Tag Archives: demography

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).


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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How I engaged my way to excellent research success and you can too

kid on string phone in front of computer screen

Kid photo CC from MB Photography; collage by pnc.

Too often sociologists think of social media, or online communications generally, primarily as a way of broadcasting their ideas and building their audience, instead of as a way of deepening their engagement with different people and perspectives. You see this when academics start a twitter account right when their book is coming out. Nothing wrong with that, but it’s very limited. A crucial part of being a public scholar, public intellectual, or a public sociologist, etc., is reading, listening, and learning through engagement, and digital communication can enhance the metabolism of that process. Especially important is the chance to learn from people you don’t normally interact with. For all the complaints about social media bubbles, some true, social media also offers huge efficiencies for meeting and learning from new people.

As I’m writing an essay about this, I thought of my work on divorce as an example. So here’s that thread, condensed.

A divorce story

In 2008 I was teaching an undergraduate Family Sociology course at the University of North Carolina, and included a section on divorce based on other people’s research. I was also developing a proposal for my own textbook, which at the time framed family structures and events, including divorce, as consequences and causes of inequality. I was reading research about divorce along with many other family issues that were outside of my formal training and experience (the closest I had come to a family demography or family sociology course was a seminar on Gender, Work & Family in grad school).

Then in 2009, I wrote a post on my pretty new blog criticizing something bad the Brad Wilcox had written about divorce. I was trying to be newsy and current, and he was claiming that the recession was lowering divorce rates because hard times pulled people together. We didn’t yet know what would happen in the recession. (In the comments, Louise Roth suggested it would take time for divorces “caused” by the recession to show up, which turned out to be true.)

I kept on that path for a while, criticizing Wilcox again for similar work in 2011. By then — prompted by the combination of my reading, the blog debates, and the news coverage around families and the recession — I was working on a paper on divorce using the American Community Survey. I presented it at a demography meeting in the summer of 2011, then revised and presented it at the Population Association of America the following spring. I blogged about this a couple more times as I worked on it, using data on state variation, and Google searches, each time getting feedback from readers.

A version of the paper was rejected by Demography in the summer of 2011 (which generated useful reviews). Although now discredited as not peer-review-publishable (which no one knew), my commentary on divorce and the recession was nevertheless featured in an NPR story by Shankar Vedantam. Further inspired, I sent a new version of the paper (with new data) to Demographic Research, which also rejected it. I presented on the work a couple of times in 2012, getting feedback each time. By August 2012, with the paper still not “published,” I was quoted describing my “divorce/recession lull-rebound hypothesis” in New York magazine.

The news media pieces were not simply my work appearing in the news, in a one-directional manner, or me commenting on other people’s research, but rather me bringing data and informed commentary to stories the reporters were already working on. Their work influenced my work. And all along that news coverage was generating on- and offline conversations, as I found and shared work by other people working on these topics (like the National Center for Marriage and Family Research, and the Pew Research Center). Looking back over my tweets about divorce, I see that I covered divorce and religion, disabilities, economics, and race/ethnic inequality, and also critiqued media coverage. (Everything also got discussed on Facebook, in a smaller semi-private circle.)

By 2014 I finally got the paper — now with even newer data — published in a paywalled peer-reviewed journal, in Population Research and Policy Review. This involved writing the dreaded phrase, “Thank you very much for the opportunity to revise this paper again.” (Submitted October 2012, revision submitted August 2013, second revision submitted January 2014, final revision April 2014.) The paper, eventually titled, “Recession and Divorce in the United States, 2008-2011,” did improve over this time as new data provided better leverage on the question, and the reviewers actually made some good suggestions.

Also in 2014 the descriptive analysis was published in my textbook. The results were reported here and there, and expanded into the general area of family-recession studies, including this piece in the Conversation. I also developed a method of projecting lifetime divorce odds (basically 50%), for which I shared the data and code, which was reported on here. Along the way I also did some work on job characteristics and divorce (data and code, working paper). When I posted technical notes, I got interesting responses from people like economist Marina Adshade, whom I’ve never met.

So that’s an engagement story that includes teaching, the blogosphere and social media, news media, peer-reviewed publishing, conference presentations and colloquium talks. I did research, but also argued about politics and inequality, and taught and learned demography. It’s not a story of how I used social media, or the news media, to get the word out about my research, although that happened, too. The work product, not just the “publications,” were all public to varying degrees, and the discussions included all manner of students, sociologists, reporters, and interested blog or Twitter readers, most of whom I didn’t know or wouldn’t have met any other way.

So I can’t draw a line dividing the “engagement” and the “research,” because they weren’t separate processes.

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No, early marriage is not more common for college graduates

Update: IFS has taken down the report I critiqued here, and put up a revised report. They have added an editor’s note, which doesn’t mention me or link to this post:

Editor’s Note: This post is an update of a post published on March 14, 2018. The original post looked at marriage trends by education among all adults under age 25. It gave the misimpression that college graduates were more likely to be married young nowadays, compared to non-college graduates.

At the Institute for Family Studies, Director of Research Wendy Wang has a post up with the provocative title, “Early Marriage is Now More Common For College Graduates” (linking to the Internet Archive version).

She opens with this:

Getting married at a young age used to be more common among adults who didn’t go to college. But the pattern has reversed in the past decade or so. In 2016, 9.4% of college graduates ages 18 to 24 have ever been married, which is higher than the share among their peers without a college degree (7.9%), according to my analysis of the most recent Census data.

And then the dramatic conclusion:

“What this finding shows is that even at a young age, college-educated adults today are more likely than their peers without a college degree to be married. And this is new.”

That would be new, and surprising, if it were true, but it’s not.

Here’s the figure that supports the conclusion:


It shows that 9.4% of college graduates in the age range 18-24 have been married, compared with 7.9% of those who did not graduate from college. (The drop has been faster for non-graduates, but I’m setting aside the time trend for now.) Honestly, I guess you could say, based on this, that young college graduates are more likely than non-graduates to “be married,” but not really.

The problem is there are very very few college graduates in the ages 18-19. The American Community Survey, which they used here, reports only about 12,000 in the whole country, compared with 8.7 million people without college degrees ages 18-19 (this is based on the public use files that IPUMS.org uses; which is what I use in the analysis below). Wow! There are lots and lots of non-college graduates below age 20 (including almost everyone who will one day be a college graduate!), and very few of them are married. So it looks like the marriage rate is low for the group 18-24 overall. Here is the breakdown by age and marital status for the two groups: less than BA education, and BA or higher education — on the same population scale, to help illustrate the point:


If you pool all the years together, you get a higher marriage rate for the college graduates, mostly because there are so few college graduates in the younger ages when hardly anyone is married.

To show the whole thing in terms of marriage rates, here is the marital status for the two groups at every age from 15 (when ACS starts asking about marital status) to 54.


Ignoring 19-21, where there are a tiny number of college graduates, you see a much more sensible pattern: college graduates delay marriage longer, but then have higher rates at older ages (starting at age 28), for all the reasons we know marriage is ultimately more common among college graduates. In fact, if you used ages 15-24 (why not?), you get an even bigger difference — with 9.4% of college graduates married and just 5.7% of non-college graduates. Why not? In fact, what about ages 0-24? It would make almost as much sense.

Another way to do this is just to look at 24-year-olds. Since we’re talking about the ever-married status, and mortality is low at these ages, this is a case where the history is implied in the cross-sectional data. At age 24, as the figure shows, 19.9% of non-college graduates have been married, compared with 12.9% of college graduates. Early marriage is not more common for college graduates.

In general, I don’t recommend comparing college graduates and non-graduates, at least in cross-sectional data, below age 25. Lots of people finishing college below age 25 (and increasingly after that age as well). There is also an important issue of endogeneity here, which always makes education and age analysis tricky. Some people (mostly women) don’t finish college because they get married and have children).

Anyway, it looks to me like someone working for a pro-marriage organization saw what seemed like a story implying marriage is good (that’s why college graduates do it, after all), and one that also fits with the do-what-I-say-not-what-I-do criticism of liberals, who are supposedly not promoting marriage among poor people while they themselves love to get married (a critique made by Charles Murray, Brad Wilcox, and others). And, before thinking it through, they published it.

Mistakes happen. Fortunately, I dislike the Institute for Family Studies (see the whole series under this tag), and so I read it and pointed out this problem within a couple hours (first on Twitter, less than two hours after Wang tweeted it). It’s a social media post-publication peer review success story! If they correct it.


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Visiting Israel, with demography (this is not sustainable edition)

With audio, and photographs!

Israel’s trajectory is unsustainable in more ways than one.

The political situation is not the subject of this post, but it’s necessary to say at the beginning that the oppression of Palestinians by the state of Israel, made possible by the United States, is morally unacceptable and relative to all the other national oppression in the world rates pretty bad. For that reason, although I don’t endorse the movement for academics to boycott Israel, I oppose the movement to censor it.

So, last month I went to Israel for the first time since 1979. Since this is a blog I can include both academic and personal observations from that visit.

The Shuk Market, Jerusalem, on Friday afternoon (photo pnc: https://flic.kr/p/23AxGdJ)


The workshop I was invited to attend was a joint effort of colleagues at the University of Maryland and Tel Aviv University, with the Israel Forum for Population, Environment, and Society, called “Interdisciplinary Perspectives on Culture and Sustainable Population Dynamics.” The main organizers were Alon Tal and Michele Gelfand. Tal has written a very good book called, The Land Is Full: Addressing Overpopulation in Israel, which is both a demographic history and an ecological analysis, from which I learned a lot.

I’m not expert on the ecological stuff, but the demography is quite shocking on its own. (In the demography here, unless noted I’m talking about Israel within its pre-1967 borders, which is now most of these statistics are reported.) Israel is very densely populated, although everyone I talked to (besides demographers) was surprised to hear it. That may be because when you travel outward from the cities, it quickly looks like barren countryside — it’s just that the empty countryside doesn’t go on very far before you get to the sea or a border.

The population of about 1 million in 1950 is now almost 9 million, having doubled in the past 30 years. This figure shows the population density of countries with 5 million or greater population in 2016, with select countries labeled using World Bank codes and those with populations over 100 million circled. The 1986 density is on the x-axis and the 2016 density is on the y-axis, so to distance above the diagonal is the increase. That’s Israel way up at 200, 400 (click to enlarge).

Population density 1986-2016The rapid rise in population density in Israel will invariably exacerbate their problems with water, energy, transportation, housing, habitats, pollution, and — of course — politics. These are all pretty bad problems, which Tal explains at length.

Contrary to popular belief, since the wave of ex-USSR immigrants in the early 1990s, most of the population growth has been from births, not immigration. And contrary to other popular beliefs, the growth is now — and increasingly — driven not by the Arab or Muslim populations but by the so-called Ultra Orthodox or Haredi population. (Here I cite a paper by Barbara Okun, but we also heard from demographers Eliahu Ben Moshe and Ameed Saabneh, whose presentations I do not have to share.) This figure from Tal’s book shows the Jewish/Arab breakdown. Where in 1997 there were about 2.3 Jewish births for each Arab birth, in 2013 it was more than 3-to-1:


Overall, Arab and Muslim fertility have fallen a lot, and Jewish fertility has not (most but not all Arabs are Muslim; some Jews have Arab ancestry, but they don’t count as Arab). Here are the overall trends, using completed fertility by birth cohorts, from this paper by Barbara Okun:


The Arab/Muslim trend looks like a lot of poor countries, while the Jewish and total trends (Israel is about 80% Jewish) does not look like a lot of rich countries. As a result, Israel has the highest birth rate of all OECD countries, by a lot, and it’s now rising (runner-up Mexico shown for comparison):


Why is Israel’s birth rate rising? Increasingly, because of the Ultra-Orthodox population, among whom the most recent cohorts to reach age 40 have averaged about 7 children per woman:


Right now the Haredi population are 13% of the total Jewish population. Not-that-long story short, the Haredi will be the majority of Israeli Jews pretty soon (maybe 50 years). And because of population momentum (the next generation’s parents are already born), that is likely almost no matter what else happens.

As Ben Moshe pointed out, this process of rising ultra-orthodox dominance may be accelerated if the “secular” Jews (two-thirds of whom think having a religious wedding is “very important,” and 38% of whom fast on Yom Kippur) reduce their fertility rates to something more like the European norm. If that happens, it won’t do much to slow Israel’s population growth, but it will change the composition of the population. The math of this is pretty dramatic.

Postmodern premodernism. She wears a fashionable wig, he wears an old European-style hat and coat, the baby (girl, just guessing) wears pink. (photo pnc: https://flic.kr/p/24BvW9C)

The idea of a policy to reduce birth rates — that is, Jewish birth rates — in Israel is so far a complete political non-starter. Even among secular Jews, Ben Moshe reports, 80% say they would like to have three children or more. State policy is very pro-natal. The national health insurance pays for unlimited IVF cycles, and Israel has more than 10-times as many IVF treatments per capita as the US does, and more than twice as many as the next highest country (as Daphna Carmeli reported). Same-sex couples can’t marry or adopt children, but they can produce and parent them with IVF or through surrogacy. Abortion is technically legal but discouraged. The state pays monthly child subsidies for each kid, and provides child care from age 3.

The Haredi population, which plays a pivotal role in the country’s parliamentary coalition, controls their own state-funded school curriculum, and they are exempt from the mandatory military service that most other Jews are required to perform. In addition to fostering resentment among the non-orthodox, this also means they get started on their childbearing earlier, since they don’t have military time after high school. Of course, these are not biologically distinct populations, and people can move in and out of the groups, but thus far the Haredi population is not experiencing much intergenerational defection, partly because of the institutional supports they have from the state.


Anyway, I had the chance at the workshop to offer remarks, which I present in edited form here, in a 15-minute audio clip.

One part is was a warning about “population policy” from Puerto Rico and China. And I commented on gender inequality, saying, “It’s indelicate to walk into a place and say that. On the other hand, if we look at the history of extremely high-fertility, very religiously-oriented, patriarchal societies, that’s what they are,” and talked about how education affects birth rates:

It’s one thing to increase an individual woman’s education and then see that she is less likely to have more children. But you’re not increasing her education when she’s 18, you’re increasing her educational opportunity when she’s 18, or her vision for herself 20 years in the future that’s going to change her behavior at age 18. If you say to an 18-year-old, “You live in a society where everybody goes to college, and women have good jobs when they come out,” then her behavior at age 18 is much less likely to be marriage and children right then. It’s more likely to be, “I will pursue this education, and then I’ll be in a better position to pursue my career, to bargain from a better position in terms of choosing a spouse,” and the behavior follows from that knowledge of the future.

Also some comments on the border situation, where I said, in a very roundabout way:

I think it’s interesting for the discussion of why do the secular Israel Jews still have such non-European fertility levels, and it partly is the context. Maybe it’s how religious were their parents, or their other relatives or their siblings, or maybe it’s their city or the culture they were brought up in in some way, or the policies of their government, but it’s also — in terms of the war and ethnic conflict — it may have to do with the political or ethnic or perceived national threat. And so in my idealistic world when we open all the borders, one source of conflict is actually reduced, and the people’s behavior is changed.

Here’s the talk:

There was a writeup on the workshop in the Jerusalem Post, here, which includes more from Alon Tal.

Entering the Western Wall Jewish area of the Old City in Jerusalem. (photo pnc: https://flic.kr/p/23AxGdJ)

Visiting Israel

As far as I’m concerned I’ve always been White in America, which is the dominant status. But once in a while being Jewish makes me feel I’m down a peg. Or even sometimes, for a fleeting minute, as the Nazis on Twitter like to tell me, that I’m not really White. Funny thing about being in Israel, for me, was that it felt kind of like being really White in America. My people were on top, as they usually are, but a little more specifically. Surprisingly, perhaps, this felt less morally compromising than I expected, at least in comparison to how I normally feel in America. It also reinforced my growing sense of Jewish as ethnicity rather than religion in the US context (I’m an atheist), which has of course been exacerbated by the current pro-Nazi regime and anti-Semitic attacks I get on Twitter since Trump took power.

Being a Jewish-American (the ethnic term) anti-Trump person on Twitter is odd. One of the weirder things I did not predict, but which I see very often, is the gotcha thing the anti-Semites give me when I speak out against Trump on xenophobia and the Mexican-border wall. For example, these are tweets I got from people I don’t know in response to posting this photo essay on the border wall in Contexts, without mentioning Israel.


Contrary to popular belief among Nazis, some Jews don’t support Israeli apartheid. (I wrote a post comparing the Israel/Palestine and US/Mexico borders, here.) Anyway, on top of that, I have family members in Israel whom I dearly love. And on top of that, some of those family members are Jews with whom I have the most in common about Israeli politics (and some, not much at all). So, it’s complicated.


On the bus in Jerusalem. (photo pnc: https://flic.kr/p/GxAkrE) Also on the bus was a sign that read: “Anyone may sit anywhere (except places marked for disabled people). Harassment of a passenger on this matter may be a criminal offense.” This was to stop ulta-orthodox men from forcing women to sit in the back of the bus, and represented a victory for feminists.

Of course, the closer you look the more “nuanced” things become. To Haredi folks, for example, there are large, vital differences between different Haredi communities, that you or I would probably find hard to discern. And for another example, there are a lot of negative attitudes toward the Haredi people from some secular Jews in Israel, for living off government benefits, not serving in the military, not letting the buses run on Saturday, and subjugating women. And sometimes, maybe just because I’m more defensive about anti-Semitism these days, those attitudes have a slight anti-Semitic aftertaste. So they are simultaneously the “most” Jewish people in a “Jewish state,” with outsized political and cultural influence, but also something like a disparaged minority.

Anyways, I have no conclusion.

These photos, and others from the trip, are on Flickr under Creative Commons license: https://flic.kr/s/aHsmeU5n6s.


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For social relationships outside marriage

Stephanie Coontz has a great piece in tomorrow’s New York Times titled, “For a Better Marriage, Act Like a Single Person.” From her intro:

Especially around Valentine’s Day, it’s easy to find advice about sustaining a successful marriage, with suggestions for “date nights” and romantic dinners for two. But as we spend more and more of our lives outside marriage, it’s equally important to cultivate the skills of successful singlehood. And doing that doesn’t benefit just people who never marry. It can also make for more satisfying marriages.

From there she develops the case with, as usual, a lot of the right research. Well worth a read.

Stephanie used two empirical bits from my work:

No matter how much Americans may value marriage, we now spend more time living single than ever before. In 1960, Americans were married for an average of 29 of the 37 years between the ages of 18 and 55. That’s almost 80 percent of what was then regarded as the prime of life. By 2015, the average had dropped to only 18 years.

In many ways, that’s good news for marriages and married people. Contrary to some claims, marrying at an older age generally lowers the risk of divorce. It also gives people time to acquire educational and financial assets, as well as develop a broad range of skills — from cooking to household repairs to financial management — that will stand them in good stead for the rest of their lives, including when a partner is unavailable.

The first figure, the average years spent in marriage between the ages of 18 and 55 is very easy to calculate. You just sum the proportion of people married at each age. Here’s what it looks like, comparing 1960 (from the decennial Census) and 2015 (from the American Community Survey), both from IPUMS.org (click to enlarge):


I think it’s a nice, simple way to show the declining footprint of marriage in American life. (I first did this, and described in the rationale, in 2010.)

The bit about older age at marriage being associated with lower odds of divorce is from this post. Here’s the result, showing odds of divorce in one year by age at marriage, with controls for duration, education, race/ethnicity, and nativity, for women in their first marriages (click to enlarge):
Divorce by age at marriage

There’s more discussion in the post, as well as in this followup post, which has this cool figure, where red is the highest odds of divorce and green is the lowest, and the axes are years married and age at marriage (click to enlarge):

Divorce By Age And Duration

My new book is out! Enduring Bonds: Inequality, Marriage, Parenting, and Everything Else That Makes Families Great and Terrible. Available all the usual places, plus here at the University of California Press, where Chapter 1 is available as a sample, and where instructors can request a review copy.

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Data analysis: Are older newlyweds saving marriage?

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Is the “institution” still in decline if the incidence of marriage rebounds, but only at older ages?

In my new book I’ve revisited old posts and produced this figure, which shows the refined marriage rate* from 1940 to 2015, with a discussion of possible futures:


The crash scenario – showing marriage ending around 2050, is there to show where the 1950-2014 trajectory is headed (it’s also a warning against using linear extrapolation to predict the future). The rebound scenario is intended to show how unrealistic the “revive marriage culture” people are. The taper scenario emerges as the most likely alternative; in fact, it’s grown more likely since I first made the figure a few years ago, as you can see by the 2010-2014 jag.

So let’s consider the tapering scenario more substantively — what would it look like? One way to get a declining marriage rate is if marriage is increasingly delayed, even if it doesn’t become less common; people still marry, but later. (If everyone got married at age 99, we would have universal marriage and a very low refined marriage rate.) I give some evidence for this scenario here.

These trends are presented with minimal discussion; I’m not looking at race/ethnicity or social class, childbearing or the recession; I’m not discussing divorce and remarriage and cohabitation, and I’m not testing hypotheses. (This is a list of research suggestions!) To make the subject more enticing as a research topic (and for accountability), I’ve shared the Census data, Stata code, and spreadsheet file used to make this post in this OSF project. You can use anything there you want. You can also easily fork the project — that is, make a duplicate of its contents, which you then own, and take off on your own trajectory, by adding to or modifying them.


For some context, here is the trend in percentage of men and women ever married, by age, from 1960. (“Ever married” means currently married, separated, divorced, or widowed.) This clearly shows both life-course delay and lifetime decline, but delay is much more prominent, at least so far. Even now, almost 90% of people have been married by age 60 or so, while the marriage rates for people under 35 have plummeted.


People become ever-married when they get first-married. We measure ever-married prevalence from a survey question on current marital status, but first-marriage incidence requires a question like the American Community Survey asks, “In the past 12 months, did this person get married?” Because they also ask how many times each person has been married, you can calculate a first marriage rate with this ratio:

(once married & married in the past 12 months) / (never married + (once married & married in the past 12 months))

Until recently it hasn’t been easy to measure first-marriage across all ages; now that we have the ACS marital events data (since 2008) we can. This allows us to look at the timing of first marriage, which means we can use current age-specific first-marriage rates to project lifetime ever-married rates under current conditions.

Here are the first-marriage rates for men and women, by age. Each set of bars shows the trend from 2008 to 2016. The left side shows men, by age; the right side shows women, by age; the totals for men and women are in the middle. This shows that first-marriage rates have fallen for men and women under age 35, but increased for those over age 35. The total first-marriage rate has rebounded from the 2013 crater, but is still lower than 2008.


This is a short-range trend, 9 years. It could be recession-specific, with people delaying marriage because of hardships, or relationships falling apart under economic stress, and then hurrying to marry a few years later. But it also fits the long-term trend of delay over decline.

The overall rates for men and women show that the 2014-2016 rebound has not brought first-marriage rates back to their 2008 level. However, what about lifetime odds of marriage? The next figure uses women’s age-specific first-marriage rates to project lifetime odds of marriage for three years: 2008, the 2013 crater, and 2016. This shows, for example, that at 2008 rates 59% of women would have married by age 30, compared with 53% in both 2013 and 2016.


The 2013 and 2016 lines diverge after age 30, and by age 65 the projected lifetime ever-married rates have fully recovered. This implies that marriage has been delayed, but not forgone (or denied).

Till now I’ve shown age and sex-specific rates, but haven’t addressed other things that might changed in the never-married population. Finally, I estimated logistic regressions predicting first-marriage among never married men and women. The models include race, Hispanic origin, nativity, education, and age. In addition to the year and age patterns above, the models show that all races have lower rates than Whites, Hispanics have lower rates than non-Hispanics, foreign-born people have higher rates (which explains the Hispanic result), and people with more education first-marry more (code and results in the OSF project).

To see whether changes in these other variables change the story, I used the regressions to estimate first-marriage rates at the overall mean of all variables. These show a significant rebound from the bottom, but not returning to 2008 levels, quite similar to the unadjusted trends above:


This is all consistent with the taper scenario described at the top. Marriage delayed, which reduces the annual marriage rate, but with later marriage picking up much of the slack, so that the decline in lifetime marriage prevalence is modest.

* The refined marriage rate is the number of marriages as a fraction of unmarried people. This is more informative than the crude marriage rate (which the National Center for Health Statistics tracks), which is marriages as a fraction of the total population. In this post I use what I guess you would call an age-specific refined first-marriage rate, defined above.

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Demographic facts your students should know cold

Here’s an update of a series I started in 2013, and updated in 2016.

Is it true that “facts are useless in an emergency“? Depends how you define emergency I guess. I used to have a little justification for why we need to know demographic facts, as “the building blocks of first-line debunking.” It’s facts plus arithmetic that let us ballpark the claims we are exposed to all the time. The idea was to get our radar tuned to identify falsehoods as efficiently as possible, to prevent them spreading and contaminating reality. Although I grew up on “facts are lazy and facts are late,” I actually still believe in this mission, I just shake my head slowly while I ramble on about it.

It started a few years ago with the idea that the undergraduate students in my class should know the size of the US population. Not to exaggerate the problem, but too many of them don’t, at least when they reach my sophomore level family sociology class. If you don’t know that fact, how can you interpret statements such as Trump’s “I’ve created over a million jobs since I’m president”? (The U.S. population grew by about 1.3 million between the 2016 election and the day he said that; CNN has a jobs tracker.)

What’s a number for? Lots of people disparage the nitpickers when they find something wrong with the numbers going around. But everyone likes a number that appears to support their argument. The trick is to know the facts before you know the argument, and for that you need some foundational demographic knowledge. This list of facts you should know is just a prompt to get started in that direction.


Here’s the list of current demographic facts you need just to get through the day without being grossly misled or misinformed — or, in the case of journalists or teachers or social scientists, not to allow your audience to be grossly misled or misinformed. Not trivia that makes a point or statistics that are shocking, but the non-sensational information you need to make sense of those things when other people use them. And it’s really a ballpark requirement (when I test the undergraduates, I give them credit if they are within 20% of the US population — that’s anywhere between 260 million and 390 million!).

This is only 25 facts, not exhaustive but they belong on any top-100 list. Feel free to add your facts in the comments (as per policy, first-time commenters are moderated). They are rounded to reasonable units for easy memorization. All refer to the US unless otherwise noted. Most of the links will take you to the latest data:

Fact Number Source
World Population 7.4 billion 1
US Population 326 million 1
Children under 18 as share of pop. 23% 2
Adults 65+ as share of pop. 15% 2
Official unemployment rate 4.3% 3
Unemployment rate range, 1970-2017 4% – 11% 4
Labor force participation rate, age 16+ 63% 9
Labor force participation rate range, 1970-2015 60% – 67% 9
Non-Hispanic Whites as share of pop. 61% 2
Blacks as share of pop. 13% 2
Hispanics as share of pop. 18% 2
Asians as share of pop. 6% 2
American Indians as share of pop. 1% 2
Immigrants as share of pop 13% 2
Adults age 25+ with BA or higher 30% 2
Median household income $54,000 2
Total poverty rate 14% 8
Child poverty rate 20% 8
Poverty rate age 65+ 9% 8
Most populous country, China 1.4 billion 5
2nd most populous country, India 1.3 billion 5
3rd most populous country, USA 324 million 5
4th most populous country, Indonesia 258 million 5
5th most populous country, Brazil 206 million 5
Male life expectancy at birth 76 6
Female life expectancy at birth 81 6
National life expectancy range 50 – 85 7

1. U.S. Census Bureau Population Clock

2. U.S. Census Bureau quick facts

3. Bureau of Labor Statistics

4. Google public data: http://bit.ly/UVmeS3

5. CIA World Factbook

6. National Center for Health Statistics

7. CIA World Factbook

8. U.S. Census Bureau poverty tables

9. Bureau of Labor Statistics

Handy one-page PDF: Demographic Facts You Need to Know 2017


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