Proceedings from the ECFIN Workshop "The budgetary implications of structural reforms" - Brussels, 2 December 2005



be accounted for in the econometric estimates by controlling for the impact of reforms undertaken
in other fields. Therefore, aggregate and stacked up datasets are used each in turn in the Probit
regressions below.

Probit estimates on aggregate data are presented in column 1 of Table 2.95 In order to
mitigate potential endogeneity problems and to account for the fact that policy decisions may
be reflected in the structural policy indicators with lags, most explanatory variables are lagged
one (crisis, fiscal and independent monetary policy variables) or more (unemployment
variable
96) periods. Both the fiscal and control variables have the expected signs and are
statistically significant. The probability of carrying out a structural reform in at least one of the
five fields considered is estimated to be higher the poorer the recent macroeconomic conditions,
the smaller the country size, the higher the level of the cyclically-adjusted fiscal position and the
smaller the change in the cyclically-adjusted primary fiscal balance. Taking into account that the
scale of the explanatory variables differs, the size of the estimated coefficients -as measured in
Table 2 by the marginal probabilities under parentheses- seems to imply that the largest impact on
the propensity to reform would arise from the prevalence of an economic crisis and the size of the
country, but the estimated effects of the fiscal variables are also far from negligible.

However, while Australia has the third lowest trade openness ratio in the OECD area (after the United States and Japan), the Netherlands has the
third highest (after Belgium and Ireland). This suggests that Australia should be classified as a large country and the Netherlands as a small one.

95.Logit estimates yield (qualitatively) similar results.

96.Unemployment being a highly auto-correlated variable, several alternative lags were statistically significant in the regressions. Here we selected
the number of lags which maximized the t-statistic of the unemployment rate variable (3 periods).

194



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