Gender pay gap nearly explained in full, but the discrimination narrative lives on

10 Dec

From Mark Perry:

bls

According to a TV election ad in 2012, “President Obama knows that women being paid 77 cents on the dollar for doing the same work as men isn’t just unfair, it hurts families.” Do the data support the president’s claim? Not at all.

For example, the Bureau of Labor Statistics (BLS) releases an annual report on the “Highlights of Women’s Earnings” (since the BLS report actually looks equally at data for both men’s and women’s earnings, one might ask why the report isn’t simply titled “Highlights of Earnings in America?”, but maybe that’s a politically incorrect question). Here’s the opening paragraph from the most recent BLS report “Highlights of Women’s Earnings in 2013” that was released this week:

 In 2013, women who were full-time wage and salary workers had median usual weekly earnings of $706. On average in 2013, women made 82.1 percent of the median weekly earnings of male full-time wage and salary workers ($860). In 1979, the first year for which comparable earnings data are available, women earned 62 percent of what men earned.

How do we explain the 23% gender pay gap claimed by Obama, or the fact that women working full-time earned only 82.1 cents for every dollar men earned in 2013 according to the BLS? Here’s how the National Committee on Pay Equity explains it:

The wage gap exists, in part, because many women and people of color are still segregated into a few low-paying occupations. Part of the wage gap results from differences in education, experience or time in the workforce. But a significant portion cannot be explained by any of those factors; it is attributable to discrimination. In other words, certain jobs pay less because they are held by women and people of color.

Let’s investigate the claim that the gender pay gap is a result of discrimination by looking at some of the wage data by gender in the BLS report for 2013:

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, meaning that men working full-time last year were almost twice as likely as women to work 41 hours per work or more. Further, men working full-time were also more than twice as likely as women to work 60-hour weeks: 6.3% of men worked 60 hours per week in 2013 compared to only 2.7% of women working full-time who worked those hours.

Also, women were more than twice as likely as men to work shorter full-time workweeks of 35 to 39 hours per week: 12.2% of women worked those hours in 2013, compared to only 5% of men who did so.  Although not reported by the BLS, I estimate using their data that the average workweek for full-time workers last year was 41.4 hours for women and 43.4 hour for men;therefore, the average man working full-time worked 2 more hours per week in 2013 compared to the average woman.

Comment: Because men work more hours on average than women, some of the raw wage 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 82.5% of median male earnings for all workers working 35 hours per week or more, for a raw, unadjusted pay gap of 17.5% for full-time workers (Table 5). But for those workers with a 40-hour workweek, women earned 89.6% of median male earnings, for a pay gap of only 10.4%. Therefore, once we control only for one variable – hours worked – and compare men and women both working 40-hours per week in 2013, almost half of the raw 17.5% pay gap reported by the BLS disappears.

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. Also in Table 8, we see that for never married hourly workers of all ages, women earned 92.7% of the hourly earnings of their male counterparts in 2013, which explains almost half of the unadjusted 13.4% gender difference in hourly earnings.

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. In a more comprehensive study that controlled for all of the relevant variables simultaneously, we would likely find that those variables would account for almost 100% of the unadjusted, raw earnings differential of 17.9% lower earnings for women reported by the BLS. Discrimination, to the extent that it does exist, would likely account for a very small portion of the raw gender pay gap.

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