Tag Archives: gender stall

Women’s Equality Day earnings data stuff and suffrage note

Tomorrow is Women’s Equality Day, which commemorates the day, in 1920, when U.S. women were granted the right to vote. (Asterisk: White women.)

One historical story

Congress finally passed a Constitutional amendment for women’s suffrage in 1918, after decades of activism. The suffrage movement in the end successfully made a few convincing arguments – and one clarification. The most important may have been that White women had proved their patriotism during the war, and so they finally deserved the vote. I wrote in 1996:

“No one thing connected with the war is of more importance at this time than meeting the reasonable demand of millions of patriotic and Christian women of the Nation that the amendment for woman suffrage be submitted to the states,” declared Representative James Cantrill. And, he added, “Right, justice, liberty and democracy have always been, and will always be, safe in the tender care of American womanhood.”

And you know what he meant by “American womanhood” (an image the mainstream suffrage movement encouraged to various degrees over the years):


American Progress, by John Gast (1872)

The important clarification was that women’s suffrage would absolutely not hurt White supremacy in the South. You know how it is when you just need that Southern vote. I went on:

If reluctant congressmen would only believe in the contribution of white women that was waiting to be made, suffrage advocates explained, the political math was irresistible. “There are more white women of voting age in the South to-day than there are negro men and women together,” [Congress’s only woman, Jeannette] Rankin said. Representative Scott Ferris assured them that poll taxes and literacy tests would remain untouched, so that “for every negro woman so enfranchised there will be hundreds and thousands of intelligent white women enfranchised” (Congressional Record 1918, 779). And Representative Thomas Blanton proclaimed, “So far as State rights are concerned, if this amendment sought to take away from any State the right of fixing the qualifications of its voters, I would be against it first, last, and all the time, but such it does not.” Although states should be allowed to set qualifications for voting, he believed, they could not do so at the expense of undermining true republicanism, and, “if you deny the 14,000,000 white women of this country the right to vote, you are interfering with a republican form of government [Applause]” (786). That day, the House passed the amendment with the required two-thirds vote.

Anyway, rights are rights, America is America, history is history (ha ha).

Some pay gap numbers

Back to nowadays. Today’s numbers come from some analysis of the gender earnings gap I did to support the Council on Contemporary Families brief for Women’s Equality Day. One big story is women’s rising education levels, especially BA completion.

In the active labor force as often described (age 25-54, working at least 20 hours per week and 26 weeks in the previous year), women surpassed men in BA completion in 2002:


That’s very good for women with regard to the earnings gap, because at every level of education men earn more than women. Women’s full-time full-year earnings are between 70% and 80% of men’s at all education levels except the highest, where they diverge: men who are doctors and lawyers earn much more than women, while women PhDs are doing relatively well. Here’s the 2015 breakdown by education:


With the education trend and differentials in mind, consider these multivariate model results. Going back to the sample of 25-54-year-old people working at least half-time and half the year, here are two results. The first line, in blue, shows the gender earnings ratio when only age is controlled. It shows women gaining on men from 2000 to 2016, from 77% to 83%. This is not much progress for 25 years, but it’s the slow pace we’ve come to expect during that time. The other line shows result from a more complete model, which adds controls for education, race/ethnicity, marital status, and presence of children; it shows even less progress.


In the full model (orange line) the relative gains for women are not as great. (Note I don’t include occupation in the “full” model although that’s very important; it’s just also an outcome of gender so I let it be in the gender variable for descriptive purposes.)

In the old days, when women had less education than men, controlling for education shrank the gap; now it appears the opposite is true. I haven’t done the whole decomposition to confirm this, but here’s another way to look at it. The next figure shows the same models, but in two separate samples, with and without BA degrees (and no control for education). The figure shows little progress within education groups. This implies it’s the increase in education for women that is driving the progress seen in the previous figure.


In conclusion: there is a substantial gender earnings gap at every level of education. The limited progress toward equality we’ve seen in the past 25 years may be driven by increases in women’s education.

There is a lot of other research on this — especially about segregation, which I didn’t include here — and a lot more to be done.

This is a little analysis, but if you’d like to do more, or see how I did what I’ve shown here, I posted the Stata code, data from IPUMS.org, codebook, and spreadsheet file on the Open Science Framework site here. You can use any of it for whatever you like, with a citation that looks like this one the OSF generates:

Cohen, P. N. (2017, August 25). Gender wage gap analysis, 1992-2016. Retrieved from osf.io/mhp3z


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Kids these days really know how to throw off a narrative on gender and families

The most important thing is that Stephanie Coontz has written another very good, and very important, New York Times essay. It describes a “slippage” in support for gender equality among young people these days, and warns that without improved work-family policies, progress toward egalitarian family arrangements may be imperiled. The piece also announced a package of short papers in a Council on Contemporary Families symposium, which provided the supporting evidence. (This kind of work, incidentally, is why I’m a proud member, and board member, of CCF.) If you haven’t read Stephanie’s essay, I recommend reading it now, and if you forget to come back here that’s fine.

Anyway, an unfortunate confluence of events created some chaos after the piece came out. First, the NYTimes wrote a headline, “Do Millennial Men Want Stay-at-Home Wives?”, that emphasized only one piece of the evidence. It referred to a figure showing General Social Survey data on the trend in very young men and women (ages 18-25) disagreeing with the statement, “It is much better for everyone involved if the man is the achiever outside the home and the woman takes care of the home and family.” (That is the classic FEFAM question, to GSS fans, asked since 1977. I’ve used it myself, and it figures in the key analysis of stalled gender progress by Cotter, Hermsen, and Vanneman.)

This was the figure, showing a marked divergence between men and women:


The second event was the unfortunate timing: between the time Stephanie wrote the piece and the day it appeared, the General Social Survey released its 2016 round of data (it’s been running every two years). The survey is fickle. It’s very good quality and has many great demographic and attitude items running for 40 years, making it the best source for analyzing many social trends. But it’s not that big. In 2014 it had 2,867 respondents, of whom only 141 were ages 18-25. So it wasn’t surprising that the 2016 numbers were different from the 2014 numbers, but the scale of the blip was shocking, as reported independently by Emily Beam and Neal Caren. Here is what the updated trend looks like:


Yikes. As exciting as it is for survey analysts to see such a wild swing, it’s not what anyone wants to see the day after their NYTimes piece drops. We can’t know yet what happened, but on further inspection, at least we can say that it’s not limited to the youngest group and its small sample. Among men ages 26-54, the percentage disagreement with FEFAM also jumped, from 73.7 to 78.3 (women 26-54 were up one point).* In fact, 2014 may have been as big a blip as 2016, you just wouldn’t notice because it continued the trend.

Anyway, back for a minute to the main point. Joanna Pepin, who co-wrote one of the symposium pieces with David Cotter (and who is also an advisee of mine), has pointed out that the divergence between men and women is secondary to the main trend, which is the reversal of progress on FEFAM for both men and women since the mid-1990s. They used the Monitoring the Future survey, and find a big drop in FEFAM disagreement among high school seniors — regardless of gender. Here’s their key figure, with the FEFAM trend shown in green (their full paper is available on SocArXiv):


So that is the most important news: a big reversal among young adults on attitudes toward homemaker-breadwinner family arrangements.

Now, If you’ve now read Stephanie’s piece, and Joanna’s, and you’re back, here’s a little more on the minor kerfuffle that arose over the new data.

When to call a trend a trend

I don’t think Stephanie was wrong to use the GSS trend, although it might have been better to widen the age range, or pool the data over several years. The bigger problem was the headline selling that divergence as the main story, which it wasn’t in the grand scheme. (The fact that so many jumped on the story shows how good they are at headline writing.) But even that wasn’t really wrong, given the information they had. The Op-Ed staff checked the facts, and the facts were the facts. Until yesterday.

To confirm this, I ran some tests on the gender divergence in the data they used (I started with code that Neal shared; it’s at the bottom). I started at 1994, the last peak of the trend, to look for the divergence after that, which is what Stephanie referred to. First, here is what you get if you run a logistic model that controls for race/ethnicity and individual years of age (two things that changed over the last two decades), and enters the years individually in an interaction with gender (those are 95% confidence intervals).


If you stop at 2014, it looks like men are pulling away from women (in the direction of “traditional” attitudes), but it’s not definitive. And obviously 2016 is an issue. To help with the small samples, I ran a linear test of the year trend, that is, entering year as a continuous variable instead of individual years. I did it ended at 2014 and then through 2016. Here are the results:


In the 1994-2014 model, the Male*Year interaction is statistically significant at conventional levels, which in my opinion means it’s legit to say men were pulling away from women. Of course 2016 ruined that; if you had 2016 and didn’t use it, that would be really wrong. There are other ways to slice it, but at some point we have to call a trend a trend and deal with it. It was a reasonable decision. Of course, new data always comes along (until the last trend of all, whatever that is), no trend lasts forever; it’s just a shame when it comes along the next day. In addition, though I’m not showing it because it’s boring, if you didn’t disaggregate the trends by gender, you would also see a significant decline in FEFAM disagreement after 1994, which gets to Joanna’s point.

Anyway, score one for sociology Twitter. People came up with the data, shared code and results, and discussed interpretations. It got back to Stephanie and the NYTimes editors, and within a day they added an addendum to the original piece:

Update: After this article was posted, 2016 data from the General Social Survey became available, adding some nuance to this analysis. The latest numbers show a rebound in young men’s disagreement with the claim that male-breadwinner families are superior. The trend still confirms a rise in traditionalism among high school seniors and 18-to-25-year-olds, but the new data shows that this rise is no longer driven mainly by young men, as it was in the General Social Survey results from 1994 through 2014.

This is pretty much how it’s supposed to work. As the Car Guys used to say, if you never stall you’re wearing out your clutch (sorry, Millennials). If you never overshoot an analysis of trends you’re probably waiting too long to get the information out.

* Note: I originally accidentally described this as “over 25.” 

You can get the data here. Here’s the STATA code:

/* recodes */

recode fefam (1/2=0) (3/4=1), gen(fefam_d)
gen young=age>=18&age<=25
recode sex (2=0), gen(male)

/* the model for the figure */

logit fefam_d i.year##i.male i.age i.race if year>=1994 & young==1 [pweight = wtssall]
margins year##male

/* the models for the table */

logit fefam_d c.year##i.male i.age i.race if year>=1994 & young==1 & year<=2014 [pweight = wtssall]
logit fefam_d c.year##i.male i.age i.race if year>=1994 & young==1 [pweight = wtssall]


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