The news from a few weeks ago remarked on the 50th anniversary of the Equal Pay Act. Predictably, much of the reporting focused on the fact that women only earn 77 cents for every dollar that a man earns:
Unfortunately, five decades later, women still earn an average of 77 cents for every dollar earned by a man. For African-American and Hispanic women it’s even lower: 64 and 54 cents, respectively.
And just as predictably, democrats rushed to submit new legislation:
The disparity led Sen.r Kirsten Gillibrand, D-N.Y., to co-sponsor an update to the law, called the Paycheck Fairness Act, along with a number of other female senators.
“We believe this is an economic issue. It’s not only about women but the middle class, and if you’re not paying a woman dollar for dollar for the exact same work you’re not really tapping the full potential of the economy,” said Gillibrand on “CBS This Morning.” “And why wouldn’t you tap the full potential of 52 percent of the resources of the women of this country? “If you paid women for dollar for dollar, you could raise the GDP by up to 9 percent.”
But is it true? Are women really paid 77% of a man’s salary?
Payscale controlled for a variety of factors and found that the pay gap is far narrower among men and women who have similar levels of experience, work in the same fields and locations, have the same skills and certifications and are otherwise workplace clones. Among non-managerial workers, Payscale found no pay gap at all, on an apples-to-apples basis. At more senior levels, women do earn slightly less than men, but the biggest gap was only 8.5% — far lower than the frequently mentioned 23%. And that gap may exist because top male executives put in more hours, travel more and spend more time with clients than their female counterparts, which is hard to measure among salaried employees.
In certain sectors there is no gap. In other sectors where there is a gap, it can be explained by other factors including the amount of time put in at the office. Or a requirement that an individual travel.
Other reasons exist:
As other pay experts have pointed out, women tend to earn less overall because they are more likely to work in fields such as health care, education and social work that pay less than male-dominated fields such as vocational trades, engineering and financial services. But women don’t go into the workforce blindly, and they often know the tradeoffs.
“Women consider a lot of factors and not just monetary benefits,” points out Katie Bardaro, lead economist for Payscale. “Many women choose jobs with a certain level of flexibility.”
Women work different jobs than men. A sure sign that this is true? Check the workplace mortality figures one day. Try to explain why men are dying on the job at rates significantly higher than women.
Finally, if you really wanna see a proponent of legislation akin to Ms. Gillibrand squirm, ask them for legislation that would create equality in college. Women are earning significantly more college degrees. Not just bachelor degrees, but advanced degrees as well. Ask them to explain the inequity there.
And listen to their answer.
And that gap may exist because top male executives put in more hours, travel more and spend more time with clients than their female counterparts, which is hard to measure among salaried employees.
I’m pretty suspicious of anyone who finds a 8 point pay gap and dismisses it as inconsequential because he can make up reasons why it could exist.
And then you look at the methodology they use to reach that answer:
In order to provide an apples-to-apples comparison, we determine the characteristics of the typical man within a job and then adjust the characteristics of the typical woman in the same job to match those of the average man. The result is the median pay calculated for the average woman if they had the exact same breakdown of compensable factors as the average man.
I’ve taken a number of courses in stats, math, etc. over the years, and I have no idea what they’re talking about. What do they mean by “adjust the characteristics of the typical woman”? It really sounds like they were fudging data a bit in order to generate something “interesting” so people would flock to their website. I’m not seeing any defensible methodology here to justify their findings.