We analyse gender wage inequalities in Italy in the mid-1990s and in the mid-2000s. In this period important labour market developments occurred: institutional changes have loosened the use of flexible and atypical contracts; the female employment rates and educational levels have substantially...

Abstract: This paper studies the gender wage gap by educational attainment in Italy using the 1994–2001 ECHP data. We estimate wage distributions in the presence of covariates and sample selection separately for highly and low educated men and women. Then, we decompose the gender wage gap...

Sizeable gender differences in employment rates are observed in many countries. Sample selection into the workforce might therefore be a relevant issue when estimating gender wage gaps. This paper proposes a new semi-parametric estimator of densities in the presence of covariates which...

This paper studies the gender wage gap by educational attainment in Italy using the 1994–2001 ECHP data. We estimate wage distributions in the presence of covariates and sample selection separately for highly and low educated men and women. Then, we decompose the gender wage gap across all the...

We show non-parametric identification of lagged duration dependence in mixed proportional hazard models for duration data, in the presence of competing risks and consecutive spells. We extend the results to the case in which data provide repeated realizations of consecutive spells competing...

We study the identification of a mixed proportional hazard model with lagged duration dependence when data provide multiple outcomes per stratum. Within strata variation is exploited to non-parametrically identify lagged duration dependence in more general models than in the literature.

This paper studies the gender wage gap by educational attainment in Italy using the 1994–2001 ECHP data. We estimate wage distributions in the presence of covariates and sample selection separately for highly and low educated men and women. Then, we decompose the gender wage gap across all the...