Ordinary least squares (OLS) estimates of the impact of gender on earnings are potentially biased owing to non-randomness in sample selection. In this note, OLS estimates are compared with the results of two methods that have been proposed to allow for these selection effects – first Heckman’s method and secondly a novel approach based on quantile regression promulgated by D’Haultfoeuille et al. (2018). Estimates are provided for 18 countries over a recent three year period. Differences between the results obtained using the alternative methods are highlighted and explained, with lessons drawn for the application of these techniques in future exercises.