There are many reasons to be concerned about existing gender inequalities across a range of labour market outcomes (such as labour supply, wages, occupations and/or unemployment) and in pre-labour market conditions (such as education or health) that have an effect on the labour market performance of the economy. It is clear that gender inequalities decrease women’s well-being at individual level. Without forgetting the importance of this point, however, we would like to focus interest on the effect of gender inequality on the economy wide performance, i.e. at the social level. Gender inequality will be inefficient at an aggregate level if it limits firms’ abilities to maximize their productive capacity.
There is an enormous literature on gender inequality of pay, but again very little literature on the relationship between gender inequality in pay and economic growth. The literature that does exist has not established an unambiguous relationship between pay gaps and growth. Some empirical evidence suggests that large gender earnings gaps, combined with high female labour force participation rates, encourages economic growth. To understand this empirical finding (and consider the implications for the longer run) it is important to be able to distinguish between inequality and discrimination (unequal treatment for men and women for the same characteristics), since it is discrimination which would have a linkage with productivity and consequently with growth. Based on Becker’s “taste for discrimination” or “statistical discrimination”, if there is a share of women, who are not hired due to discrimination (employment discrimination) a loss in productivity relative to the non-discriminatory employment level would occur.
Therefore, the aim of this project is to analyse in detail the different interactive dimensions of gender inequality, in particular, seeking to identify the interrelations between them. This project would be instrumented through a workshop that will put together the main international researchers on gender and labour-market covering different associated dimensions such us: wages, occupation, employment, mobility, education, time uses and health.