numerical limit in the previous year. First there is a general upward tendency of the constrained variables if the fictional fiscal rules are complied with ( R F t 1,0 ), but this effect is strongly dampened if the fiscal rule is in force (R t R F t 1,0 ). If a country does not comply with its fiscal rule which is enshrined in law or constitution, there is a strong effect to lower the contrained variable towards the numerical limit (R t R+ F t 1,0 ). There is no such tendency if the fiscal rule is not in force. As with the level estimations the constant effect is not significant anymore if the differences are split between positive and negative values, as their coefficients show opposite effect which cancel out if used in an aggregated form. 15

16 5.2 Policy reaction to (non-)compliance in forecasts The previous section analyses the reaction of policy makers to (non-)compliance with fiscal rules from actual values of one year to the next. Table 6 shows similar estimations for differences accross forecasts, i.e. presenting how policy makers change the constrained variables from one forecast to the next with respect to the distance to the forecast numerical limit. Overall the effects are qualitatively the same as for the estimations using the annual values. Table 6 shows the estimation results of Equation 8 analysing the differences in the forecasts. The dependent variable is the change in the difference between constrained variable and numerical limit from one forecast to the next ( τ ( R F t,τ )). Column (3) shows that there is a tendency towards the constraint from above and below, regardless of the fiscal rules being in force or not. I.e. if the variable is in compliance with a fictional fiscal rule which is not effective (difference between variable and constraint is negative), each next forecast the variable is increased by 0.55% of GDP per percentage point between variable and constraint. And if the rule is binding (difference between variable and constraint is positive) the variable is decreased by 0.07% of GDP per percentage point between variable and constraint towards the constraint. The effect of reducing the constrained variable if in non-compliance is much strengthened to 0.23% of GDP if the fiscal rule is in force and the effect of increasing the constrained variable if in compliance is much dampened to 0.23% of GDP. In summary the results show that from forecast to forecast there is a general tendency towards the numerical limit from above and below, but contrary to when there is a fiscal rule in law or constitution the effect is not symetrical but much stronger from below if there is no such rule in effect. 16

17 Table 6: Estimation results: Difference between constrained variable and numerical limit R F t,τ 1 R+ F t,τ 1 R F t,τ 1 (1) (2) (3) (4) (5) Dep. Var.: τ ( R F t,τ ) 0.24 (0.06) R t R F t,τ (0.06) R t R+ F t,τ 1 R t R F t,τ (0.02) 0.55 (0.08) 0.16 (0.04) 0.32 (0.10) R t (0.12) (0.24) (0.26) All Controls Yes Yes Yes Rule FE Yes Yes Yes Time FE Yes Yes Yes N 1,320 1,320 1,320 R 2 (within) RMSE Notes: Estimation results for Equation 8; fixed effects included in regressions as stated in the middle panel; robust standard errors in parentheses; standard errors clustered by country, rule and year; dependent variable is the change in the change of the difference from forecast to forecast of the constrained variable to its numerical constraint ( τ ( R F t,τ )), explanatory variables are the same variable for the earlier of the forecasts R F t,τ 1, split into positive R+ F t,τ 1 and negative R F t,τ 1 values, and a dummy variable being one if the fiscal rule is in force in the respective years R t. 5.3 Quantifying the effect of introducing fiscal rules To quantify the change after the introduction of fiscal rules Table 7 uses the dummy variable B t,τ instead of the difference between constrained variable and numerical limit. The dummy is one if a country does not comply with its fiscal rule, i.e. the rule is binding, in year t 1 or in forecast τ 1 for year t. To avoid endogeneity issues the dummies are not regressed on the difference between constrained variable and numerical limit anymore, but only on the change of the constrained variable from one year or forecast to the next ( t F t,τ or τ F t,τ ). 17

18 Table 7: Estimation results: Dummy variable of non-compliance (1) (2) (3) (4) Dep. Var.: t F t,τ τ F t,τ B t B t,τ (0.31) (0.58) (0.23) (0.33) R B t R B t,τ (0.95) (0.27) R t 1.37 R t 0.51 (1.07) (0.23) All Controls Yes Yes Yes Yes Rule FE Yes Yes Yes Yes Time FE Yes Yes Yes Yes N ,320 1,320 R 2 (within) RMSE Notes: Estimation results for Equation 9; fixed effects included in regressions as stated in the middle panel; robust standard errors in parentheses; standard errors clustered by country, rule and year; dependent variable is the change of the constrained variable from one forecast to the next τ F t,τ, explanatory variables are a dummy variable being one if the country does not comply with its fiscal rule in the earlier of the forecasts B t,τ 1 values, and a dummy variable being one if the fiscal rule is in force in the respective years R t. Column (2) of Table 7 shows that the change of the constrained variable is generally lowered by -2.39% of GDP if a fictional fiscal rule is not complied with in the year before (B t 1 ) As seen before, governments adjust their policy towards the constraint, if they do not comply with their fiscal rule, irrespective of the fact that the rule is in force or not. But the results also show that this adjustment is much stronger (more than twice as strong) if the rules are actually in force. For the change in forecasts (Column (4) of Table 7) this result remains the same, just the coefficients are approximately divided in half corresponding to the semi-annual frequency of the forecasts. 5.4 Level effects of the introduction of fiscal rules The previous sections showed that after including the difference between constrained variable and numerical limit (split between positive and negative values) no (strongly) significant constant effect of introducing fiscal rules is left. One reason could be that the numerical limits introduced in the fiscal rules were just set close to the long run average of the constrained variables. This way no level change in the behavior of the governments could be observed, as they move towards the average (from above and from below) also without a fiscal rule in force. Table 8 explores this argument. Column (1) shows the average of the constrained variable in the 10 years (or less depending on distance to beginning or end of sample period) before the fiscal rule was introduced, Column (2) the 18

19 average of the numerical limit 10 years after the rule was introduced and Column (3) the average of the constrained variable 10 years after the fiscal rule was introduced. About 60% of the numerical constraints set by the fiscal rules are within one standard deviation of the 10 year average of the constrained variable. Many countries introduced their fiscal rules only very late in the sample period thus the 10 year average after the introduction of the fiscal rule might not be very informative. But for the rules which were in force already for at least 5 years no significant shift of the constrained variable compared to before the introduction of the rule can be observed on average. Table 8: Mean of constrained variable and numerical limit before and after introduction of fiscal rule (1) (2) (3) (1) (2) (3) Ctry FR Time 10F 10F R 10F Ctry FR Time 10F 10F R 10F BG DR HU ER BG BBR HU DR BG ER LT ER DE BBR PL DR DE BBR PL ER ES BBR PT BBR ES BBR RO ER ES BBR SE BBR HU BBR SK DR HU BBR UK BBR HU ER UK DR Notes: Average values of the constrained variables F and the numerical limits F R either 10 years before ( 10 ) or after ( 10 ) the fiscal rule was introduced. If the rule was introduced too early or too late in the sample period only the average from or until the sample beginning or end is reported. Also investigating the changes of the rule fixed effects after introducing the fiscal rules does not show a clear pattern. This underlines that there is no significant constant level effect due to the introduction of fiscal rules, but a change in the reaction of policy makers to (non-)compliance with fiscal rules. 6 Conclusions This paper is the first to establish a data set of compliance with national numerical fiscal rules in 11 EU countries from and the difference between the constrained variables and the numerical limits imposed by those rules. The descriptive statistics suggest that countries comply with their fiscal rules only in half of the years, but although there might be an optimistic bias in the forecasts it vanishes the closer the forecasts get to the actual year. Futhermore, the statistics show significant differences between the different types of fiscal rules with debt rules being complied with in 80% of the years and balanced budget rules only in 35%. Expenditure rules show the strongest adjustment 19

20 towards compliance from 35% in the two year ahead forecasts to 73% in the actual values. The empirical analysis shows that introducing fiscal rules decreases the strong persistence in (non-)compliance of the constrained variables with (fictional) numerical limits. There is a general tendency of fiscal policy to increase the constrained variables if in compliance, although this effect is much dampened when fiscal rules are introduced in law or constitution. Effective fiscal rules also significantly force policy makers to reduce the constrained variables towards the numerical limit if the country does not comply with its fiscal rule in the previous year or forecast. The general level shift effect of introducing fiscal rules which was found in many studies in this stream of literature does not remain significant in the empirical settings of this paper. In quantitative terms the introduction a fiscal rule leads to a twice as strong reaction of the fiscal variables to high levels or non-compliance with the fiscal rules. Much research remains to be done on the exact mechanisms and effects of numerical fiscal rules. There is an overall positive effect when introducing (or strengthening) fiscal rules to keep fiscal variables under control, but when and why governments are changing their fiscal policy due to a violation of fiscal rules remains unclear. Another open question is the effectiveness of medium term budgeting frameworks and their relative performance compared to fixed numerical fiscal rules. And finally the effect of (non-)compliance with fiscal rules needs to be investigated in the light of other economic variables, like output, unemployment and the open account, where fiscal rules can also have substantial (negative) effects. References Alesina, A. and Bayoumi, T. (1996), The costs and benefits of fiscal rules: Evidence from us states. NBER Working Paper No Alesina, A., Hausmann, R., Hommes, R. and Stein, E. (1999), Budget institutions and fiscal performance in latin america, Journal of Development Economics 59, Alt, J. and Lowry, R. (1994), Divided government, fiscal institutions, and budget deficits: Evidence from the States, The American Political Science Review 88(4), Ayuso-i Casals, J., Gonzalez, D., Moulin, L. and Turrini, A. (2007), Beyond the sgp: Features and effects of eu national-level fiscal rules, in E. Commission, ed., The Role of Fiscal Rules and Institutions in Shaping Budgetary Outcomes, Economic Papers. Bohn, H. and Inman, R. P. (1996), Balanced Budget Rules and Public Deficits: Evidence from the U.S. States. NBER working paper No