Returns to Education and Gender Wage Gap Across Quantiles in Italy

Abstract

Various quantile regression approaches are implemented to analyze the
characteristics of Italian data on earnings in the tails. A changing coefficients
pattern across quantiles shows increasing returns to education along the wage
distribution. A quantile decomposition approach shows that higher education
grants higher return at all quantiles, thus implying additional, non-linear returns
to higher education throughout the entire pattern of the earning distribution.
Wage gender gap displays a decreasing pattern across quantiles, and it does
not disappear at the higher quantiles. The southern workers penalty decreases
across quantiles as well for highly educated workers.