I suppose that should technically read “Correcting The State Of The Union Address,” since I make no claims as to my ability to fix all of the nonsense that is currently going in the U.S. Anyway, I of course had a number of (usually nitpicky) objections regarding President Obama’s State of the Union address last night, but I know by this point that people have to choose their battles. So here’s mine…from the speech:
Today, women make up about half our workforce. But they still make 77 cents for every dollar a man earns. That is wrong, and in 2014, it’s an embarrassment. A woman deserves equal pay for equal work. She deserves to have a baby without sacrificing her job. A mother deserves a day off to care for a sick child or sick parent without running into hardship – and you know what, a father does, too. It’s time to do away with workplace policies that belong in a “Mad Men” episode. This year, let’s all come together – Congress, the White House, and businesses from Wall Street to Main Street – to give every woman the opportunity she deserves. Because I firmly believe when women succeed, America succeeds.
I am soooooo sick of this statistic, since it basically suggests that a woman shows up at a workplace and her boss is like hey, you look like you might have ovaries, here’s $0.77 rather than $1. And that’s not what is actually happening. Yes, it is true that, on average (actually, comparing medians if you want to be technical), a woman in the U.S. earns 77 percent of what a man in the U.S. earns, but that figure doesn’t control for any relevant determinants of income- schooling, industry, tenure, etc. Therefore, I cringe whenever the “equal pay for equal work” line is trotted out, since “equal work” would imply that whoever is handing out this 77 percent figure did in fact run some sort of regression that would control for enough to get to a point where the comparison was at least close to equal. In the spirit of actually wanting to understand the gender pay disparity issue and not just quote a meaningless number, let’s look at some actual research from Claudia Goldin. Some helpful excerpts:
Men and women begin their employment with earnings that are fairly similar, both for full-time year-round workers and for all workers with controls for hours and weeks. In the case of the latter group, relative earnings are in the 90 percent range for the most recent cohorts even without any other controls. But these ratios soon decline and in some cases plummet to below the 70 percent level.
Translation: We’re basically at a place now where young men and women don’t differ substantially in their levels of education (in fact, I think women are actually outperforming in terms of educational attainment according to a number of metrics), so when comparing the initial situations of these young people, the divide is 90-some-odd cents on the dollar, not 77. And this is without taking into account the fact men pay be sorting into higher-paying jobs. That said, there seems to be a shift in gender disparity as people move on their lives that should be examined.
The main takeaway is that what is going on within occupations—even when there are 469 of them as in the case of the Census and ACS—is far more important to the gender gap in earnings than is the distribution of men and women by occupations. That is an extremely useful clue to what must be in the last chapter. If earnings gaps within occupations are more important than the distribution of individuals by occupations then looking at specific occupations should provide further evidence on how to equalize earnings by gender. Furthermore, it means that changing the gender mix of occupations will not do the trick.
Translation: Convincing men and women to enter the same occupations wouldn’t make the gender disparity go away, so let’s perhaps stop focusing on that so much as a potential solution.
The clear finding is that the occupations grouped as Business have the largest negative coefficients and that occupations grouped as Technology and Science have the smallest ones. That is, given age and time worked residual differences for Business occupations are large and residual differences in Technology and Science are small. In fact, for the “young” group (less than 45 years old) some Technology and Science occupations have positive coefficients.
Translation: The female “penalty” differs a lot by occupation, and in some cases there is no penalty and even a benefit to being female.
As I will later demonstrate using data on occupations in business and law, the impact of hours on the gender gap is large and goes far to explain much of the gender earnings gap. Individuals who work long hours in these occupations receive a disproportionate increase in earnings. That is, the elasticity of earnings with respect to hours worked is greater than one.
Translation: Within an occupation (in some cases), being a high earner (even on a per-hour basis) requires long hours and, as is shown in another part of the paper, working a particular schedule. This feature explains a lot of the gender discrepancy and is a result of women and men selecting into these situations at different rates, especially as women start caring for families.
The gender gap in annual earnings for the JDs and MBAs, although large by year 15, is almost entirely explained by various factors, such as hours worked, time out of the labor force, and years spent in part-time employment.
Translation: This is not an ovaries penalty story, at least not directly.
What, then, is the cause of the remaining pay gap? Quite simply the gap exists because hours of work in many occupations are worth more when given at particular moments and when the hours are more continuous. That is, in many occupations earnings have a nonlinear relationship with respect to hours. A flexible schedule often comes at a high price, particularly in the corporate, financial, and legal worlds.
Hopefully there is no translation needed here. The overall point of presenting this is that, in order to craft an actual solution to a problem, it’s crucially important to identify what is causing the problem. As a society, we seem to have decided that a gender pay differential is a problem. However, the lack of understanding of the nature and cause of the problem is going to prevent the problem from being solved. The information provided above suggests that any legislation of the “equal pay for equal work” form, for example, will be mostly ineffective, since observed differences in pay are in fact largely explained by inequalities in either job tenure or work quantity. In order to solve the problem, then, policymakers must look one step behind the curtain and think about how to mitigate the effects of differences in worker hours or tenure rather than just keep trotting out a well-worn sound bite to overshadow the real issue.
Econgirl out. *mic drop*