Details in BLS report suggest that the ‘gender earnings gap’ can be explained by age, marital status, children, hours worked, etc.

Link: https://www.aei.org/carpe-diem/details-in-bls-report-suggest-that-the-gender-earnings-gap-can-be-explained-by-age-marital-status-children-hours-worked-etc/

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Excerpt:

Let’s investigate the claim that the gender pay gap is a result of discrimination by looking at some of the data on wages and hours worked by gender and by marital status and age in the BLS report for 2020:

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Comment: Because men work more hours on average than women, some of the raw earnings gap naturally disappears just by simply controlling for the number of hours worked per week, an important factor not even mentioned by groups like the National Committee on Pay Equity. For example, women earned 82.3% of median male earnings for all workers working 35 hours per week or more in 2020, for a raw, unadjusted pay gap of 17.7% for all full-time workers. But for those workers with a 40-hour workweek (more than three-quarters of all full-time female workers), women earned 87.4% of median male earnings, for a smaller pay gap of only 12.6% (see chart and Table 1). Therefore, once we control only for one variable – hours worked – and compare men and women both working 40-hours per week in 2020, almost one-third (5.1 percentage points) of the raw 17.7% pay gap reported by the BLS for full-time workers disappears.

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Bottom Line: When the BLS reports that women working full-time in 2020 earned 82.3% of what men earned working full-time, that is very much different from saying that women earned 82.3% of what men earned for doing exactly the same work while working the exact same number of hours in the same occupation, with exactly the same educational background and exactly the same years of continuous, uninterrupted work experience, and with exactly the same marital and family (e.g., number of children) status. As shown above, once we start controlling individually for the many relevant factors that affect earnings, e.g., hours worked, age, marital status, and having children, most of the raw earnings differential disappears. In a more comprehensive study that controlled for all of the relevant variables simultaneously, we would likely find that those variables would account for nearly 100% of the unadjusted, raw earnings differential of 17.7% for women’s earnings compared to men as reported by the BLS. Discrimination, to the extent that it does exist, would likely account for a very small portion of the raw 17.7% gender earnings gap.

Author(s): Mark J. Perry

Publication Date: 22 Oct 2021

Publication Site: AEI