Here’s the 2020 update of a series I started in 2013. This year, after the basic facts, I’ll add some pandemic facts below.
Is it true that “facts are useless in an emergency“? I guess we’ll find out this year. Knowing basic demographic facts, and how to do arithmetic, lets us ballpark the claims we are exposed to all the time. The idea is to get your 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 (and tell the same stories over and over).
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 like, “The U.S. economy lost a record 20.5 million jobs in April“?
Everyone likes a number that appears to support their perspective. But that’s no way to run (or change) a society. The trick is to know the facts before you create or evaluate an 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.
These are 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 264 million and 396 million!).
This is only a few dozen 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:
The pandemic is changing everything. A lot of the numbers above may look different next year. Here are 21 basic pandemic facts to keep in mind — again, the point is to get a sense of scale, to inform your consumption of the daily flow of information (and disinformation). These are changing, too, but they are current as of August 31, 2020.
Global confirmed COVID-19 cases: 25 million
Confirmed US COVID-19 cases: 6 million
Second most COVID-19 cases: Brazil, 3.9 million
Third most COVID-19 cases: India, 3.6 million
Global confirmed COVID-19 deaths: 850,000
Confirmed US COVID-19 deaths: 183,000
Second most COVID-19 deaths: Brazil, 121, 000
Third most COVID-19 deaths: India: 65,000
Percent of U.S. COVID patients who have died: 3%
COVID-19 deaths per 100,000 Americans: 50
COVID-19 deaths per 100,000 non-Hispanic Whites: 43
COVID-19 deaths per 100,000 Blacks: 81
COVID-19 deaths per 100,000 Hispanics: 55
COVID-19 deaths per 100,000 Americans over age 65: 400
Annual deaths in the U.S. (these are for 2017): Total, 2.8 million
I was on a panel at the American Enterprise Institute, titled, “Demographic decline: National crisis or moral panic?” The event featured Lyman Stone, who argued that “demographic decline” in the U.S. is a national crisis, and my reply. Nick Eberstadt from AEI also offered comments. The moderator was AEI’s Karlyn Bowman.
The video of the event (which was on CSPAN) is below.
In my presentation I used the projections and other material I described earlier, here (where you can also link to the data and package I used). The gist of my talk is that with immigration we don’t have an issue of declining population.
I also emphasized the political implications of catastrophic “demographic decline” talk, which are based on a combination of doomsday demographics and increasing race/ethnic diversity. For that part I included these two figures, which I worked up for the next edition of my textbook. The first shows Census Bureau projections of the U.S. population by race/ethnicity, which is the basis for the White supremacist panic. (Important caveat about this figure is the assumptions about the ethnic identity of the descendants of today’s Latinos, see Richard Alba.)
For the politics of immigration, which is a giant topic, I presented this very simple figure showing the rise of Latin American and Asian immigration since 1965.
Here is the video on YouTube. If you prefer the CSPAN production style (or don’t want to give AEI click), theirs is here. My talk is 15 minutes, starting at 13:40.
Happy to hear your responses, including on the dicey issue of whether to participate in an AEI event.
(In the YouTube comments, the first person calls me a “Jewish supremacist” and demands to know my view on Israeli immigration policy, and another says, “This guy is through and through an open borders globalist.” So that’s the dialogue, too.)
Unless something changes outside the demogosphere, the divorce rate is going to go down in the coming years.
Divorce represents a number of problems from a social science perspective.
Most people seem to assume “the divorce rate” is always going up, compared with the good old days, which are supposed to be the whole past but are actually represented by the anomalous 1950s.
On other hand, social scientists have known for a few decades that “the divorce rate” has actually been declining since the 1980s. That shows up in the official statistics, with the simple calculation — known as the refined divorce rate — of the number of divorces per 1,000 married women.
On the third hand, the official statistics are very flawed. The federal system, which relies on states voluntarily coughing up their divorce records, broke down in the 1990s and no one fixed it (hello, California doesn’t participate). In the debate over different ways of getting good answers, a key 2014 paper from Sheela Kennedy and Stephen Ruggles showed that the decline in divorce after 1980 was mostly because the whole married population was getting older, and older people get divorced less. That refined divorce rate doesn’t account for age patterns. When you remove the age patterns from the data, you see a continuously increasing divorce rate. Yikes!
On the fourth hand, Kennedy and Ruggles stopped in about 2010. Since then, the very divorce-prone, multi-marrying, multi-divorcing Baby Boomers have moved further out of their peak action years, and it’s increasingly clear that divorce rates really are falling for younger people.
In my new analysis, which I wrote up as a short paper for submission to the Population Association of America 2019 meetings, I argue that all signs point to a divorce decline in the coming years. Here is the paper on SocArXiv, where you will also find the data and code. And here is the story, in figures (click to enlarge).
1. The proportion of married women who divorce each year has fallen 18% in the decade after 2008. (There are reasons to do this for women — some neutral, some good, some bad — but one good thing nowadays is at least this includes women divorcing women.) And when you control for age, number of times married, years married, education, race/ethnicity, and nativity, it has still fallen 8%.
2. The pattern of increasing divorce at older ages, described by Susan Brown and I-Fen Lin as gray divorce, is no longer apparent. In the decade after 2008, the only apparent change in age effects is the decline at younger ages, holding other variables constant.
3. The longer term trends, identified by Kennedy and Ruggles, which I extend to 2016, show that the upward trajectory is all about older people. These are prevalences (divorced people in the population), not divorce rates, but they are good for illustrating this trend.
4. In fact, when you look just at the last decade, all of the decline in age-specific divorce rates is among people under age 45. This implies there will be more older people who have been married a long time, which means low divorce rates. Also, their kids won’t be as likely to have divorced parents, although more kids will have parents who aren’t married, which might work in the other direction. (You can ignore then under-20s, who are 0.2% of the total.)
5. Finally, to get a glimpse of the future, I looked at women who report getting married in the year before the survey, and how they have changed between 2008 and 2016 on traits associated with the risk of divorce. They clearly show a lower divorce-risk profile. They are more likely to be in their first marriage, to have college degrees, to be older, and to have no children in their households (race/ethnicity appears to be a wash, with fewer Whites but more Latinas).
6. Finally finally, I also looked at the spouses of the newly-married women, and made an arbitrary divorce-protection scale, with one point to each couple for each spouse who was: age 30 or more, White or Hispanic, BA or higher education, first marriage, and no own children. Since 2008 the high scale scores have become more common and the low scores have become rarer.
7. It’s interesting that the decline in divorce goes against the (non-expert) conventional wisdom. And it is happening at a time when public acceptance of divorce has reached record levels (which might be part of why people think it’s growing more common — less stigma). Here are the trends in attitudes from Pew and Gallup:
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 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).
The 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.
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.
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.
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.
Over the course of two weeks in China, I saw several versions of signs like this:
This one is posted in the old-town section of Nanxun (now a tourist attraction), naturally, above a urinal.* Invoking civilization may be overblown for the problem of men standing too far away (which didn’t seem to be especially extreme, compared to U.S. urinals), but China has a long tradition of using dramatic slogans to call citizens to higher common purpose. Here was one that struck me, in downtown Shanghai:
This is from the Shanghai public health authorities. (No, I don’t know Chinese, but I love trying to use a dictionary, and I ask people.) The fascinating thing about that is the composition of the civilized family pictured: father, mother, two grandparents, and two children.
Fertility rates in China are well below replacement level, as they are in other East Asian countries, meaning the average woman will have fewer than two children in her lifetime and the population will eventually shrink (barring immigration). China’s total fertility rate nationally is probably at about 1.5. In Shanghai, a metro area with some 20 million people, the norm was already one child per family before the one-child policy was implemented in 1980, and fertility has continued to fall; it most recently clocked in at a shockingly low .88 per woman as of 2008.
Reasons for ultra-low fertility are varied and contested, but likely culprits include expensive housing and education costs for children. It was reported to me informally that about half of children can go to college-track high schools instead of vocational schools, and that is determined by a standardized test administered at the end of middle school. That puts tremendous pressure on parents with middle-class aspirations. Which helps explain the extensive system of expensive supplemental private education, as promoted by this ad I saw in an upscale mall:
The website for this company promises, “Super IQ, Wealth of Creativity, Instant Memory Capacity.” How many kids are you going to send to this private program?
One of the five perfect, super-involved parents at the parent-child class is a man, which may or may not seem like a lot. Of the many people taking their kids to school on scooters, I didn’t see a lot with more than one child, and the only picture I got was of one piloted by the apparent dad (note also something you don’t see here much: schoolboy in pink shirt):
This recalls another probable cause of low-low fertility, the gender-stuck family and employment practices that keep women responsible for children and other care work (scooter dads notwithstanding). In conjunction with women outperforming men in college graduation rates these days (as in the U.S.), this indirectly reduces fertility by leading to delayed marriage, and directly reduces fertility by causing parents to decide against a second child.
The weak system of care hurts on both ends, with people having fewer children because raising them is expensive, and people needing children to take care of old people because public support is lacking. This may be one reason why grandparents can have a positive effect on parents’ motivation to have children, as reported by Yingchun Ji and colleagues (including Feinian Chen, who hosted my visit). The fact that it is common for grandparents to provide extensive care for their grandchildren, as Feinian Chen has described (paywall), presumably helps strengthen their pronatal case.
Lots of pictures of grandparents taking care of a single grandchild to choose from. Here’s one, from the (awesome) Shanghai Museum:
The one-child policy ended in 2016, and couples no longer have to get permission to have a first or second child (but they do for a third or more). This change alone, although a better-late-than-never thing, may not do much to increase birth rates. That is the conclusion from studies of families for whom the policy was relaxed earlier. Sadly, although birth rates were already falling dramatically in the 1970s and the one-child policy was not responsible for the trend, the policy still (in addition to large scale human rights abuses) created many millions of one-child families that will struggle to meet intergenerational care obligations in the absence of adequate public support. (Here’s a good brief summary from Wang Feng, Baochang Gu, and Yong Cai.)
This is a challenge for civilization.
The pictures here, and a few hundred more, are on my Flickr site under creative commons license.
* Americans who love the funny translations of signs in China may be in for some disappointment, as the Standardization Administration has announced plans to implement thousands of stock translations in the service sector nationwide.
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:
* I put the data file, the Census Bureau description, and the Excel file on the Open Science Framework here: https://osf.io/qanre/.
[SKIP TO THE END for a mystery-partly-solved addendum]
Normally when we teach demography we use population pyramids, which show how much of a population is found at each age. They’re great tools for visualizing population distributions and discussing projections of growth and decline. For example, consider this contrast between Niger and Japan, about as different as we get on earth these days (from this cool site):
It’s pretty easy to see the potential for population growth versus decline in these patterns. Finding good pyramids these days is easy, but it’s still good to make some yourself to get a feel for how they work.
So, thinking I might make a video lesson to follow up my blockbuster total fertility rate performance, I gathered some data from the U.S., using the 2013 American Community Survey (ACS) from IPUMS.org. I started with 10-year bins and the total population (not broken out by sex), which looks like this:
There’s the late Baby Boom, still bulging out at ages 50-59 (born 1954-1963), and their kids, ages 20-29. So far so good. But why not use single years of age and show something more precise? Here’s the same data, but showing single years of age:
That’s more fine-grained. Not as much as if you had data by months or days of birth, but still. Except, wait: is that just sample noise causing that ragged edge between 20 and about 70? The ACS sample is a few million people, with tens of thousands of people at each age (up age 75, at least), so you wouldn’t expect too much of that. No, it’s definitely age heaping, the tendency of people to skew their age reporting according to some collective cognitive scheme. The most common form is piling up on the ages ending with 0 and 5, but it could be anything. For example, some people might want to be 18, a socially significant milestone in this country. Here’s the same data, with suspect ages highlighted — 0’s and 5’s from 20 to 80, and 18:
You might think age heaping results from some old people not remembering how old they are. In the old days rounding off was more common at older ages. In 1900, for example, the most implausible number of people was found at age 60 — 1.6-times as many as you’d get by averaging the number of people at ages 59 and 61. Is that still the case? Here it is again, but with the red/green highlights just showing the difference between the number of people reported and the number you’d get by averaging the numbers just above and below:
Proportionately, the 70-year-olds are most suspicious, at 10.8% more than you’d expect. But 40 is next, at 9.2%. And that green line shows extra 18-year-olds at 8.6% more than expected.
Unfortunately, it’s pretty hard to correct. Interestingly, the American Community Survey apparently asks for both an age and a birth date:
If you’re the kind of person who rounds off to 70, or promotes yourself to 18, it might not be worth the trouble to actually enter a fake birth date. I’m sure the Census Bureau does something with that, like correct obvious errors, but I don’t think they attempt to correct age-heaping in the ACS (the birth dates aren’t on the public use files). Anyway, we can see a little of the social process by looking at different groups of people.
Up till now I’ve been using the full public use data, with population weights, and including those people who left age blank or entered something implausible enough that the Census Bureau gave them an age (an “allocated” value, in survey parlance). For this I just used the unweighted counts of people whose answers were accepted “as written” (or typed, or spoken over the phone, depending on how it was administered to them). Here are the patterns for people who didn’t finish high school versus those with a bachelor’s degree or higher, highlighting the 5’s and 0’s (click to enlarge):
Clearly, the age heaping is more common among those with less education. Whether it’s really people forgetting their age, rounding up or down for aspirational reasons, or having trouble with the survey administration, I don’t know.
Is this bad? As much as we all hate inaccuracy, this isn’t so bad. Fortunately, demographers have methods for assessing the damage caused by humans and their survey-taking foibles. In this case we can use Whipple’s index. This measure (defined in this handy United Nations slideshow) takes the number of people whose alleged ages end in 0 or 5 and multiplies that by 5, then compares it to the total population. Normally people use ages 23 to 62 (inclusive), for an even 40 years. The amount by which people reporting ages 25, 30, 35, 40, 45, 50, 55, and 60 are more than one-fifth of the population ages 23-62, that’s your Whipple’s index. A score of 100 is perfect, and a score of 500 means everyone’s heaped. The U.N. considers scores under 105 to be “very accurate data.” The 2013 ACS, using the public use file and the weights, gives me a score of 104.3. (Those unweighted distributions by education yield scores of 104.0 for high school dropouts and 101.7 for college graduates.) In contrast, the Decennial Census in 2010 had a score of just 101.5 by my calculation (using table QT-P2 from Summary File 1). With the size of the ACS, this difference shouldn’t have to do with sampling variation. Rather, it’s something about the administration of the survey.
Why don’t they just tell us how old they really are? There must be a reason.
The age 18 pattern is interesting — I don’t find any research on desirable young-adult ages skewing sample surveys.
This is all very different from birth timing issues, such as the Chinese affinity for births in dragon years (every twelfth year: 1976, 1988…). I don’t see anything in the U.S. pattern that fits fluctuations in birth rates.
I focused one education above, but another explanation was staring me in the face. I said “it’s something about the administration of the survey,” but didn’t think to check for the form of survey people took. The public use files for ACS include an indicator of whether the household respondent took the survey through the mail (28%), on the web (39%), through a bureaucrat at the institution where they live (group quarters; 5%), or in an interview with a Census worker (28%). This last method, which is either a computer-assisted telephone interview (CATI) or computer-assisted personal interview (CAPI), is used when people don’t respond to the mailed survey.
It turns out that the entire Whipple problem in the 2013 ACS is due to the CATI/CAPI interviews. The age distributions for all of the other three methods have Whipple index scores below 100, while the CATI/CAPI folks clock in at a whopping 108.3. Here is that distribution, again using unweighted cases:
There they are, your Whipple participants. Who are they, and why does this happen? Here is the Bureau’s description of the survey data collection:
The data collection operation for housing units (HUs) consists of four modes: Internet, mail, telephone, and personal visit. For most HUs, the first phase includes a mailed request to respond via Internet, followed later by an option to complete a paper questionnaire and return it by mail. If no response is received by mail or Internet, the Census Bureau follows up with computer assisted telephone interviewing (CATI) when a telephone number is available. If the Census Bureau is unable to reach an occupant using CATI, or if the household refuses to participate, the address may be selected for computer-assisted personal interviewing (CAPI).
So the CATI/CAPI people are those who were either difficult to reach or were uncooperative when contacted. This group, incidentally, has low average education, as 63% have high school education or less (compared with 55% of the total) — which may explain the association with education. Maybe they have less accurate recall, or maybe they are less cooperative, which makes sense if they didn’t want to do the survey in the first place (which they are legally mandated — i.e., coerced — to do). So when their date of birth and age conflict, and the Census worker tries to elicit a correction, maybe all hell breaks lose in the interview and they can’t work it out. Or maybe the CATI/CAPI households have more people who don’t know each other’s exact ages (one person answers for the household). I don’t know. But this narrows it down considerably.
I was replaced on the guest list for KCRW’s To the Point discussion about Jonathan Last’s book, What To Expect When No One’s Expecting: America’s Coming Demographic Disaster. But before I was cut I did some preparation — read some of the book and made some notes.
Last is a writer for the Weekly Standard(in which capacity he recently suggested that, rather than try to reach out to single people, the GOP should instead work on convincing more people to get married), who also wrote for First Things, a Christian conservative website. His essay in the Wall Street Journal sparked my initial post, but the book is more extreme than that column was.
Last doesn’t add substantively to the general concern that below-replacement fertility causes problems, except to exaggerate it cartoonishly for the U.S. (“The root cause of most of our problems is our declining fertility rate”). The historical perspective is so weak here I feel the need to remind him that caring for aging Baby Boomers is a problem not of low fertility but high fertility. Were it not for the high fertility of the Baby Boomers’ parents, we would have had gradually declining long-run fertility levels and a working-age population much more up for the task of funding Medicare and Social Security.
In the book he relies heavily on Phillip Longman, the author of “The Empty Cradle,” whom I’ve written about before, but also summons (without mentioning it) Charles Murray’s Coming Apart, which bemoans the divergent family structures of middle- and working-class White America and chastises the rich for being too self-absorbed and pleasure-driven to keep up their responsibilities as moral compasses. Thus, he tuts:
The bearing and raising of children has largely become the province of the lower classes.
Last and Longman are helping the American patriarchal right get its desire for “traditional” family structures in sync with corporate America’s amoral economic growth obsession, and it turns out boosting fertility is a message they can all get behind (plus it pleases both evangelical Protestant and conservative Catholic culture warriors).
Of course, fertility rates in the U.S. fell after the Baby Boom as women’s employment rates and educational attainment increased. And those women with better opportunities have fewer children, on average. (However, this relationship is not universal or inevitable — see developments in Norway, for example.) But Last doesn’t want to create the impression that his wish for higher fertility implies opposition to women’s progress.
I’d also like to offer a preemptive defense against readers who may take this book to be a criticism of the modern American woman. Nothing could be further from my intent. … The more educated a woman is, on average, the fewer children she will have. To observe this is not to argue that women should be barefoot, pregnant, and waiting at home for their husbands every night with a cocktail and a smile.
But that he suggests we have more children — without taking steps to reconcile our endemic work-family conflicts and persistent gender imbalances (he’s not advocating universal childcare or healthcare, better welfare, paid family leave or a shorter workweek) — means that even if he’s not arguing for a return to barefoot-and-pregnant status, he’s at least willing to live with it.
His passing nod to Esther Boserup was interesting to me. Writing in the 1960s and 1970s (which Last carelessly calls “a century ago,” after apparently skimming her Wikipedia entry), Boserup argued that population pressure spurred agricultural innovation. That is, farmers figured out how to rotate land more efficiently, for example, when there was more demand for farmland (and food). I don’t know how well this theory is holding up in the historical scholarship (I don’t think it explains European divergence from China, for example) but it is interesting — and we’ve now spent as much time thinking about it as Last did).
From this Last declares that the reverse is also true, that postindustrial societies suffer a lack of innovation when populations shrink. That is a question Boserup was unlikely to have troubled herself with (but let me know if I’m missing something she wrote on it). However, I could conjure the opposite hypothesis – that a rapidly shrinking population would spur a different kind of innovation in postindustrial society. For example, we may face pressure for old people to be more productive, as they delay retirement; and to invest more wisely (and heavily) in the smaller cohorts of children’s education and skill development.
Last goes out of his way to say (perhaps too much) that he’s not against immigration, without which American fertility rates would be much lower. He is just against the immigration of people who don’t assimilate into America’s Christian majority. He writes:
A reasonably liberal program of immigration is necessary for the longterm health of our country. Yet at the same time, this liberal approach to immigration should be coupled with a staunchly traditionalist view of integration. America has been lucky in the way it has assimilated most of its immigrants. Europe—and France in particular—has not. “Europe” as we have known it for 15 centuries is almost certain to fade away in the next 50 years, replaced by a semi-hostile Islamic ummah. All that will remain of what we traditionally know as “Europe” is the name [It’s not clear why the hostile Islamic majority of 2063 would retain the name “Europe” -pnc]. This change was not inevitable; it is the result of a policy choice made by adherents of a truly radical faith: multiculturalism. … Tolerance need not be surrender and a certain amount of cultural chauvinism is necessary for societal coherence.” (p. 169)
“Racism” is the wrong term for this attitude. I guess his term “cultural chauvinism” is accurate because it assumes a cultural superiority. But that doesn’t quite capture the animus. Anyway: If the problem is falling fertility, why worry about the culture that the fertile immigrants bring? It’s just possible that Last’s problem is not just with fertility.
Like Longman, Last is sad about the demise of religion in the “public square,” which reduces fertility. In this he reveals his apocalyptic Christian moorings:
Of all of the evolutions in twentieth-century America, the most consequential might be the exodus of religion from the public square.
Really. More consequential than civil rights, women’s rights, science, public health, militarism and Wall Street? And isn’t exodus a strong word for what’s happened? There’s only one reason to believe a moderate decline in religiosity is more important than anything else: Because God said so. Anyway, besides ending the War on Christmas, Last also wants us to give credit for births where it is due (to God).
America is the most demographically healthy industrialized nation; it is also the most religiously devout. This is not a coincidence. … There is no reason for wishing the United States to be a theocracy. That said, it is important we preserve the role of religion in our public square, resisting those critics who see theocracy lurking behind every corner. Our government should be welcoming of, not hostile to, believers—if for no other reason than they’re the ones who create most of the future taxpayers. After all, there are many perfectly good reasons to have a baby. (Curiosity, vanity, and naïveté all come to mind.) But at the end of the day, there’s only one good reason to go through the trouble a second time: Because you believe, in some sense, that God wants you to.
I guess that means atheists don’t have a good reason to have more than one child. (Are there multiple-child atheists out there to respond to this?) Anyway, it’s usually not a good sign when an author follows “There is no reason for wishing the United States to be a theocracy,” with, “That said…”
We can see the depth of Last’s commitment to the long term in his discussion of transportation. One reason New Englanders and other liberals don’t have enough children, he believes, is because land is too expensive where they live. So they have small houses and long commutes, which aren’t conducive to child-rearing.
The answer is not more public transportation. Light rail might work for the child-free. (Or it might not; there is a stark divide in the literature on mass transit.) But parents trying to balance work and children need the flexibility automobiles provide; they cannot easily drop a child at a babysitter or school, then take a train to work, then train home, and then fetch the child. (If you don’t believe me, you try it.) The solution is building more roads.
That’s our destiny? A more efficient suburban sprawl to nurture our larger families? Doesn’t he care about climate change? Maybe, maybe not. He writes in a footnote:
The only environmentalist concern that population [growth] might legitimately affect is climate change, a subject so fraught with theological division that I’ll leave it be.
What courage, refusing to genuflect the climate-change authorities like that. And yet what cowardice to refuse to take a position in the face of “theological division.” That’s some combination.
Never one to wait till the last minute, I completed the syllabus for my graduate seminar with more than 12 hours to spare.
At UNC the sociology department offers a two-seminar series for students starting out with a concentration in demography, which is also standard for predoctoral trainees at the Carolina Population Center. The course has passed around the department, offering the best of our different perspectives — as well as the risk of inertia. I overhauled it quite a bit, but it still owes lots to Lisa Pearce and Anthony Perez, who taught it most recently.
Took me a long time. But what a moment! Looking down the list of two books and 55 other required or optional readings over 13 weeks, I think: how much would you know if you really read all that? And also: there’s probably no one in the world (not even me) who’s read this combination of things before. Etc.
Here’s a teaser: one graph I made for illustrating population growth. It replicates one John Bongaarts made in 1975, showing where the countries of the world lie on the birth-rate / death-rate axis. Bottom line: when birth rates are higher, population grows. The other 54+ readings are details…