Abstract:

Over the last few decades, a growing body of research has been giving evidence of a favourable impact of education on personal earnings, income distribution and, more generally, on the economic performance of a country. As a result, it might seem at first glance that balancing between quality and quantity in education is a key force that can speed up the economic growth of a country, enhance its income distribution, promote social mobility and upgrade standards of living.

In this field, the paper aims at evaluating the role of formal education in generating individual earnings with special focus on the relationship between returns to education and income inequality and the likely causes of this relationship. The comparative analysis, drawn upon the EU-SILC data, involves 27 European countries in the light of the variety of national schooling systems, in terms of stratification-standardization framework and vocational specificity, and welfare regimes. The study is carried out in a longitudinal perspective (2007-2010) and is focused on all workers, aged 18-65, employees and self-employed, irrespective of their activity sector, who have been continuously and successfully interviewed from 2007 to 2010.

More precisely, two specific objectives are envisaged to be achieved. Firstly, the potential of EU-SILC balanced micro-panel is exploited by random effects models through which log-earnings equations are estimated for recovering the returns to education; a semi-log functional form is informed by extensions of the Mincerian human capital model in order to also identify other factors that are likely to explain differences in generating income. Secondly, the ANOGI (Analysis of Gini) decomposition is performed by educational level in order to evaluate the contribution of each educational subgroup (i.e., individuals with the same formal educational attainment) to the overall income inequality and to assess the degree to which each sub-population is stratified, i.e., how different a group’s members are from members of other educational groups.

The results show that the increase in income inequality is partially accounted for by the returns to education; as they say, beside explaining personal earnings all over Europe, the formal education also strongly contributes to income differentials since the rates of returns unequally impact on the conditional earnings distribution. Moreover, despite their heterogeneity across countries, these rates increase with the educational level and a clear positive detachment in favour of the more stratified groups of the highest-educated workers exists for the most countries. Indeed, the between-groups inequality (i.e., inequality among educational groups depending on the distance between the mean income of the same sub-populations) accounts for a much higher share of total inequality as opposed to other covariates (i.e., gender, marital status, age, employment status and contract, type of profession).

In short, greater rewards to education seem to be directly associated with higher levels of income inequality and ranking countries along these two (and other) dimensions (i.e., from the well-developed countries of North Europe to the more-unequal Mediterranean and Eastern States rather than the more controversial Central countries) permit assessing the quality of national policies in the light of the institutional differences in order to address the possibility of making changes.

Keywords:

Income-generating, returns to education, ANOGI.