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Selection trials: comparing approaches for correcting sample selection bias in evaluating the gender wage gap

Research output: Contribution to journalJournal article

<mark>Journal publication date</mark>8/12/2019
<mark>Journal</mark>Economics Bulletin
Issue number4
Number of pages5
Pages (from-to)2746-2750
Publication statusPublished
Original languageEnglish


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.