Appendix 1. Nuts and Bolts of the Fiscal Council Dataset
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The paper has benefitted from useful comments by participants at the conference on “Fiscal Frameworks in Europe: Background and Perspectives” in Copenhagen on June 1st and 2nd, 2017, and the IMF – Fiscal Affairs Department weekly seminar series. Without implications, we are particularly grateful to Michael Bergman, Luc Eyraud, Vitor Gaspar, Lars Jonung, Martin Larch, Paolo Mauro, Wolfgang Reuter, Abdel Senhadji, Teresa Ter-Minassian, David Vines, and Charles Wyplosz. Sungwook Yoon provided valuable inputs at an early stage of this project. Wolfgang Reuter kindly shared data on compliance with fiscal rules.
Earlier initiatives include the European Union (EU) Commission’s database of independent fiscal institutions last updated in 2013 and covering only EU members.
That said, unlike veteran fiscal councils, recent institutions have not yet been put to the test of a full-blown crisis or other extreme event that typically challenges the credibility and resilience of even well-established institutional frameworks.
As the sample contains only EU countries, all countries have fiscal rules. For the real GDP forecasting error, the category of “fiscal rule, no fiscal council” includes 258 observations, and the category of “fiscal rule, fiscal council” includes 109 observations. For the primary balance forecasting error, the category of “fiscal rule, no fiscal council” includes 252 observations, and the category of “fiscal rule, fiscal council” includes 100 observations.
EU countries were differently affected by the recent debt crisis (as captured by 10-year government bond yields). The differentiated effects of the crisis on the various countries in the sample cannot be adequately captured by time or country effects.
A one-percentage point increase in the debt ratio lowers the forecast error by 0.02 percentage points on average.
Replacing the IFC dummy with dummies capturing IFCs with only certain characteristics, such as legal independence, safeguards on the budget, and other potential determinants of effectiveness does not allow identifying features that might be more influential than others.
The measure of noncompliance used here is crude as it ignores escape clauses and other provisions allowing deviations from numerical limits. This measurement error might bias the estimated IFCs’ impact downward so that our results are likely to capture a lower bound of IFC effectiveness.
The same test performed to assess the influence of a less optimistic growth forecast does not reject the null of no influence.