Gender wage and employment gaps are negatively correlated across countries. We argue that non-random selection of women into work explains an important part of such correlation and thus of the observed variation in wage gaps. The idea is that, if women who are employed tend to have relatively high-wage characteristics, low female employment rates may become consistent with low gender wage gaps simply because low-wage women would not feature in the observed wage distribution. We explore this idea across the US and EU by estimating gender gaps in potential wages. We recover information on wages for those not in work in a given year using alternative imputation techniques. Imputation is based on (i) wage observations from other waves in the sample, (ii) observable characteristics of the nonemployed and (iii) a statistical repeated-sampling model. We then estimate median wage gaps on the resulting imputed wage distributions, thus simply requiring assumptions on the position of the imputed wage observations with respect to the median, but not on their level. We obtain higher median wage gaps on imputed rather than actual wage distributions for most countries in the sample. However, this difference is small in the US, the UK and most central and northern EU countries, and becomes sizeable in Ireland, France and southern EU, all countries in which gender employment gaps are high. In particular, correction for employment selection explains more than a half of the observed correlation between wage and employment gaps.
median gender gaps sample selection wage imputation