Wage inequality and returns to schooling in Europe: a semi-parametric approach using EU-SILC data

In this paper we apply a semi-parametric approach (quantile regression - QR) to the last 2007 wave of the EU-SILC data set, in order to explore the connection between education and wage inequality in 8 European countries. We find that wages increase with education and this holds true across the whole distribution. Furthermore, this effect is generally more important at the highest quantiles of the distribution than at the lowest, implying that schooling increases wage dispersion. This evidence is found to be rather robust as showed through tests of linear hypothesis. We also corroborate the idea that, although OLS coefficients estimates are substantially in line with the QR’s, the former technique really misleads relevant information about cross-countries heterogeneity in the impact of education on within group inequality at different points of the wage distribution. Hence this paper confirms that a semi-parametric QR approach is more interesting, as well as more appropriate, because it measures the wage effect of education at different quantiles, thus describing relevant cross-countries changes or bounces not only in the location, but also in the shape of the distribution.