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All posts by Dan Whalen,
Providence, RI (resume)

Thursday, December 13, 2012

Earnings Gap Between Sexes

Introduction

I want to start off by telling you one thing about this issue.  Its complicated.  You could make yourself an entire career just studying the gap in the earnings between men and women.

From both the social/policy angle and from the analytical/technical end, this is a difficult issue to examine.  The causes are unclear, the direct repercussions murky - heck just measuring the gap is tricky business, and that's kind of the point of this post.

I think the reason for this is that something as large and complex as the national workforce just doesn't lend itself to analysis along one simple dimension.

If we divided the large and complex US labor market up into any two groups - men vs women, whites vs non-whites, over 40 vs under 40, etc. - all we've done is created two large and complex groups.  They still would be difficult to study in any meaningful way.

In other words: not ALL working men are identical, interchangeable, homogenous units.  Not ALL working women are identical, interchangeable, homogenous units.  So how do we compare ALL working men to ALL working women in a reasonable way?

In any event, the pay gap is real, and its something we care about, and its something that matters.  It's an important thing for us as a society to address.

But to impress upon you the complexity of the issue, this post will mostly look at different approaches we can take just in measuring the disparity in earnings - and the contrasting conclusions those measurements can point us towards.


The data

The Bureau of Labor Statistics (the guys who measure the unemployment rate) collect tons of demographic and financial data on America's workforce.  Everyday, non-stop, the BLS conducts surveys with workers and employers, as a way of tracking trends in the national labor market.

Four times a year, they release the "Usual Weekly Earnings of Wage and Salary Workers", which reports results of their perpetual surveys.  All data referred to in this post I grabbed directly from the 2012 Third Quarter report.

So one thing to be aware of right now is that this is survey data.  We assume that the numbers are close-ish but not exact.  But given the size and scope of the BLS, and the significant resources they have access to (they are part of the US gov't, after all - and those guys have money), they probably have the best numbers we're gonna get.  

For more on how this data is collected, check out the "Technical Note" section on page 3 of the 2012 Third Quarter report.


How big is the gap?

The BLS states it this way:

"Women who usually worked full time had median weekly earnings of $685, or 82.7 percent of the $828 median for men." - See pg. 1, 2nd bullet 

Ok, so lets decode this a bit.  First off, we're looking at a median value, not the mean.  Using the median tempers the effect of outliers that could skew the "average."

Next, "usually worked full time."  "Full-time" for the BLS is 35 hours a week at one place.

So we can rephrase the BLS's quote to be: "Every week, on average, working women made 82.7 cents for every dollar working men made."

There are tons of other methods of measuring this gap, and they all come up with slightly different results.  But I will point out that the differing approaches all come within a limited range (80 - 85 cents for women per dollar for man or so), and that no one is finding women earn more then men, on average.

Also, keep in mind, that this is not (at least not yet) an issue of "unequal pay for equal work."  It's same employment status (ie "full-time"), different average earning.  Do a larger portion of women work in lower paying fields?  Do more work men overtime?  Is there a gender gap in education?

Remember, not all "working women" are the same person.  The female workforce is not a homogenous, monolithic, identical whole.  Now that we have the workforce divided up into men and women, lets split them up again, and see what we can see.


How many women work full time?

As of October 2012, there were officially 103,577,000 people in the US labor pool.  That's about a third of the total population.

Of those workers, 58,069,000 were male (56%) and 45,508,000 were female (44%).


The effects of educational attainment

Your level of education plays a significant role in determining your earnings.  Can the gender pay gap be explained by a gap in educational attainment?

Of the working people out there with degrees, a bit more of them are men.

Numbers are in thousands

BUT - women who do have degrees still earn less in an average week then do men.  Looks like education alone doesn't explain the gap.

(Note that while average earnings increase with any degree, for both genders, the gap in pay - the difference in height of the two bars - also grows.  On average, men with advanced degrees make about $400 more per week then women with advanced degrees.  Men with less than a HS diploma make an average of $100 more per week then women with no diploma.)


The effects of occupation

Some jobs are traditionally mostly done by men, and some that are mostly done by women.  Do the kinds of jobs typically worked by women also happen to be the kinds of jobs that don't pay well?

The BLS does split up survey respondents by job type (albeit pretty broadly), so we can dig a little bit into this question.

Before you study the chart below, let me make it clear how to read it:
  • Blue bars are the percent of working men employed in that sector
  • Red bars are the percent of working women employed in that sector
  • The number floating above each pair is the ratio between the median weekly paycheck for men and the median paycheck for women employed in that sector.  
So a "1" means there is no pay differential between the sexes - the average pay for women is the same as it is for men in that field.  But a ".74," for example, signifies that for every dollar the men receive, the women get 74 cents.  (Or simply: the lower the number, the greater the pay gap between the sexes.)

Alright, so there is A LOT going on in this chart.  We could do several blog posts based on this info alone.  But I have a day job, so lets just look at some of the things that really pop out:

First off, notice how women are not distributed very well throughout the employment sectors.  While men are decently represented in each job category, the majority of women workers are concentrated in just three: Management, Business and Financial Operations, Office and Administrative Support and Professional and Related

Next, we see there are barely any women at all working in Construction and Extraction, yet there is no pay gap at all in that sector.  Installation, Maintenance, and Repair occupations are equally devoid of female workers, but offers pay equality exceeded only by Construction and Extraction.  Are women best off in fields where they are an extreme minority?

Well, not necessarily.  We see Office and Administrative Support occupations capture a large share of working women, and the pay equality there is realtively good.

And how about Sales and Related?  An equal proportion of the male and female labor force is drawn to sales, but the pay gap is more extreme here then it is in any other field.

Here's an observation: when I first looked at this graph I thought "I bet pay equality has the best chance in fields where pay is typically hourly, since people work for a stated, fixed rate, not a negotiated, 'commensurate-with-experience' (read: subjective and variable) pay - like salaried folks do."

But the more I look at this chart, the more I question about that hypothesis.  Sure, that could be what's going on in Installation, Maintenance, and Repair, or Office and Administrative Support.  But the Service sector is dominated by hourly worker, and only has relatively equal pay - but not perfectly.

One last thing to consider - its possible that the base pay for a lot of these jobs are the same for men and women in practice, but men are better able to take advantage of the incentive pay.

Mothers, who often end up with more family obligations than fathers - and are more likely to be a single parents - are less likely to have particularly flexible schedules.  They mightn't be as able to take advantage of overtime, work holidays, do out of town jobs, meet with clients at odd hours, etc.

This would be of particular disadvantage for Transportation and Material Moving occupations (where employees are often paid by the mile driven), and Sales and Related (where networking and client face time affects one's ability to make a sale - and get that commission).  More on this "motherhood effect" later.

And as always, keep in mind that these are median values.  They're averages.  Not all women in these categories have to be experiencing the same, group wide, pay inequality.  Some of these apparent gaps could be products of how the survey respondents were grouped by the BLS.

For example: look at Professional and Related.  This category includes a lot of very different occupations - nurses, cops, lawyers, teachers - pretty much anything you need a specialized degree, license, card or certification to do.

Is it possible that, say, female professional firefighters are paid the same as their male counterparts, but female scientists are not.  The scientists' low median pay might affect the group wide average for "professional working women."  But the firefighters might look at this chart and say "hey, we have a pay equity problem," when really they don't.  We really can't tell just by looking at this particular dataset alone.


A little challenge

Well, that's all just speculation on my part.  But I want to demonstrate the types of questions we can ask, and thoughts we can explore just from that one chart alone.

But I'm sure I didn't think of everything.  So I encourage you to take some time and think about this chart.  What is it telling us?  What do you think is going on here?  How do you interpret this data?  I'm relying on you to do some thinking here for yourself.

Make hypotheses and test them out!  Look for data that supports your hypotheses and data that refutes it.  Do research.  Get sciencey!  If you have any thoughts or breakthroughs please share!  Post them in the comments below.


The effects of age

There's one more big thing I noticed while sifting through the BLS data.

The pay gap doesn't really manifest until a few years in.  Males under the age of 20 earn only an average of $35 more per week then females of the same age.  But by the time we reach 35, the difference is over $200.


There's plenty of theories going around trying to tackle this phenomenon.  Could it be the males get promoted more earlier and more often?  Are women not as well-positioned or aggressive when it comes to gunning for the high pay, highly competitive top positions?

Or: if you're a 50 year old woman, and a product of the bad old days when girls were less encouraged to work demanding jobs, get promotions or get a degree, your earnings might have peaked years ago, while your brother's continue to ramp up. 

Or: is it the "motherhood effect"?  There's many more single mothers out there than single fathers.  And in many married couples, women are often are the ones expected to maintain the household.  Are the demands of a family more likely to cut into a woman's opportunities for advancement and working overtime than a man's?

The average age of a women when she has her first child in the US is 23.  For women with a Bachelor's degree or higher (read: mothers with the highest earning potential) its 27.9.

The pay gap explodes right around the time people normally start having families.  Now, this may be a coincidence too, of course.  Heck, its is also the age most people finish college, or start to take salaried jobs.  Besides, not all moms are employed, and not all employed women are moms.

But remember, these are average numbers were talking about here.  The fact that some working women have kids competing with careers for their time and energy could be enough to affect the group median - the weekly average pay for all women.

There is something intrinsically appealing to me about the "motherhood effect" explanation: regardless of race, education and profession, women, as a monolithic whole, bear more of the brunt when it comes to the children.

This gives the "motherhood effect" hypothesis some pretty sweeping explanatory power, as its the only characteristic/factor that can ever be relevant to the entire female workforce.

Women in retail have more chances to work weekends than professional women do.  A woman with a degree earns more then a women without.  Being a woman lawyer versus a woman professor have their own unique challenges.

But a child demands the same level of care and attention, no matter who its mom is, where she works, or what resources are available to her.  Children of nurses sleep as often as the children of CEOs.  A 60 is passing, whether or not your parent works nights.  Kids are kind of the great equalizer here.

You might object to this and say "but not all women have kids," or "not all fathers don't help out around the house."

But remember, this data only reflects broad trends and averages within the entire group.  These exceptions to these rules won't influence the data to any meaningful degree.  As long as the overall trend in a society is that women are more often expected to perform domestic duties than men, then "women," as a unified group, are uniquely subject to this "motherhood effect."

A major implication of the motherhood effect would be: the earnings gap CANNOT be shored up by regulation and legislation alone.  A change in social trends and home dynamics need to be a part of the solution too.

Of course I'm not saying that motherhood alone can explain the entire earnings gap.  But it is very likely a contributing factor - one of many, as we've seen.


To wrap this up...

Like I said, my point here today was just to talk about how tricky it is to define and quantify the earnings gap between sexes.  No one out there questions that the gap exists.  The controversy is more in what exactly the gap is, and where it is.  Because if we don't know what the problem is, we can only guess as to how we can eradicate it.

We've only scratched the surface of this topic, and already I've gone on too long.  I highly encourage you to think critically about the topic, and share with us any resources, thoughts and ideas you have in the comments section.

To get you started, I've put together a list of interesting reading to check out:

The Economist:
 
Economix:  

Forbes:

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