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Selection trials: comparing approaches for correcting sample selection bias in evaluating the gender wage gap
| Content Provider | Semantic Scholar |
|---|---|
| Author | Johnes, Geraint |
| Copyright Year | 2019 |
| Abstract | 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. |
| Starting Page | 2746 |
| Ending Page | 2750 |
| Page Count | 5 |
| File Format | PDF HTM / HTML |
| Volume Number | 39 |
| Alternate Webpage(s) | https://eprints.lancs.ac.uk/id/eprint/139343/1/D_Haultefoeuille.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
