Tag Archives: census

Theology majors marry each other a lot, but business majors don’t (and other tales of BAs and marriage)

The American Community Survey collects data on the college majors of people who’ve graduated college. This excellent data has lots of untapped potential for family research, because it tells us something about people’s character and experience that we don’t have from any other variables in this massive annual dataset. (It even asks about a second major, but I’m not getting into that.)

To illustrate this, I did two data exercises that combine college major with marital events, in this case marriage. Looking at people who just married in the previous year, and college major, I ask: Which majors are most and least likely to marry each other, and which majors are most likely to marry people who aren’t college graduates?

I combined eight years of the ACS (2009-2016), which gave me a sample of 27,806 college graduates who got married in the year before they were surveyed (to someone of the other sex). Then I cross-tabbed the major of wife and major of husband, and produced a table of frequencies. To see how majors marry each other, I calculated a ratio of observed to expected frequencies in each cell on the table.

Example: With weights (rounding here), there were a total of 2,737,000 BA-BA marriages. I got 168,00 business majors marrying each other, out of 614,000 male and 462,000 female business majors marrying altogether. So I figured the expected number of business-business pairs was the proportion of all marrying men that were business majors (.22) times the number of women that were business majors (461,904), for an expected number of 103,677 pairs. Because there were 168,163 business-business pairs, the ratio is 1.6.  (When I got the same answer flipping the genders, I figured it was probably right, but if you’ve got a different or better way of doing it, I wouldn’t be surprised!)

It turns out business majors, which are the most numerous of all majors (sigh), have the lowest tendency to marry each other of any major pair. The most homophilous major is theology, where the ratio is a whopping 31. (You have to watch out for the very small cells though; I didn’t calculate confidence intervals.) You can compare them with the rest of the pairs along the diagonal in this heat map (generated with conditional formatting in Excel):

spouse major matching

Of course, not all people with college degrees marry others with college degrees. In the old days it was more common for a man with higher education to marry a woman without than the reverse. Now that more women have BAs, I find in this sample that 35% of the women with BAs married men without BAs, compared to just 22% of BA-wielding men who married “down.” But the rates of down-marriage vary a lot depending on what kind of BA people have. So I made the next figure, which shows the proportion of male and female BAs, by major, marrying people without BAs (with markers scaled to the size of each major). At the extreme, almost 60% of the female criminal justice majors who married ended up with a man without a BA (quite a bit higher than the proportion of male crim majors who did the same). On the other hand, engineering had the lowest overall rate of down-marriage. Is that a good thing about engineering? Something people should look at!

spouse matching which BAs marry down

We could do a lot with this, right? If you’re interested in this data, and the code I used, I put up data and Stata code zips for each of these analyses (including the spreadsheet): BA matching, BA’s down-marrying. Free to use!

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Unequal marriage markets for Black and White women

Joanna Pepin and I have posted a new paper titled, “Unequal marriage markets: Sex ratios and first marriage among Black and White women.” In the paper, we find that the marriage markets of Black and White women are very different, with Black women living in metropolitan areas that have many fewer single men than White women do. And, in a regression model with other important predictors of marriage, this unmarried sex ratio is strongly associated with the odds of marrying.

We count this as evidence on the side of “structure” over “culture” in the debates over the decline in marriage. Here’s the main result, showing Black and White women in 172 metro areas (scaled for size), and the difference in sex ratios (the horizontal spread), the difference in marriage rates (the vertical spread), and the statistical effect of sex ratios on marriage (the slopes).

mmpif2

In a nutshell: As you move from left to right, there are more men, and higher odds of marriage. And almost all the White women are up and to the right compared with the Black women. One implication is that this could be one reason why marriage promotion programs in the welfare system aren’t working.

There are a couple of noteworthy innovations here. First, we used the American Community Survey marital events data, which is marriage happening (did you get married in the last year?) rather than just existing (are you married?). This is a better way to assess what might influence marriage. Second, young people, especially single young people who might be getting married, move around a lot. So what is their marriage market? It’s impossible to say exactly, but we define it as the metro area where they lived one year earlier, rather than just where they live now. (This is especially important because the people who move may move because they just got married.)

The paper is on SocArXiv, where if you follow the links you get to the project page, where we put most of the data and code. The paper is under review now, and we’d love to know if you find any mistakes or have any suggestions.

(This began with a blog post four years ago in which I critiqued a NYT Magazine piece by Anne Lowrie about using marriage to cure poverty. Then we presented a first pass at the Population Association in 2014, and I put some of the descriptive statistics in my textbook, and we made a short video out of it, in which I said, “So, larger social forces — the economy, job discrimination, incarceration policies, and health disparities — all impinge on the ability of individuals to shape their own family lives.” Along the way, I presented some about it here and there, while thinking of new ways to measure marriage inequalities.)

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2016 U.S. population pyramid, with Baby Boom

I’m finishing up revisions for the second edition of The Family, and that means it’s time to update the population pyramids.

Because it’s not so easy (for me) to find population by age and sex for single years of age for the current year, and because there is a little trick to making population pyramids in Excel, and because I’m happy to be nearing the end of the revision, I took a few minutes to make one to share.

The data for single year population estimates for July 1, 2016 are here, and more specifically in the file called NC-EST2016-AGESEX-RES.csv, here. To make the pyramid in Excel, you multiply one of the columns of data by -1 and then display the results as absolute values by setting the number to a custom format, like this: #,###;#,###. Then in the bar graph you set the two series to overlap 100%.*

In this figure I highlighted the Baby Boom so you can see the tsunami rolling into the 70s now. Unlike when I discuss cohorts previously, when I let it slide, here I actually adjusted this from what you would get applying the official Baby Boom years (1946-1964) with subtraction from 2016. That would give you ages 52 to 70, but the boom obviously starts ate age 69 and ends at age 51 here, so that’s what I highlighted. Maybe this has to do with the timing within years (nine months after the formal end of WWII would be May 2, 1946). Anyway, this is not the official Baby Boom, just the boom you see.

Click to enlarge:

2016 pop pyramid


* I put the data file, the Census Bureau description, and the Excel file on the Open Science Framework here: https://osf.io/qanre/.

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African American marital status by age, Du Bois replication edition

At the 1900 Paris Exposition, sociologist W. E. B. Du Bois presented some the work of his students. In The Scholar Denied: W. E. B. Du Bois and the Birth of Modern Sociology, Aldon Morris writes:

Du Bois’s meticulousness as a teacher is apparent in the charts and graphs that he prepared with his students. For example, as part of his gold medal-winning exhibit for the 1900 Paris Exposition, Du Bois and his students produced detailed hand-drawn artistically colored graphs and charts that depicted the journey of black Georgians from slavery to freedom.

Some of collection is shown in this post at the Public Domain Review (shared by Tressie McMillan Cottom yesterday); the full collection is online at the Library of Congress (LOC).

The one that caught my eye was this, showing marital status (“conjugal condition”) by age and sex for the Black population. I can’t find the source details in the LOC record, so I don’t know if it’s Georgia or national, but I presume it’s from tabulations of 1890 decennial census or earlier:

33915v

It’s artistic and meticulous and clearly informative, beautiful. So I tried to make a 2015 update to complement it. I used data from the 2015 American Community Survey via IPUMS.org, and did it a little differently.* Most importantly, I added two more conjugal conditions, cohabiting and separated/divorced. Second, I used five-year age groupings all the way up, instead of ten. Third, I detailed the age groups up to age 85. Here’s what I got:

du bois marstat replication.xlsx

Some very big differences: Much smaller proportions of African Americans married now. Also, much later marriage. In the 1900 figure more than 30% of men and 60% of women have been married by age 25; those numbers are 5-6% now. I don’t know how they counted separated/divorced people in 1900, but those numbers are high now at 31% for women and 24% for men at age 60-64. Widowhood is later now, as 42% of women were widowed before age 65 in 1900, compared with only 13% now (of course, that’s off a lower marriage rate, and remarried people are just counted as married). And of course cohabitation, which the chart doesn’t show for 1900. Note I included people in same-sex as well as different-sex couples.

So, thanks for indulging me. I hope you don’t think it’s frivolous. I just love staring at the old charts, and going through the (very different) steps of replicating it was really satisfying. (I also just love that in another 100 years someone might look back on this and say, “Wait, which one was Earth again?”)

Note: If you want to compare them side-by-side, here’s a go at that. The age ranges don’t line up perfectly but you can get the idea (click to enlarge):


* SAS code, ACS data, images, and the spreadsheet used for this post are shared as an Open Science Framework project, here.

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Is there sex selection among Asian immigrants in the US?

There is a 2008 paper reported in the New York Times in 2009, which found skewed sex ratios among children of immigrants from China, Korea, and India, if their older siblings were girls, using the 2000 Census. The implication was that some parents were using IVF or abortion to select boy children if their first two were girls — as is the case in their home countries. There has been some other research on this from the early 2000s, but I haven’t seen it updated since then.

I took a quick stab at it, but don’t have time right now to pursue it more thoroughly. So here’s the quick answer I got, and I shared my data, code, and results in an Open Science Framework project, here. I hope someone will be interested and pursue it further (using my approach or not). The files there include all different ethnic/racial groups.

This is preliminary.

Using the American Community Survey data from 2010-2015, from IPUMS.org, I took U.S.-born children ages 0-5, whose parents were both born in China, Korea, or India and both were present in the household. I counted the sex of any present siblings under age 15 (excluding step- and adopted children). Then I restricted the data to those with 2 older siblings, and compared the sex ratios among those who had 0 or 1 older sister to those who had 2 older sisters. I did this in a logistic regression controlling for individual years of age, and using ACS person weights. There are judgment calls to make about age, siblings, data and other issues. The older you get the more likely you are to have kids moving out in a way that is not sex-neutral (for example, if parents with girls are more or less likely to divorce), and so on. Should parents be matched on immigration status, siblings born abroad included, why the years 2010-2015, and so on. This is what I mean by preliminary. But these results are interesting enough to prompt me to post them and encourage discussion and more analysis.

Here’s what I got:

sex selection.xlsx

The sex differences between those with 0/1 older sister and 2 older sisters are not statistically significant at p.<.05 in each of the three groups, but they are for the combined set (.046). These comparison involve a few hundred cases. Here are the unweighted, unadjusted results:

sexratiosunweighted

As you can see, just a few families intervening to choose boys — or some other force rearranging the living arrangements, or survival, of children and families, and the difference would not hold. Still, I think it’s worth pursuing. Maybe someone already has. If you decide to get into it, feel free to use this stuff, and let me know what you come up with!

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Why Heritage is wrong on the new Census race/ethnicity question

Sorry this is long and rambly. I just want to get the main points down and I’m in the middle of other things. I hope it helps.

Mike Gonzalez, a Bush-era speech writer with no background in demography (not that there’s anything wrong with that), now a PR person for the Heritage Foundation, has written a noxious and divisive op-ed in the Washington Post that spreads some completely wrong information about the U.S. Census Bureau’s attempts to improve data collection on race and ethnicity. It’s also a scary warning of what the far right politicization of the Census Bureau might mean for social science and democracy.

Gonzalez is upset that “the Obama administration is rushing to institute changes in racial classifications,” which include two major changes: combining the Hispanic/Latino Origin question with the Race question, and adding a new category, Middle Eastern or North African (MENA). Gonzalez (who, it must be noted, perhaps with some sympathy, recently wrote one of those useless books about how the Republican party can reach Hispanics, made instantly obsolete by Trump), says that what Obama has in mind “will only aggravate the volatile social frictions that created today’s poisonous political climate in the first place.” Yes, the “poisonous political climate” he is upset about (did I mention he works for the Heritage Foundation?) is the result of the way the government divides people by race and ethnicity. Not actually dividing them, of course (which is a real problem), but dividing them on Census forms. (I hadn’t heard this particular version of why Trump is Obama’s fault — who knew?)

How will the new reforms make the Trump situation he helped create worse? Basically, by measuring race and ethnicity, which Gonzalez would rather not do (as suggested by the title, “Think of America as one people? The census begs to differ,” which could have been written at any time in the past two centuries).

Specifically, Gonzalez claims, completely factually inaccurately, that Census would “eliminate a second question that lets [Hispanics] also choose their race.” By combining Hispanic origin and race into one question — on which, as before, people will be free to mark as many responses as they like — Gonzalez thinks Census would “effectively make ‘Hispanic’ their sole racial identifier.” He is upset that many Latinos will not identify themselves as “White” if they have the option of “Hispanic” on the same question, even if they are free to mark both (which he doesn’t mention). Some will, but that is not because anyone is taking away any of their choices.

The Census Bureau, of course, because they always do, because they are excellent, has done years of research on these questions, including all the major stakeholders in a long interactive process that is scrupulously documented and (for a government bureaucracy) quite transparent. Naturally not everyone is happy, but in the end the trained demographic professionals come down on the side of the best science.

Race that Latino

The most recent report on the research I found was a presentation by Nicholas Jones and Michael Bentley from the Census Bureau. This is my source for the research on the new question.

First, why combine Hispanic with race? You have probably seen the phrase “Hispanics may be of any race” on lots of reports that use Census or other government data. The figure below is from the first edition of my book, using 2010 data, in which I group all 50 million Hispanics, and show the races they chose: about half White, the rest other race or more than one race (usually White and other race). Notice that by this convention Hispanics are removed from the White group anyway, just because we don’t want to have people in the same picture twice (“non-Hispanic Whites” is already a common construction).

family_fig03-02

The “may be of any race” language is the awkward outcome of an approach that treats Hispanic as an “ethnicity” (actually a bunch of national origins, maybe a panethnicity), while White, Black, Asian, Pacific Islander, and American Indian are treated as “races.” The distinction never really made sense. These things have been measured using self-identification for more than half a century, so we’re not talking about genetics and blood tests, we’re talking about how people identify themselves. And there just isn’t a major categorical difference between race and ethnicity for most people — people of any race or ethnicity may identify with a specific national origin (Italian, Pakistani, Mexican), as well as a “race” or panethnic identify such as Asian, or Latino. And now that the government allows people to select multiple races (since 2000), as well as answering the Hispanic question, there really is no good justification for keeping them separate. As you can see from my figure above, when we analyze the data we mostly pull all the Hispanics together regardless of their races. The new approach just encourages them to decide how they want that done, which is usually a better approach.

Of course, Asians and Pacific Islanders have been answering the “race” question with national origin prompts for several decades. There was no “Asian” checkbox in 2000 or 2010 (or on the American Community Survey). So they have been using their ethnicity to answer the race question all along — that’s because for some reason you just can’t get “Asian” immigrants, especially recent immigrants — that is, people from India, Korea, and Japan, Vietnam, and so on — to see themselves as part of one panethnic group. Go figure, must be the centuries of considering themselves separate peoples, even “races.” So, a new question that combines the more ethnic categories (Mexican, Pakistanis, etc.), with America’s racial identities (Black, White, etc.), just works better, as long as you let people check as many boxes as they want. This is what the “race” question looked like in 2014. Note there is no “Asian” checkbox:

acsrace2014

As a general guide, the questionnaire scheme works best when (a) everyone has a category they like, and (b) few people choose “other.” That is the system that will yield the most scientifically useful data. It also will tend to match the way people interact socially, including how they discriminate against each other, burn crosses on each other’s lawns, and randomly attack each other in public. We want data that helps us understand all that.

Through extensive testing, it has become apparent that, when given a question that offers both race and Hispanic origin together, Latino respondents are much more likely to answer Hispanic/Latino only, rather than cluttering up the race question with “some other race” responses (often writing in “Hispanic” or “Latino” as their “other race”). If I read the presentation right, in round numbers, given the choice of answering the “race” question with “Hispanic,” in the test data about 70% chose Hispanic alone; about 20% chose White along with Hispanic, and 5% choose two races. In fact, the number of Latinos saying their only race is White probably won’t change much; the biggest difference is that you no longer have almost 40% of Latinos saying they are “some other race,” or choosing more than one race (usually White and Other) which usually just means they don’t see a race that fits them on the list.

In the end, the size of the major groups (Hispanics and the major races) are not changed much. Here’s the summary:

betterhispanic

In fact, the only major group that will shrink is probably the non-group “multiracial” population, which today is dominated by Hispanics choosing White and “some other race.”

It’s really just better data. It’s not a conspiracy. It’s not eliminating the White race or discouraging assimilation of Hispanics. In short, keep calm and collect better data. We can fight about all that other stuff, too.

I’m sure Gonzalez doesn’t really think this will “eliminate Hispanics’ racial choices.” He’s dog-whistling to people who think the government is trying to reduce the number of Whites by not letting Hispanics be White. His statements are factually incorrect and the Washington Post shouldn’t have printed them. (I don’t know how the Post does Op-Eds; when I wrote one for the NY Times it was pretty thoroughly fact-checked.)

MENA

The Migration Policy Institute estimates there are about 2 million MENAs in the U.S. now, about half of them immigrants. This is a pretty small population, mostly Arab-speaking immigrants and their descendants, and more Christian (relative to Muslim) than the countries they left. This is especially true of the more recent immigrants, which don’t include a lot of Iranians (who aren’t Arab).

Census could have instead defined them by linguistic origin (Arab), and captured most, but they instead are going with country of origin, which is consistent with how the other race/ethnic groups are identified (for better or worse). Their testing showed that this measure captures most people with MENA ancestry, encourages them to identify their ancestry, cuts down on them identifying as White, and cuts down on them using “some other race.”

The difference is dramatic for those identifying as White, which fell from 85% to 20% in the test once a MENA category was offered. Would it be better if they just identified as White? I’m really not trying to shrink the count of Whites, I just think this is more accurate. I don’t care about the biology of Whiteness and whether Iranians are part of it, for example (and don’t ever say “Caucasian,” please), I care about the experience and identity of the people we’re talking about — as well as the beliefs of the people who hate them and those who want to protect them from discrimination. Counting them seems better than shoehorning them into a category most of them avoid when given the chance.

Here’s one version of the proposed new combined question, from that Census presentation:

newraceq

Yuck

Why not Mike Gonzalez to run Census? Unbelievably, he probably knows more about it than Trump’s education and HUD department heads know about their new portfolios.

But that’s just one odious possibility. It makes me kind of sick to think of the possible idiots and fanatics Trump might put in charge of the Census Bureau, after all this work on research and testing, designed to get the best data we can out of a very messy and imperfect situation.

What else would they do? Will they continue to develop ways to identify and count same-sex couples? The Supreme Court says they can get married, but there is no law that says the Census Bureau has to count them. What about multilingual efforts to reach immigrant communities? This has been a focus of Census Bureau development as well. And so on.

It is absolutely in Trump’s interest, and the interests of those who he serves (not the people who voted for him), to reduce the quality and quantity of social science data the government produces and enables us to produce.

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How do Black-White parents identify their children?

In 2015 the American Community Survey yields an estimate of 66,913 infants who have one Black parent and one White parent present in the household. (Either parent may be multiracial, too.)

What is the race of those infants? 73% of them were identified as both White and Black by whoever filled out the Census form.

bwinfants

(Note “other” doesn’t mean they specified “other,” it just means they used some other combination of races.)

These are children age 0 living with both parents, so it’s a pretty good bet they’re mostly biological parents, though some are presumably adopted. This is based on a sample of 507 such infants. If you pooled some years of ACS there is plenty to study here. Someone may already have done this – feel free to post in the comments.

That’s it, just FYI.

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