Explain to me again how marriage is the problem here

This is one of those things you share with all your friends on social media.

how-marriage-is-the-problem-here

Black married parents are 2.4-times more likely to be in poverty, are 2.1-times more likely to be unemployed, and have one-ninth the median net worth compared with White married parents. So explain to me again how marriage is the problem here.

Why?

The other day I picked on someone’s fact meme, and wondered what makes these things work, without offering a constructive alternative. I can’t answer the question I asked in that post (how old are the fathers of teen mothers’ children?), but I can answer some other questions about families and Black-White inequality. So that’s what I did.

Feel free to take these facts (or any others) and make something better.

How?

Here are my sources:

Poverty: 2014 American Community Survey from IPUMS.org. It’s Black and White, non-Hispanic, householders who are married and have their own children in the household. The poverty rates were 5% for White married parents and 11.9% for Black married parents. The poverty variable goes from 0 to 501, with 0-99 being below the poverty line, so you specify the recode like this: poverty(r:0-99 “poor”; 100-501 “not poor”). Here’s how you fill out the boxes in the online analysis tool:

povacscode

Unemployment: Again, 2014 American Community Survey from IPUMS.org. It’s Black and White, non-Hispanic, householders who are married and have their own children in the household. For this one you limit it to people in the labor force (empstat(1-2)) to get the unemployment rate. I did it for men and women combined, getting unemployment rates of 3.1% for White married parents and 6.6% for Black married parents. The numbers are higher for women (3.7% versus 7.3%) but the Black/White ratio is a little worse for men (2.6% versus 5.8%). Here’s how:

unempacscode

Median net worth: I used the Survey of Consumer Finances from 2013, available here. These are also non-Hispanic Black and White parents living with children. The median net worths were $150,500 for Whites and $16,000 for Blacks (Hispanics, incidentally, have $18,750, and the rest are just coded “other”). This data set combines married people with those who are “living with partner,” so this comparison includes cohabitors. (I don’t know how that affects the results, but I’m sure there’s still lots of inequality.) I put my STATA code in an Open Science Framework project here, so feel free to play with it yourself.

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The fathers behind teen births (or, statistical memes and motivated blind trust)

When makes people trust statistical memes? I don’t know of any research on this, but it looks like the recipe includes a combination of scientific-sounding specificity, good graphics, a source that looks credible, and – of course – a number that supports what people already believe (and want their Facebook friends to believe, too).

If that’s the problem, and assuming the market can’t figure out how to make journalism work, I have no solution except seizing the Internet and putting it under control of the Minister of Sociology, or, barring that, encouraging social scientists to get engaged, help reporters, and make all their good work available publicly, free, and fast.

Today’s cringe:

13179054_1158267840891715_8960394622916968249_n

The blogger TeenMomNYC takes credit for creating this, and the Facebook version has been shared tens of thousands of times. Its popularity led to this story from Attn: “The Truth About Teenage ‘Baby Mamas’ is Quite Revealing.” (If anyone did want to study this issue, this is a neat case study, because she posted 8 “did you know” graphics on Facebook at the same time, and none of the others took off at all – why?)

I don’t know anything about TeenMomNYC, but I share her desire to stop stigmatizing and shaming young mothers. I wish her work were not necessary, but I applaud the effort. That said, I don’t necessarily think shaming young fathers (even if they’re not quite as young) is a solution to that, but that’s not the point. My point is, what is this statistic?

According to the footnote (thanks!), it comes from this 1995 National Academies report, and (except for changing “29” to “29.7”) it represents it accurately. From p. 205:

These data highlight an additional component of the sexual abuse picture— the evidence that an appreciable portion of the sexual relationships and resulting pregnancies of young adolescent girls are with older males, not peers. For example, using 1988 data from the NSFG and The Alan Guttmacher Institute, Glei (1994) has estimated that among girls who were mothers by the age of 15, 39 percent of the fathers were ages 20–29; for girls who had given birth to a child by age 17, the comparable figure was 53 percent. Although there are no data to measure what portion of such relationships include sexual coercion or violence, the significant age difference suggests an unequal power balance between the parties, which in turn could set the stage for less than voluntary sexual activity. As was recently said at a public meeting on teen pregnancy, “can you really call an unsupervised outing between a 13-year-old girl and a 24-year-old man a ‘date’?”

This is an important point, and was good information in 1995, when it cited a 1994 analysis of 1988 data, which asked women ages 15-44 a retrospective question. In other words, this refers to births that took place as early as 1958, or between 28 and 58 years ago. That is historical, and really shouldn’t be used like this today, given how much has changed regarding teen births.

The analysis is of the 1988 National Survey of Family Growth, a survey that was repeated as recently as 2011-2013. Someone who knows how to use NSFG should figure out the current state of the age gap between young mothers and fathers and let TeenMomNYC know.

Even if I didn’t know the true, current statistic, this would give me pause. Births to women before age 15 are extremely rare. The American Community Survey, which asks millions of women whether they have had a birth in the previous year, does not even ask the question of women younger than 15. The ACS reports there were 179,000 births in the previous year among women who were under 20 when interviewed, of which only 6,500 were to women age 15 at the interview. So that’s 3.7% of teen births, and 3 out of every thousand 15-year-old women. In 1958 this was much more common, and the social environment was much different.

Another issue is the age range of the fathers, 20-29, which is very wide when dealing with such young mothers. Look at the next phrase from the 1995 report: “girls who had given birth to a child by age 17, the comparable figure was 53 percent.” Realize that the great majority of girls who had a birth “by age 17” were 17 when they did, and the great majority of those men were probably close to 20. I’m not very positive about 20-year-old men having children with 17-year-old women, but it’s pretty different from 29-versus-13.

I can’t find the original source for this, but this report from the Resource Center for Adolescent Pregnancy Protection attributes this table to the California Center for Health Statistics in 2002, which shows that the father was age 20 or older  for 23% of women who had a birth before age 15. And of those, 93% were 20-24 (rather than 25+).

cateen

Anyway, this is a good case of a well-intentioned but under-resourced effort to sway people with true information, picked up by click-bait media and repeated because people think it will help them win arguments, not because they have any real reason to believe it’s true (or not true).

So I really hope someone with the resources, skills, and training to answer this question will produce the real numbers regarding father’s age for teen births, and post them, with accompanying non-technical language, along with their code, on the Open Science Framework (or other open-access repository).

Fixing the media and its economy is a tall order, but academics can do better if we put our energy into this work, reward it, and restructure our own system so that good information gets out better, faster and more reliably.

Related posts:

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Black women really do have high college enrollment rates (at age 25+)

The other day I reported on the completely incorrect meme that Black women are the “most educated group” in the U.S. That was a simple misreading of a percentage term on an old table of degree attainment, which was picked up by dozens of news-repeater websites. Too many writers/copiers and editors/selectors don’t know how to read or interpret social statistics, so this kind of thing happens when the story is just too good to pass up.

I ignored another part of those stories, which was the claim that Black women have the highest college enrollment rates, too. This is more complicated, and the repeated misrepresentation is more understandable.

Asha Parker in Salon wrote:

By both race and gender there is a higher percentage of black women (9.7 percent) enrolled in college than any other group including Asian women (8.7 percent), white women (7.1 percent) and white men (6.1 percent), according to the 2011 U.S. Census Bureau.

You know the rewrite journalists are playing telephone when they all cite the same out-of-date statistics. (That Census report comes out every year — here’s the 2014 version; pro-tip: with government reports, try changing the year in the URL as a shortcut to the latest version.)

But is that true? Sort of. Here I have to blame the Census Bureau a little, because on that table they do show those numbers, but what they don’t say is that 9.7% (in the case of Black women) is the percentage of all Black “women” age 3 or older who are attending college. On that same table you can see that about 2% of Black “women” are attending nursery school or kindergarten; more relevant, probably, is the attendance rate for those ages 3-4, which is 59%.

So it’s sort of true. Particularly odd on that table is the low overall college attendance rate of Asian women, who are far and away the most likely to go to college at the “traditional” college ages of 18-24. That’s because they are disproportionately over age 25 (partly because many have immigrated as adults). But, if you just limit the population to those ages 18-54, Black women still have the highest enrollment rates: 15.5%, compared with 14.6% for Asians, 12.6% for Hispanics, and 12.4% for Whites. Asians are just the most likely to be over 25 and not attending college, most of them having graduated college already.

This does not diminish the importance of high enrollment rates for Black women, which are real — after age 25; the pattern is interesting and important. Here it is:

womcolen

Under age 25, Black women are the least likely to be in college, over 25 they’re the most likely. This really may say something about Black women’s resilience and determination, but it is not a feel-good story of barriers overcome and opportunity achieved. And, despite her presence in the videos and stories illustrating this meme, it is not the story of Michelle Obama, who had a law degree from Harvard at age 24.

This is part of a pattern in which family events are arrayed differently across the life course for different race/ethnic groups, and the White standard is often mistaken as universal. I have noted this before with regard to marriage (with more Black women marrying at later ages) and infant mortality (which Black women facing the lowest risk of infant death when they have children young). It’s worth looking at more systematically.

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Life table says divorce rate is 52.7%

After the eternal bliss, there are two ways out of marriage: divorce or death.

I have posted my code and calculations for divorce rates using the 2010-2012 American Community Survey as an Open Science Framework project. The files there should be enough to get you started if you want to make multiple-decrement life tables for divorce or other things.

Because the American Community survey records year of marriage, and divorce and widowhood, it’s perfectly set up for a multiple-decrement life table approach. A multiple-decrement life table uses the rate of each of two exits for each year of the original state (in this case marriage), to project the probability of either exit happening at or after a given year of marriage. It’s a projection of current rates, not a prediction of what will happen. So, if you write a headline that says, “your chance of divorce if you marry today is 52.7%,” that would be too strong, because it doesn’t take into account that the world might change. Also, people are different.

The divorce rate of 52.7% can accurately be described like this: “If current divorce and widowhood rates remain unchanged, 52.7% of today’s marriages would end in divorce before widowhood.” Here is a figure showing the probability of divorce at or after each year of the model:

div-mdlt

So there’s 52.7% up at year 0. Marriages that make it to year 15 have a 30% chance of eventually divorcing, and so on.

Because the ACS doesn’t record anything about the spouses of divorce or widowed people, I don’t know who was married to whom, such as age, education, race-ethnicity, or even the sex of the spouse. So the estimates differ by sex as well as other characteristics. I estimated a bunch of them in the spreadsheet file on the OSF site, but here are the bottom lines, showing, for example, that second or higher-order marriages have a 58.5% projected divorce rate and Blacks have a 64.2% divorce rate, compared with 52.9% for Whites.

div-mdlt-tab

(The education ones should be taken with a grain of salt because education levels can change but this assumes they’re static.)

Check the divorce tag for other posts and papers on divorce.

The ASA-style citation to the OSF project would be like this:  Cohen, Philip N. 2016. “Multiple-Decrement Life Table Estimates of Divorce Rates.” Retrieved (osf.io/zber3).

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No Black women are not the “most educated” group in the US

I don’t know where this started, but it doesn’t seem to be stopping. The following headlines are all completely factually wrong, and the organizations that published them should correct them right away:

The Root: Black Women Now the Most Educated Group in US

Upworthy: Black women are now America’s most educated group

SalonBlack women are now the most educated group in the United States

GoodBlack Women Are Now The Most Educated Group In The U.S.

And then the video, by ATTN:, on Facebook, with 6 million views so far. I won’t embed the video here, but it includes these images, with completely wrong facts:

bweduc1

bweduc2

What’s true is that Black women, in the 2009-2010 academic year, received a higher percentage of degrees within their race/ethnic group than did women in any other major group. So, for example, of all the MA degrees awarded to Black students, Black women got 71% of them. In comparison, White women only got 62% of all White MA degrees. Here is the chart, from the data that everyone linked to (which is not new data, by the way, and has nothing to do with 2015):

bwdegchart

For Black women to be the “most educated group,” they would have to have more degrees per person than other groups. In fact, although a greater percentage of Black women have degrees than Black men do, they have less education on average than White women, White men, Asian/Pacific Islander women, and Asian/Pacific Islander men.

Here are the percentages of each group that holds a BA degree or higher (ages 25-54), according to the 2010-2014 American Community Survey, with Black women highlighted:

bwdegchartBA

23% of Black women ages 25-54 have BA degrees or more education, compared with 38% of White women. This does not mean Black women are worse (or that White women are better). It’s just the actual fact. Here are the percentages for PhD degrees:

bwdegchartPhDJPG

Just over half of 1% of Black women have PhDs, compared with just over 1% of White women – and almost 3% of Asian/PI women. White women are almost twice as likely to have a PhD and Black women, Asian/PI women are more than 5-times as likely.

Racism is racism, inequality is inequality, facts are facts. Saying this doesn’t make me racist or not racist, and it doesn’t change the situation of Black women, who are absolutely undervalued in America in all kinds of ways (and one of those ways is that they don’t have the same educational opportunities as other groups). There are some facts in these stories that are true, too. And of course, why Black women (and women in general) are getting more degrees than men are is an important question. But please don’t think it’s my responsibility to research and present all this information correctly before it’s appropriate for me to point out the obvious inaccuracy here. You don’t need this meme to do the good you’re trying to do by sharing these stories.

Our current information economy rewards speed and clickability. Journalists who know what they’re doing are more expensive and slower. Making good graphics and funny GIFs is a good skill, but it’s a different skill than interpreting and presenting information. We can each help a little by pausing before we share. And those of us with the skills and training to track these things down should all pitch in and do some debunking once in a while. For academics, there is little extra reward in this (as evidenced by my most recent, sup-par departmental “merit” review), beyond the rewards we already get for our cushy jobs, but it should be part of our mission.

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Why male and female ‘breadwinners’ aren’t equivalent (in one chart)

Here’s a quick addition to some old posts on breadwinners (here and here).

Nowadays, women are much more likely to earn more income than their husbands do. But this is a shift, not a revolution, because very very few women are the kind of breadwinner that men used to be.

Using data on 18-64 year-old married wives (and their husbands*) from Decennial Censuses and the 2014 American Community Survey (via IPUMS.org), here are some facts from 2014:

  • In 2014, 25% of wives earn more than their spouses (up from 15% in 1990 and 7% in 1970).
  • The average wife-who-earns-more takes home 68% of the couple’s earnings. The average for higher-earning husbands is 82%.
  • In 40% of the wife-earns-more couples, she earns less than 60% of the total, compared with 18% for husbands.
  • It is almost 9-times more common for a husband to earn all the money than a wife (19.6% versus 2.3%).

Here is the distribution of income in married couples (wife ages 18-64; the bars add to 100%):

coupincdist

Male and female breadwinners are not equivalent; making $.01 more than your spouse doesn’t make you a 1950s breadwinner, or the “primary earner” of the family. (Also, you might call a single mother a breadwinner or primary earner, but not if you’re describing trends from a gender-equality perspective.)

* I forgot that in 0.5% of the 2014 cases the wife’s spouse is also a woman, so it would be more accurate to replace “husband” with “spouse” in the facts that follow.

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NYT’s Richtel traffic hype soars at historic rate

What if everything you learned about traffic fatalities you got from Matt Richtel at the New York Times?

On April 27, Richtel wrote:

Over the last seven years, most states have banned texting by drivers, and public service campaigns have tried an array of tactics — “It can wait,” among them — to persuade people to put down their phones when they are behind the wheel.

Yet the problem, by just about any measure, appears to be getting worse. Americans confess in surveys that they are still texting while driving, as well as using Facebook and Snapchat and taking selfies. Road fatalities, which had fallen for years, are now rising sharply, up roughly 8 percent in 2015 over the previous year, according to preliminary estimates.

I left the paragraph breaks as they were, so you can see the connection he implied. Sure seems that all that texting is driving up the rate of fatalities, although there is no evidence offed for that. Of course, since you only read Richtel, you don’t know that since 1994, cell phone subscription rates have risen 1200% while traffic fatalities have fallen 13%. (My series on this, with all these facts, is under the texting tag.)

But what about this “now rising sharply” fact? The same fact – an estimated 8% increase in one year, grew from “now rising sharply” on April 27 to “soaring at a rate not seen in 50 years” by May 22.

When I complained to the NYT Science Desk that this was a misleading representation of a traffic fatality rate that is still at historically low levels, someone checked it out and nicely informed me they had “confirmed the article accurately states the fact: preliminary estimates indicate road fatalities are rising at a rate not seen in 50 years.” Complaint denied.

Assuming you share my obsession with this problem of hyping traffic fatalities – and distracting the public with stories of bad drivers instead of paying attention to the real problem, which is rampant car culture itself – then you’ll want to make a distinction between the facts themselves and the NYT representation of them.

Facts

The fact here is actually kind of weird. Instead of using the official traffic fatality rates, which the National Highway Traffic Safety Administration hasn’t released yet for 2015, Richtel here is reporting the preliminary 2015 estimate from a private group, the National Safety Council. The weird thing is that NSC uses a different method, counting people as dead from a traffic incident if they die from any cause within a year of the accident, while NHTSA only counts them as dead from the incident if they die within 30 days. The rule is arbitrary either way, but I prefer to NHTSA method in the absence of a compelling argument. (As any Law & Order fan can tell you, people who die can have that death attributed to something that happened years earlier if the medical examiner owes the detectives a favor.) Not surprisingly, NSC produces estimates that are higher – about 8% higher, about 3,000 deaths more than the roughly 35,000 NHTSA reports. The longer death window seems bad for comparing rates over time, because the population is aging and therefore the death rate will probably rise among people who have had an accident in the previous year just because they’re older on average.

Anyway, since NSC doesn’t report their long-term trend (at least on the free part of their website), I applied their estimate of the “soaring” 2015 change – an 8.2% increase in total deaths – to the NHTSA series (helpfully recorded on this Wikipedia page), to extend the series to 2015. We also now have the Federal Highway Administration’s report on vehicle miles traveled in 2015 (+4% from 2014), so I can use that estimate of total deaths to calculate deaths per mile for 2015, as well as deaths per person (using the average of the Census Bureau’s monthly estimates for the year, which was 321.4 million, +0.8%). By these calculations, Richtel’s soaring 8.2% increase in total deaths becomes a 4% increase in deaths per mile, and a 7.3% increase in deaths per person. Here are the 50-year trends, with recessions shown:

trafficdeaths66-14

The dramatic increase in deaths for 2015, which is quite large on a relative scale during this time period – in fact, at no time in last 50 years has the number of deaths increase by 8.2% in one year – looks kind of small. But perhaps more important, it seems in line with the cyclical nature of the trend. Death rates fall during recessions and rebound afterwards. In fact, the declines in 2008 and 2009 – which were 9.3% and 9.5% respectively – are also unprecedented during this period, so a larger rebound is not surprising.

Representations

So how should Richtel describe the trend? Keep in mind this is a reporter who is still promoting a book premised on the crisis of distracted driving – the homepage for which, despite notifications to the author and publisher, still repeats the bogus internet meme that 11 teens per day die from texting while driving.

After I complained on Twitter, Richtel tweeted to his followers:

So I put the description question to the test of my Twitter readers, offering them a poll. I made two figures, one from the actual death trend (with my 2015 estimate), and one with the same trend in reverse, and asked people (without comment) which one they thought was better described by Richtel’s phrase:

My readers were closely divided, but gave Richtel the edge, 56% to 44%:

I don’t think it’s very strong vindication to barely eke out a majority in a poll where people are asked to choose which is right, what you said or the exact opposite of what you said. I would think real reporting would have a higher rate of concordance than that.

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