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Inequality in workers’ lifelong learning across european countries: Evidence from EU-SILC data-set

Biagetti, Marco and Scicchitano, Sergio (2009): Inequality in workers’ lifelong learning across european countries: Evidence from EU-SILC data-set.

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Abstract

The primary purpose of this paper is to explore the potential for EU-SILC data to deepen our understanding of the determinants of inequality in workers’ formal life-long learning (LLL) in Europe. In particular we investigate the incidence of personal, job-specific and firm-specific characteristics on the workers’ probability to undertake adult learning. To do so, we first estimate LLL incidence in the whole sample for men and women. Then we estimate separate 21 country-specific equations, for both sexes. This method allows to investigate cross-country gender differences and avoid unobserved heteroscedasticity due to sex, which we clearly find in the data. For the whole sample the results show that, for both men and women, formal LLL incidence is significantly higher among young, better educated, part-time and temporary workers, and lower among those who changed current job in the last year, employed in small firms and having low-skilled occupations. Furthermore, some gender differences for the whole sample emerge. When estimating separate equations for each country and for both sexes, a significant cross-country heterogeneity and a weaker significance of the coefficients come to light. In particular, a couple of relevant results emerge for Scandinavian countries with regard to the complementarity between past level of education and current adult learning. Finland is the only country in the sample in which, for both men and women, less educated workers are more likely to undertake formal LLL, thus making adult learning system able to avoid, for both men and women, existing inequality in human capital, as it results from education levels. Denmark is the only country where, for women, being less educated turns out to be the predictor with the greatest significant magnitude of the effect in the variation of the probability.

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