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An empirical investigation into the Europeanization of fiscal policy

Abstract

We investigate the Europeanization of fiscal policy in the eurozone. So doing, we empirically test the impact of a series of pertinent variables on eurozone member states’ fiscal policies during the 1984–2006 period. In addition to a host of usual suspects, we introduce two new measurements to capture a country’s Stability Culture – the effect of which has been not been addressed by previous empirical work. We find evidence that government debt is primarily driven by the state of the domestic economy. Virtually, no empirical support for the claim that institutional, political or ideational factors influence the variations in gross debt can be provided. Specifically, our results show that neither a population’s inflation aversion nor policymakers’ pledge to ‘sound’ public finances translate into lower deficits.

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Notes

  1. In addition to the SGP, a complex set of other economic coordination processes under the Open Method of Coordination (OMC, Hodson and Maher, 2001) have sought to provide a framework for the conduct of economic policies, which may touch upon fiscal policies.

  2. We are working with an arguably narrow understanding of the Europeanization of fiscal policy. Our focus of investigation lies with the state of public finances as measured by the change in government debt. In other words, we are not discussing issues pertaining to economic governance such as tax harmonization, fiscal transfers, Eurobonds or a common fiscal policy.

  3. Austria, Belgium, Italy, Ireland, the Netherlands, Finland, France, Germany, Portugal and Spain; Luxembourg as well as Greece (although not a member of the very first wave) are excluded because of a lack of data for some variables.

  4. Smaller countries are more open as the correlation between ‘population’ and ‘openness’ shows with a value of −0.58.

  5. We are not addressing the impact of national fiscal governance. For an analysis of domestic institutions/fiscal rules see Hallerberg et al (2007). What is more, we are not denying the two-way causality of European integration that has been elucidated by the dichotomy between bottom-up and top-down processes (Börzel, 1999), nor are we denying that other Europeanization process (for example, under the OMC) may impact on public finances. For analytical purposes our study adopts a top-down approach of Europeanization, even though these two processes are in reality interwoven in a highly complex manner. Concretely, it has been well documented that member states’ ideas, interests and ideologies have shaped the rules of EMU (Hoekstra et al, 2008). We control for national specific conditions by clustering for countries. We would hence not assume any bias for the variables of our ‘Europeanization matrix’.

  6. For Austria and Finland the dummy takes value 1 for the years 1995–1997.

  7. These are proxies for Stability Culture. As Guiso et al (2006, p. 26) put it ‘a necessary first step is to define culture in a sufficiently narrow way, so that it becomes easier to identify a causal link from culture to economic outcomes’.

  8. We are aware of proxying popular Stability Culture on the basis of one of its two components. Lack of data for measuring ‘deficit aversion’ prevented us from sizing its fiscal component. However, working solely with ‘inflation aversion’ should not present a problem as the two components go hand in hand and are likely to be highly correlated. It is by now established that the link between deficits and inflation is tentative at best and does not apply to low-inflation advanced economies (Catao and Terrones, 2005). Yet, the economic accuracy of the alleged transition mechanism deficit-inflation is almost irrelevant in this context. At the heart of the construction of the pan-European Stability Culture was the claim that high deficits would cause inflation (EMI, 1996), an assertion that was repeated with the reformed SGP (Gonzalez-Paramo, 2005) and in the aftermath of the financial and economic crisis (Stark, 2010). The fact that the monetization of public debt is no longer an option in EMU does not appear to have changed policymaker and central banker’s rhetoric.

  9. For a full description of the two Eurobarometer questions for the periods 1984–1993 and 2003–2006 see the Appendix. If we take only either one of the two waves of data for our estimations (thus having one constant question) the results still hold.

  10. Interestingly, the correlations between ‘economic orthodoxy’ with ‘left’, ‘right’ and ‘centre’, which account for the distribution of power (see matrix P of variables above), are −0.2, −0.03 and 0.26, respectively.

  11. Of all the relevant variables available in the Manifesto data set, one additional variable could be considered a potential proxy. ‘Keynesian Demand Management’ shows the percentage of sentences (with respect to the overall number of sentences) in the parties’ election programs that comprised ‘Demand-oriented economic policy; economic policy devoted to the reduction of depressions and/or to increase private demand through increasing public demand and/or through increasing social expenditures’. However, for most countries it stays almost constant for the entire period of analysis (1984–2006). Overall, 6 countries out of 10 in our data set have 6 or less non-zero observations for the entire series of 22 observations (the other values being zeros). Such an invariant proxy is bound to yield non-reliable results. For that reason this variable is left out of the analysis.

  12. The structure of the panel data set is unbalanced as several years of data for Spain (1984–1989) and Portugal (1984–1994) are missing.

  13. All tests carried out in the section are done at the 10 per cent significance level.

  14. We also ran a simple AR(1) process that displays an R2 of 0.28. This shows that the additional macroeconomic variables we use have a significant scope in explaining our dependent variable. All additional analyses, alternative model specifications and estimates mentioned in this article are available from the authors on request.

  15. As a robustness check, we also used an alternative variable to ‘Maastricht’ inspired by Hallerberg et al (2007) which is a measure of the lagged fiscal convergence (deficit to GDP ratio – 3 per cent) when deficit stood above the 3 per cent threshold and 0 otherwise for the years 1992–1997. Results are similar.

  16. Alternatively we created subsamples for which we observe only positive values of our dependent variable Δdebt (113 observations) and for negative values (96 observations). The smaller sample of 102 observations, when we include our variables for Stability Culture, leaves us with two subsamples of 66 and 36 observations (for positive and negative values, respectively). These are deemed to small to carry out the analysis and so our robustness checks are done without the Stability Culture variables. The results with both subsamples (not shown but available upon request) indicate that the variable SGP has no significant impact across specifications whether the country is in a ‘good or bad’ fiscal period. Our main conclusion is reinforced by these robustness checks.

  17. We use the Stata command xtpcse with the option ‘pairwise’, as our panel data set is unbalanced.

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Acknowledgements

We are grateful to Jacques Melitz and Julia Darby. Thanks are also due to Chad Damro, Iain Hardie, David Howarth, Ben Rosamond and Tal Sadeh for their helpful comments. All remaining errors are ours.

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Correspondence to Philippe LeMay-Boucher.

Appendices

Appendix A

Econometric Issues

The existence of several binary dummy variables of interest renders the use of a common panel data estimator, with fixed or random effects to capture the cross-sectional heterogeneity, impossible. Moreover, the model employed includes institutional and political variables that tend to be constant, or not varying considerably over time. Therefore, a pooled cross-section analysis is necessary and will be based on the conventional estimation technique of OLS.

A preliminary test indicates that the estimates suffer from heteroskedasticity, which does not come as a surprise. The standard errors are corrected for group-wise heteroscedasticity and contemporaneous correlation across countries of the errors with panel-corrected standard errors.Footnote 17 Contemporaneous macro-variables are interlinked. Output growth, the unemployment rate and the interest rate may be affected by contemporaneous fiscal shocks. This may create biases and raises additional doubts about the validity of the estimates.

To deal with this potential problem, we use the instrumental variables estimation technique. The macroeconomic variables are instrumented with the lag of these five variables: real GDP growth, output gap (defined as the difference between potential GDP and actual GDP), long-term interest rates, changes in unemployment rates and US long-term interest rates. These instruments are individually significant in the first stage; however, this does not in itself guarantee a successful identification in the second stage estimation. Hence, we use the Kleibergen-Paap rk F-statistic, a correspondingly robust version of the Cragg-Donald statistics to test for weak instruments. The combination of the five lagged variables listed above is selected since it provides the highest statistics (7.96 obtained for the baseline model). This value is between the Stock-Yogo weak ID test critical values for a 5 per cent and 10 per cent maximal IV relative bias. Despite the fact that the statistic is not particularly strong, we can consider that weak instruments are not a serious problem in our case. Furthermore, the Hansen J-statistics suggest that the instruments are not correlated with the error term at a 10 per cent level. The Kleibergen-Paap rk LM-statistics for overall identification allows us to strongly reject the null hypothesis that the equation is under-identified.

In sum, the results suggest the model used is reliable. We then proceed to compare the estimates, with and without instrumentation, in order to check if the macroeconomic variables suffer from endogeneity or not. In order to do this, we use the results obtained from the two-stage least squares (2SLS) using the STATA command ivreg2 with clusters (Baum et al, 2007). The results of the implemented test, defined as the difference of two Sargan-Hansen statistics, suggest that we cannot reject the null that the specified endogenous regressors can actually be treated as exogenous with a P-value of 0.33. It can also be argued that the Europeanization variable ‘SGP’ may be considered endogenous. For instrumenting this variable we use the debt level in 1997. This variable reflects the need for adequate fiscal measures and initiatives to meet the goals set in the SGP in the years to follow. The test shows that this variable can also be treated as exogenous. Consequently, we use only non-instrumented estimates for carrying out the inference. The results not shown from 2SLS can be obtained from the authors.

Appendix B

Table B1

Table B1 Variable definitions and data source

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LeMay-Boucher, P., Rommerskirchen, C. An empirical investigation into the Europeanization of fiscal policy. Comp Eur Polit 13, 450–470 (2015). https://doi.org/10.1057/cep.2014.1

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Keywords

  • fiscal policy
  • Europeanization
  • stability culture
  • economic and monetary union