Data Point: Wage Gap - not what things seem - Granite Grok

Data Point: Wage Gap – not what things seem

Female vs Male earnings

Brief snippet from the text accompanying the above graph (Federal Bureau of Labor Statistics paper here) (emphasis mine below):

1. Among full-time workers (those working 35 hours or more per week), men were more likely than women to work a greater number of hours (see Table 5). For example, 25.5% of men working full-time worked 41 or more hours per week in 2013, compared with only 14.3% of women who worked those hours, …

2. The BLS reports that for full-time single workers who have never married, women earned 95.2% of men’s earnings in 2013, which is a wage gap of only 4.8% (see Table 1 and chart above), compared to an overall unadjusted pay gap of 17.9% for workers in that group. When controlling for marital status and comparing the earnings of unmarried men and unmarried women, almost 75% of the unadjusted 17.9% wage gap is explained by just one variable (among many): marital status.

3. Also from Table 1 in the BLS report, we find that for married workers with a spouse present, women earned only 78.0% of what married men with a spouse present earned in 2013 (see chart). Therefore, BLS data show that marriage has a significant and negative effect on women’s earnings relative to men’s, but we can realistically assume that marriage is a voluntary lifestyle decision, and it’s that personal choice, not necessarily labor market discrimination, that contributes to much of the gender wage gap for married workers.

4. Also in Table 1, the BLS reports that for young workers ages 25-34 years, women earned 89.4% of the median earnings of male full-time workers for that age cohort in 2013. Once again, controlling for just a single important variable – age – we find that almost half of the overall unadjusted raw wage gap for all workers (17.9%) disappears for young workers.

5. In Table 7, the BLS reports that for full-time single workers with no children under 18 years old at home (single workers includes never married, divorced, separated and widowed), women’s median weekly earnings were 96.1% of their male counterparts (see chart).  For this group, once you control for marital status and children, you automatically explain almost 80% of the unadjusted gender earnings gap.

6. Also in Table 7, the BLS reports that married women (spouse present) working full-time with children under 18 years at home earned 78.9% of what married men (spouse present) earned working full-time with children under 18 years (see chart). Once again, we find that marriage and motherhood have a significantly negative effect on women’s earnings; but those lower earnings don’t necessarily result from labor market discrimination, they more likely result from personal family choices about careers, workplace flexibility, child care, and hours worked, etc.

7. If we look at median hourly earnings, instead of median weekly earnings, the BLS reports in Table 8 that women earned 86.6% of what men earned in 2013, which accounts for about 25% of the raw 17.9% gender earnings gap that exists for weekly earnings. And when we look at young workers, women ages 16 to 19 years earned 96.7% of the hourly wage of their male counterparts in 2013, and for the 20-24 year old group, women earned 94.0% of what men earned per hour…

Bottom Line: When the BLS reports that women working full-time in 2013 earned 82.1% of what men earned working full-time, that is very much different than saying that women earned 82.1% 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. 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

(H/T: AEIdeas)

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