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42. Jahrgang (2016), Heft 4
hence we include the Gini coefficient in our set of explanatory variables.
We find no statistically significant effect, however, we consider the income
share of the top 1% to be a better measure for personal income distribution
than the Gini coefficient, because it captures the tail of the distribution
where most of the increase in income inequality happened, while the Gini
coefficient is rather in-sensitive to changes in the tails. Furthermore, we
have less concern in the case of the income share of the top 1% with regard to endogeneity that naturally arises between a measure of functional
and personal income distribution that captures the whole population like
the Gini coefficient. Unfortunately there is no data on the income share of
the top 1% for Austria in The World Wealth and Income Database which is
why we revert to using the Gini for Austria, while we experiment with top income shares for the remaining countries in our sample.
5.4 After tax wage share
Our estimation result for the after tax wage share as the dependent variable strongly confirms our initial results for our main variables, although
the statistical significance of household debt is increased.58 Intermediate
imports, outward FDI and union density have the same effect across different samples. This implies that the effect of intermediate imports, outward
FDI and union density is similarly relevant for after tax wage share as for
the before tax wage share.
5.5 Economic effects
Finally, we report the economic significance of our variables for a specification including intermediate import penetration and union density (specification [3]) as well as a specification including all other variables (specification [8]) in Table 2. More precisely, we calculate the predicted change in
the dependent variable based on individual covariates by multiplying the
estimation coefficient of the respective explanatory variable with the crosssectional average change of that variable over the sample period and dividing by the change in the wage share.59, 60
The decline in the wage share, taken as an average over the two specifications, is 8.7 percentage points, similar to the decline in the country level
wage share which constituted 6.6 percentage points. Based on the estimation with union density (specification [3]) we find that union density had the
strongest impact in Austria, explaining 85.1 percent of the average decline
of the wage share. Increasing imports of capital and consumption goods
and the increase in capital intensity have had a sizeable positive effects.
Capital intensity had the second highest positive impact, predicting 16.5 of
the change in the wage share. Based on specification (8) we find a sizeable negative effect of household debt and, albeit much smaller in size, of ICT
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