Gender Wage Gap: A Semi-Parametric Approach With Sample Selection Correction

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 incorporates sample selection. We describe a simulation algorithm to implement counterfactual comparisons of densities. The proposed methodology is used to investigate the gender wage gap in Italy. It is found that when sample selection is taken into account gender wage gap widens, especially at the bottom of the wage distribution. Explanations are offered for this empirical finding.gender wage gap;hazard function;sample selection;glass ceiling;sticky floor

The Trend over Time of the GenderWage Gap in Italy

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 increased. We identify the time trends of different components of the gender wage gap by estimating wage distributions in the presence of covariates and sample selection and by counterfactual microsimulations. We find that women swam against the tide: whilst the trend in female qualifications slightly reduced the gender wage gap, the gender relative trends in the wage structure significantly increased it.gender wage gap;counterfactual distributions;decompositions;hazard function;labour market reforms

Gender Wage Gap:A Semi-Parametric Approach With Sample Selection Correction

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 incorporates sample selection. We describe a simulation algorithm to implement counterfactual comparisons of densities. The proposed methodology is used to investigate the gender wage gap in Italy. It is found that when sample selection is taken into account gender wage gap widens, especially at the bottom of the wage distribution. Explanations are offered for this empirical finding

FDI in hot labour markets: The implications of the war for talent

This paper highlights an inherent contradiction that exists within investment promotion activities in rich countries. Since the financial crisis, many inward investment agencies have shifted their activities from job creation per se to seeking to attract investment in high-tech activities. Such knowledge-intensive sectors are engaged in what has become referred to as “the war for talent”, so locations need to understand their value proposition to firms, especially where labour is tight. This paper explores the implications of this, in terms of the impact on employment and earnings of high skilled labour. We show that, because skill shortages already exist in many of these sectors, seeking to attract inward investment in these sectors simply causes the earnings of such workers to be bid up, and employment in the incumbent sector to fall. We highlight the over-riding importance that firms place on the availability of skilled labour when determining locations, and how policies which promote labour market flexibility, particularly through investment in skills to address skill shortages, can significantly mitigate the adverse effects, which tend to be more keenly felt in poorer regions of Europe where skilled labour is in even shorter supply