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Vertical effects of fiscal rules: the Swiss experience

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Abstract

Formal fiscal rules have been introduced in many countries throughout the world. While most studies focus on the intra-jurisdictional effects of fiscal rules, vertical effects on the finances of other levels of government have yet to be explored thoroughly. From a theoretical point of view, vertical effects could work in opposite directions, i.e., improve and burden other levels’ finances. This paper is the first formally investigating the influence of Swiss debt brakes, which primarily target the cantonal level, on municipal finances. A difference-in-differences estimation (two-way fixed effects) of aggregated and disaggregated local panel data provides unique evidence that suggests little effect of budget constraints at the cantonal level on average municipal finances and fiscal decentralization. The results are confirmed by a wide range of robustness tests. If anything, cantonal debt brakes are associated with improved local finances and fiscal centralization. These findings run counter to popular fears and emphasize the possibility of positive spillover effects of fiscal rules.

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Fig. 1

Source own illustration based on Feld et al. (2017) and own research

Fig. 2

Source own illustration

Fig. 3

Source own illustration based on data from Swiss Federal Finance Administration and Statistical Yearbooks of the Swiss Association of Cities

Fig. 4

Source Own calculations

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Notes

  1. Petra Roth (then President of the German Association of Cities and mayor of Frankfurt am Main) stated in 2011 that communities needed a protective shield, which prevented the German states (Laender), in complying with their debt brakes, from shifting public debt to their municipalities, thus deteriorating local finances.

  2. To be precise, the first sample covers municipalities from all cantons except for Basel City.

  3. For the relationship between fiscal rules and macroeconomic stability, see, e.g., Sacchi and Salotti (2015).

  4. For various guises of fiscal gimmickry, refer to Irwin (2012).

  5. Article 50 as set out in the Swiss Constitution of 1999 states: “The autonomy of the communes is guaranteed in accordance with cantonal law. The Confederation shall take account in its activities of the possible consequences for the communes. In doing so, it shall take account of the special position of the cities and urban areas as well as the mountain regions.”

  6. See Art. 33 and Art. 34 model law for cantonal budgeting 2015, available from http://www.srs-cspcp.ch/sites/default/files/pages/fe_20-2.pdf (accessed 06 March 2017).

  7. A broad overview of cantonal budget rules is provided by Stauffer (2001) and more recently by Conference of Cantonal Ministers of Finance (2012) and Waldmeier and Mäder (2015).

  8. For transmission channel (4) see Nice (1991). The channel (5) is based on vertical effects of direct democratic institutions as stated by Funk and Gathmann (2011). While cantonal debt brakes could also influence federal finances through similar transmission channels, we expect downward effects to dominate, given the design of the Swiss federal framework. Furthermore, vertical transmissions can principally take place independently of whether the cantonal debt brake targets exclusively on cantonal finances or on both cantonal and municipal finances (e.g., by means of transmission channel 1 or 2). However, we exclude the five cantonal debt brakes that apply to the cantonal level and, at least partly, to the municipal level in a robustness test in Sect. 6.

  9. We refrain from including observations after 2007 in the second sample due to a profound revision in reporting and accounting standards (see Swiss Federal Finance Administration 2016). This issue is mitigated in the first sample since the Swiss Federal Finance Administration recalculated data for 1990–2007 using the new standards and supported us in finding data for 1980–1989 that is largely consistent with the new standards. Furthermore, while the Swiss Federal Statistical Office defines municipalities (communities) with a population size above 10,000 as cities, we do not differentiate between the terms.

  10. Spending (revenue) decentralization is measured by the ratio of local spending (revenue) in a canton to local and cantonal spending (revenue) in that canton, i.e., (Local/[Cantonal \(+\) Local]). While the two ratios do not allow to differentiate between deconcentration, delegation and devolution, spending in the different categories can be seen as a simplified distinction between the different types of municipal expenditure (e.g., delegation in the field of environment and devolution in the field of education). As the second dataset covers only a few (in some cases only one) municipalities from each canton, we lack an adequate decentralization measure and, thus, analyze the effect of fiscal rules on decentralization only with respect to the first sample that covers all municipalities within a canton.

  11. Refer to this literature for a broader discussion of our control variables.

  12. A direct influence of the level of unemployment on municipal finances is unlikely since unemployment insurance is financed by a federal payroll tax and benefits are regulated by state and cantonal authorities. However, the unemployment rate can be used as a proxy for welfare spending (partly) paid for by the local level of government.

  13. Deviating from our identification strategy, the robustness analysis provides the results of models without fixed effects. Simplified, the difference-in-differences estimator can be written as:

    $$\begin{aligned} \hat{{\ss }}= & {} (\bar{y}^{\text {treatment units after treatment }}-\bar{y}^\text {treatment units before treatment}) - (\bar{y}^\text {control units after treatment }\\&-\bar{y}^\text {control units before treatment}). \end{aligned}$$

    .

  14. Results could only be obtained for the first sample, as the highly unbalanced second sample provides too few common observations across the panel to perform the test.

  15. The wild-cluster bootstrap-t procedure resamples clusters of residuals obtained from regressions which impose the null hypothesis (ß = 0) and reestimates the original equation with the newly generated residuals. The pseudo-samples of clusters are formed by multiplying the residuals with 1 and −1 with a probability of 0.5. The so-called Rademacher weight provides asymptotic refinement. See Cameron et al. (2008) for details. We employ the Stata post-estimation command bootwildct written by Bansi Malde with 1,000 repetitions.

  16. Note that a canton might face a shock although its books are balanced. This could be the case if a canton expects a budget surplus (deficit) and faces a deficit (surplus) shock. Furthermore, the definition of a fiscal shock implicitly assumes that the fiscal year’s budget forecasts are not (strategically) biased. We are grateful to Christoph Schaltegger for providing us with data on expected and actual current income and expenses for the years 1984–1998. From 1999 onwards, the data source is the Conference of Cantonal Ministers of Finance.

  17. The interpretation of the interaction terms is based on marginal effects as suggested by Brambor et al. (2006).

  18. The median regression estimates the 0.5 quantile of the dependent variable rather than the mean in ordinary regressions. This minimizes the sum of the absolute residuals. Median regression is, thus, more robust to outliers in observations and the results are valid even if the errors are not independent and identically distributed. Cook’s distance is the accumulated change in the estimated coefficients if a particular observation is excluded. We follow a rule of thumb and discard observations with a Cook’s distance greater than 4/N (where N is the number of observations in the sample).

  19. The number of municipalities is not significant in any equation. We further test whether the power of local governments influences vertical effects by interacting the number of municipalities with the debt brake dummy. However, neither the interaction term nor its constitutive terms obtain significance (results available upon request).

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Acknowledgements

We would like to thank Gerrit Gonschorek, Emma Karslake and Leonardo Palhuca for their valuable research assistance and Christoph Schaltegger for providing us with cantonal data on realized and forecasted revenue and expenditure. We are grateful to Martina Neuhaus from the Swiss Federal Department of Finance for providing us with the best data available on local finances.

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Authors and Affiliations

  1. Walter Eucken Institute, University of Freiburg, Goethestr. 10, 79100, Freiburg, Germany

    Heiko T. Burret & Lars P. Feld

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  1. Heiko T. Burret
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Correspondence to Lars P. Feld.

Appendix

Appendix

Table 7 Descriptive statistics in total and by institutional regime, whole periods
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Table 8 Definition and source of variables
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Table 9 Baseline regression of sample 1: expenditure categories in all municipalities, 1990–2011
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Table 10 Baseline regression of sample 2: expenditure categories in 139 large municipalities, 1982–2007
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Fig. 5
figure 5

Development of local finances in the control and treatment groups. a Sample 1: Debt per capita. b Sample 1: Revenue per capita. c Sample 1: Expenditure per capita. d Sample 2: Debt per capita. e Sample 2: Revenue per capita. f Sample 2: Expenditure per capita. In the interest of clarity, data of the 139 municipalities (sample 2) are aggregated at the level of the corresponding canton. The control group includes municipalities that are located in cantons without a debt brake during the whole period 1980–2010 (sample 1) and 1982–2010 (sample 2). Since the treatment took place at different points in time (year of debt brake introduction in parentheses), various treatment groups are depicted. The development of local finances in the treatment groups is only shown prior to treatment. All values are in real terms

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Table 11 Pre-estimation test on cross-sectional dependence
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Table 12 Reduced form regression of sample 1: local finances aggregated at the cantonal level, 1980–2011
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Table 13 Reduced from regression of sample 2: local finances of 139 large municipalities, 1982–2007
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Table 14 Robustness tests part I: Placebo regressions, 1980–2011
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Table 15 Robustness tests part III: further modifications
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Burret, H.T., Feld, L.P. Vertical effects of fiscal rules: the Swiss experience. Int Tax Public Finance 25, 673–721 (2018). https://doi.org/10.1007/s10797-017-9467-y

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