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

Author

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  • Geraint Johnes

    (Lancaster University Management School)

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.

Suggested Citation

  • Geraint Johnes, 2019. "Selection trials: comparing approaches for correcting sample selection bias in evaluating the gender wage gap," Economics Bulletin, AccessEcon, vol. 39(4), pages 2746-2750.
    • Handle: RePEc:ebl:ecbull:eb-19-01041
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    File URL: http://www.accessecon.com/Pubs/EB/2019/Volume39/EB-19-V39-I4-P256.pdf
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    More about this item

    Keywords

    gender; wage differential; sample selection;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • J7 - Labor and Demographic Economics - - Labor Discrimination

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