I almost posted about this last month when “Equal Pay Day” happened. Instead, I sat back on the lookout for a good explanation of why the “fact” that “women only make 77 cents for every dollar a man makes” is meaningless. There were a ton of excellent take downs by pointing out all sorts of variables that weren’t controlled for. This is fine, but the reason the number is meaningless is so much more obvious.
Now, this blog talks about math and statistics a lot, so I felt somewhat obligated to point this out. Unfortunately, this topic is politically charged, and I’ve heard some very smart, well-intentioned people repeat this nonsense who should know better. This means bias is at work.
Let’s be clear before I start. I’m not saying there is no pay gap or no discrimination. This post is only about the most prominent figure that gets thrown around: 77 cents for every $1 and why it doesn’t mean what people want it to mean. This number is everywhere and still pops up in viral videos monthly (sometimes as “78” because they presume the gap has decreased?):
I include this video to be very clear that I am not misrepresenting the people who cite this number. They really propagate the idea that the number means a woman with the same experience and same job will tend to make 77% of what a man makes.
I did some digging and found the number comes from this outdated study. If you actually read it, you’ll find something shocking. This number refers to the median salary of a full-time, year round woman versus the median salary of a full-time, year round man. You read that right: median across everything!!
At this point, my guess is that all my readers immediately see the problem. In case someone stumbles on this who doesn’t, let’s do a little experiment where we control for everything so we know beyond all doubt that two groups of people have the exact same pay for the same work, but a median gap appears.
Company A is perfectly egalitarian. Every single employee gets $20 an hour, including the highest ranking people. This company also believes in uniforms, but gives the employees some freedom. They can choose blue or green. The company is a small start-up, so there are only 10 people: 8 choose blue and 2 choose green.
Company B likes the model of A, but can’t afford to pay as much. They pay every employee $15 an hour. In company B it turns out that 8 choose green and 2 choose blue.
It should be painfully obvious that there is no wage gap between blue and green uniformed people in any meaningful sense, because they are paid exactly the same as their coworkers with the same job. Pay is equal in the sense that everyone who argues for pay equality should want.
But, of course, the median blue uniform worker makes $20/hour whereas the green uniform worker only makes $15/hour. There is a uniform wage gap!
Here’s some of the important factors to note from this example. It cannot be from discriminatory hiring practices, because the uniform was chosen after being hired. It cannot be that green uniform people are picking lower paying jobs, because they picked the uniform after picking the job. It cannot be from green uniforms wanting to give up their careers to go have a family, because we’ll assume for the example that all the workers are single.
I’ll reiterate, it can’t be from anything, because no pay gap exists in the example! But it gets worse. Now suppose that both companies are headed by a person who likes green and gives a $1/hour raise to all green employees. This means both companies have discriminatory practices which favor green uniforms, but the pay gap would tell us that green are discriminated against!
This point can’t be stated enough. It is possible (though obviously not true based on other, narrower studies) that every company in the U.S. pays women more for equal work, yet we could still see the so-called “77 cent gender wage gap” calculated from medians. If you don’t believe this, then you haven’t understood the example I gave. Can we please stop pretending this number is meaningful?
Someone who uses a median across jobs and companies to say there is a pay gap has committed a statistical fallacy or is intentionally misleading you for political purposes. My guess is we’ll be seeing this pop up more and more as we get closer to the next election, and it will be perpetuated by both sides. It is a hard statistic to debunk in a small sound bite without sounding like you advocate unequal pay. I’ll leave you with a clip from a few weeks ago (see how many errors you spot).