Tag Archives: demography

Fertility rate implications explained

(Sorry for the over-promising title; thanks for the clicks.)

First where we are, then projections, with figures.

For background: Caroline Hartnett has an essay putting the numbers in context. Leslie Root has a recent piece explaining how these numbers are deployed by white supremacists (key point: over-hyping the downside of lower fertility rates has terrible real-world implications).

Description

The National Center for Health Statistics released the 2018 fertility numbers yesterday, showing another drop in birth rates, and the lowest fertility since the Baby Boom. We are continuing a historical process of moving births from younger to older ages, which shows up as fewer births in the transition years. I illustrate this each year by updating this figure, showing the relative change in birth rates by age since 1989:

change in birthrates by age 1989-2016.xlsx

Historically, postponement was associated with reduction in lifetime births — which is what really matters for population trends. When people were having lots of children, any delay reduced the total number. With birth rates around two per woman, however, there is a lot more room for postponement — a lot of time to get to two. (At the societal level, both reduction and postponement are generally good for gender equality, if women have good health and healthcare.)

This means that drops in what we demographers call “period” fertility (births right now) are not the same as drops in “completed” fertility (births in a lifetime), or falling population in the long run. The period fertility measure most often used, the unfortunately named total fertility rate (TFR), is often misunderstood as an indicator of how many children women will have. It is actually how many births they are having right now, expressed in lifetime terms (I describe it in this video, with instructions).

Lawrence Wu and Nicholas Mark recently showed that despite several periods of below “replacement” fertility (in terms of TFR), no U.S. cohort of women has yet finished their childbearing years with fewer than two births per woman. Here is the completed fertility of U.S. women, by year of birth, as recorded by the General Social Survey. By this account, women born in the early 1970s (now in their late-forties by 2018) have had an average of 2.3 children.

Stata graph

Whether our streak of over-two completed fertility persists depends on what happens in in the next few years (and of course on immigration, which I’ll get to).

Last year at this time I summed up the fertility situation and concluded, “sell stock now,” because birth rates fell for women at all ages except over 40. That kind of postponement, I figured, based on history, reflected economic uncertainty and thus was an ill omen for the economy. The S&P 500 is up 5% since then, which isn’t bad as far as my advice goes. And I’m still bearish based on these birth trends (I bet I’ll be right before fertility increases).

Projection

It is very hard to have an intuitive sense of what demographic indicators mean, especially for the future. So I’ve made some projections to show the math of the situation, to get the various factors into scale. My point is to show what the current (or future) birth rates imply about future growth, and the relative role of immigration.

These projections run from 2016 to 2100. I made them using the Census Bureau’s Demographic Analysis and Population Projection System software, which lets me set the birth, death, and migration rates.* I started with the 2016 population because that’s the most recent set of life tables NCHS has released for mortality. Starting in 2018 I apply the current age-specific birth rates.

First, the most basic projection. This is what would happen if birth rates stayed the same as those in 2018 and we completely cut off all immigration (Projection A), or if we had net migration running at the current level of just under +1 million each year, using Census estimates for age and sex of the migrants (Projection B).

projections.xlsx

From the 2016 population of 323 million, if the birth rates by age in 2018 were locked in, the population would peak at 329 million in 2029 and then start to decline, reaching 235 million by 2100. However, if we maintain current immigration levels (by age and sex), the population would keep growing till 2066 before tapering only slightly. (Note this assumes, unrealistically, that the immigrants and their children have the same birth rates as the current population; they have generally been higher.) This the most important bottom line: there is no reason for the U.S. to experience population decline, with even moderate levels of immigration, and assuming no rebound in fertility rates. Immigration rates do not have to increase to maintain the current population indefinitely.

Note I also added the percentage of the population over age 65 on the figure. That number is about 16% now. If we cut off immigration and maintain current birth rates, it would rise to 25% by the end of the century, increasing the need for investment in old age stuff. If we allow current migration to continue, that growth is less and it only reaches 23%. This is going up no matter what.

To show the scale of other changes that we might expect — again, not predictions — I added a few other factors. Here are the same projections, but adding a transition to higher life expectancies by 2080 (using Japan’s current life tables; we can dream). In these scenarios, population decline is later and slower (and not just at older ages, since Japan also has lower child mortality).

projections.xlsx

Under these scenarios, with rising life expectancies, the old population rises more, to between 27% and 29%. Generally experts assume life expectancies will rise more than this, but that’s the assumed direction (now, unbelievably, in doubt).

Finally, I’ve been assuming birth rates will not fall further. If what we’re seeing now is fertility postponement, we wouldn’t expect much more decline. But what if fertility keeps falling? Here is what you get with the assumptions in Projection D, plus total fertility rates falling to 1.6, either by 2030 or 2050. As you can see, in the 1.6 to 1.8 range, the effects on population size aren’t great in this time scale.

projections.xlsx

Conclusion: We are on track for slowing population growth, followed by a plateau or modest decline, with population aging, by the end of the century, and immigration is a bigger question than fertility rates, for both population growth and aging.

Perspective

In a global context where more people want to come here than want to leave (to date), worrying about low birth rates tends to lend itself to myopic, religious, or racist perspectives which I don’t share. I don’t think American culture is superior, whites are in danger of extinction, or God wants us to have more children.

I do not agree with Dowell Myers, who was quoted yesterday as saying, “The birthrate is a barometer of despair.” That even as some people are having fewer children than they want, or delaying childbearing when they would rather not. In the most recent cohort to finish childbearing, 23% gave an “ideal number of children for a family to have” that was greater than the number they had, and that number has trended up, as you can see here:

Stata graph

Is this rising despair? As individuals, people don’t need to have children any more. Ideally, they have as many as they want, when they want, but they are expensive and time consuming and it’s not surprising people end up with fewer than they think “ideal.” Not to be crass about it, but I assume the average person also has fewer boats than they consider ideal.

And how do we know what is the right level of fertility for the population? As Marina Adshade said on Twitter, “Did women actually have a desire for more children in the past? Or did they simply lack the bargaining power and means to avoid births?”

However, to the extent that low birth rates reflect frustrated dreams, or fear and uncertainty, or insufficient support for families with children, of course those are real problems. But then let’s name those problems and address them, rather than trying to change fertility rates or grow the population, which is a policy agenda with a very bad track record.


* I put the DAPPS file package I created on the Open Science Framework, here. If you install DAPPS you can open this and look at the projections output, with graphs and tables and population pyramids.

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The changing household age range, U.S. 1900-2017

One way to understand daily interaction, and intergenerational resource exchange, is just to look at the structure of households. This doesn’t tell you everything that goes on in households, but it gives some strong clues. And we can measure it going back more than a century, thanks to IPUMS.org’s collection of Census microdata.

In 1900, the most common situation for an American was to live in a household where the age difference between the oldest and youngest person was about 38 years. Now the most common situation is an age range of 0 — either living alone, or with someone of the exact same age. And there are a lot more people living in households with only similar-aged adults, with age ranges of less than 10.

In between 1900 and 2017, life expectancy increased, the age at first birth increased, and the tendency to live in multigenerational households fell and then rose again. So the household structure story is complicated, and this is just one perspective.

But it’s one indicator of how life has changed. Line up your household from youngest to oldest, look to your left and look to your right — how far can you see?

household age range

 

Data and Stata code (for all decades 1900-2000, then individual years to 2017) are available on the Open Science Framework, here.

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Family Demography seminar syllabus

Sabbatical over

Syllabuses done

Welcome all students

Come many come one


34864841863_175967af26_k

Shanghai Museum, Summer 2017 (photo PNC, Flickr CC)

Here is my revised syllabus for a graduate seminar in family demography. Comments and suggestions always welcome. This is just the reading list, but the bureaucratic parts are available in the PDF version. A lot of the papers are paywalled, but you can get most by pasting the DOIs into the sci-hub pirate site search box (if it’s not blocked where you are.)

Week 1

Theoretical perspectives in demography

Week 2

Demographic transition

Week 3

Fertility in poor countries

Week 4

Second demographic transition

Week 5

U.S. History

Week 6

Marriage and social class

  • Cherlin, Andrew J. 2014. Labor’s Love Lost: The Rise and Fall of the Working-Class Family in America. New York: Russell Sage Foundation.
  • Cohen, Philip N. 2014. The Family: Diversity, Inequality, and Social Change. New York: W. W. Norton & Company. Chapter 8, “Marriage and cohabitation.”

Week 7

Divorce

Week 8

Transition to adulthood

Week 9

Women and families in Asia and Africa

  • Yeung, Wei-Jun Jean, Sonalde Desai, and Gavin W. Jones. 2018. “Families in Southeast and South Asia.” Annual Review of Sociology 44 (1): 469–95. https://doi.org/10.1146/annurev-soc-073117-041124.
  • Desai, Sonalde, and Lester Andrist. 2010. “Gender Scripts and Age at Marriage in India.” Demography 47 (3): 667–87.
  • Clark, Shelley, Sangeetha Madhavan, Cassandra Cotton, Donatien Beguy, and Caroline Kabiru. 2017. “Who Helps Single Mothers in Nairobi? The Role of Kin Support.” Journal of Marriage and Family 79 (4): 1186–1204. https://doi.org/10.1111/jomf.12404.

Week 10

U.S. economic conditions and family outcomes

Week 11

Policy, race, and nonmarital births

Week 12

More U.S. inequality issues

  • Brady, David, Ryan M. Finnigan, and Sabine Hübgen. 2017. “Rethinking the Risks of Poverty: A Framework for Analyzing Prevalences and Penalties.” American Journal of Sociology 123 (3): 740–86. https://doi.org/10.1086/693678.
  • Western, Bruce, and Christopher Wildeman. 2009. “The Black Family and Mass Incarceration.” Annals of the American Academy of Political and Social Science 621 (1): 221–242.
  • Two selections from Families in an Era of Increasing Inequality (2015) edited by Paul R. Amato, Alan Booth, Susan M. McHale, and Jennifer Van Hook, 3–23. National Symposium on Family Issues 5. Springer International Publishing.
    • McLanahan, Sara, and Wade Jacobsen. “Diverging Destinies Revisited.”
    • Cohen, Philip N. 2015. “Divergent Responses to Family Inequality.”

Week 13

Family structure and child wellbeing

Week 14

Maternal mortality

 Week 15

Immigrant families

  • Menjívar, Cecilia, Leisy J. Abrego, and Leah C. Schmalzbauer. 2016. Immigrant Families. John Wiley & Sons.

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The rise of Jewish boys’ names in the US

Names are cultural as the personal is political for marginalized groups.

I’ve had these numbers sitting around for a while, since I noticed Nazis on Twitter calling me “Shlomo” as an insult, and was just spurred to write them up by a fascinating Twitter thread from someone who goes by Benjamin (בנימן טבלוב). He writes in response to criticism of Jews who change their names from their “real” European names to Hebrew names, specifically Israeli Prime Minister Benjamin Netanyahu, whose father changed the family name from Mileikowsky after they moved from Europe to Palestine in 1920. (Netanyahu is terrible in every way, that’s not the point.)

Benjamin explained that the Jews of northern and eastern Europe historically practiced patronymic naming exclusively, naming children after their fathers, as in: Jacob, son of Isaac, son of Abraham. (The most famous contemporary patronymic society is Iceland, although they sometimes use matronyms now, too.) It was only with the bureaucratization of modern citizenship in eighteenth and nineteenth century Austria, Prussia, Russia, France, and Bavaria, that Jews were forced to take permanent surnames, and these were often not of their choosing, based things like on places, occupations, or even insults. Besides being generally dehumanizing, this system of Jewish surnames also eventually made it easy to round Jews up for the Holocaust (see the Kaplan and Bernays’ The Language of Names, and this paper, for some history). An exception, incidentally, is the use of the priestly honorific terms Cohen and Levy, which were already in place (e.g., Philip, son of Marshall the Cohen) and then became permanent surnames. I assume Israeli politicians aren’t ditching the name Cohen for something more Hebrew sounding.

So when Jews went to Palestine, they often took new Hebrew names; but when they came to America they took more English names, and then gave their kids mainstream American names. The history of coercive naming in Europe makes it easier to see why this might not have been so objectionable to the Jewish immigrants in the early twentieth century. Kaplan and Bernays quote an immigrant to New York who said, “Nothing good ever came to us while we bore them [old names]; possibly we’ll have more luck with the new names.” (My grandmother was born Tzivya (צִבְיָה), which became Cywja when she boarded a ship from Poland in 1921, and then eventually Sylvia.)

Jewish names today

Today it’s probably safe to say most Jewish children in the U.S. don’t have Jewish first names per se (although they sometimes have a Hebrew name they use just for religious occasions). Here I look at the trends for seven Jewish boys’ names I found on various naming websites: Shlomo, Chaim, Eliezer, Mordechai, Moshe, Yosef, and Zev. These were the most popular ones I could think of (feel free to suggest others).

First a little data on Yiddish and Hebrew in America. This is all from the Decennial Census and then, after 2000, the American Community Survey, which asked about “mother tongue” (language spoken at home as a child) from 1910 to 1970 (except 1950), and language spoken at home after that. The Census doesn’t ask about religion.

Yiddish was the language spoken by the big wave of Jewish immigrants in the early twentieth century. Hebrew is the primary official language of Israel, and the religious language of Judaism. This shows the percentage of people in the U.S. who spoke Yiddish or Hebrew from 1910 to 2017.* The peak in 1930 is 1.1 percent, during the immigration boom. The 1970 peak reflects the only year “mother tongue” was asked of non-immigrants as well as immigrants. By 1980 only one-in-500 Americans spoke Yiddish or Hebrew at home.

yh1.JPG

The second thing about Yiddish and Hebrew is children. There are a declining number of old immigrants speaking Yiddish, and no new immigrants speaking Yiddish. So most people speaking Yiddish as their language today are probably the descendants of those immigrants, orthodox Jews participating in ethnic revival or preservation. The same goes for people speaking Hebrew at home, except by now some of these could be immigrants from Israel and their children. (By 2000 Hebrew speakers outnumbered those speaking Yiddish.) Here’s the percentage of Yiddish and Hebrew speakers that were under 18 for the same years.

yh2

It was low in 1930, when they were mostly working-age immigrants, and then in 1960 when their kids were grown. The percentage under age 18 increased after 1960, and now 40 percent of Yiddish speakers are children (which is not the case for Hebrew). And, this is key: the proportion of all U.S. children speaking Yiddish at home has more than doubled since 1980, from 5 to 11 per 10,000. If these numbers are to be believed.

yh3.JPG

Names

The sample numbers here are small, but the ACS sample is also picking up about 150 Yiddish or Hebrew speaking women per year having babies, which implies that population is having about 10,000 babies per year, or about 26 out of every 10,000 babies born in the country.

So, who’s naming their sons Shlomo, Chaim, Eliezer, Mordechai, Moshe, Yosef, and Zev? Now switching to the Social Security names database, I find that these names together accounted for 1,943 boys born in 2017 (that’s 9.9 out of every 10,000 US boys born). What’s interesting is that none of these boys’ names reached the threshold for reporting in the database — five children — until 1942. This is remarkable given that Yiddish was in decline by then. And they’ve all been growing more common since that time. So all those Yiddish immigrants in 1920 weren’t naming their sons Moshe, or at least not legally, but now a growing (though small) proportion of their descendants are.

jbn

I can’t tell if Yiddish or Hebrew speakers are giving their sons these names. But there must be some connection between the rise of these names and the increase in the proportion of children speaking Yiddish at home. It might not be same people teaching their kids Yiddish, but they may be part of the same (highly localized) revival.

I’ve put the Social Security names data, and my SAS code for extracting name trends, on the Open Science Framework here.


* An earlier version had much higher prevalence of Yiddish and Hebrew before 1980 because I was accidentally just showing the percentages among immigrants.

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Fox News took my quotes out of context and added wrong information

Following up on Part 1, discussed here, Parts 2 and 3 of the Fox News series on demography and social change also featured quotes from me. Part 2 used a reasonable quote in a reasonable way, but Part 3 did not.

Part 2 is a good teaching lesson in sky-is-fallingism, a Fox News signature. As they’ve done before, they literally start with a 1950s TV show as if it were historical footage, and then proceed to the chaotic now.

“If Tommy suddenly woke up today, he’d be an aging Baby Boomer, receiving benefits from a Social Security trust fund that is more than 2 trillion dollars in debt. He might be tending to his aches and pains with medical marijuana, now legal in 33 states. He might see his childhood friends are legally married [showing gay male weddings] while almost half the mommies in the U.S. are not.”

Cut to racial minority students in UCLA gear. Etc. The most extreme cut is between the Heritage Foundation person saying, of Democrats, “We’re the party of government, and that way if we have voters attached to government programs they’re going to stick with us,” before, literally, cutting to archival Mao and Stalin footage, with the voice-over:

“That, while the hard lessons of socialism — 70 million dead in China, 20 million dead in the Soviet Union — that happened during Communism, are often neglected in colleges, now focused on social justice curricula.”

Great stuff, good for teaching. Anyway, my quote in the piece is just saying young people nowadays don’t like to be lectured about traditional values. They just frame it like that’s a bad thing. Here it is:

Part 3 is where they misused my quotes, in two places. The episode is about how low fertility leads to immigration, which creates chaos and causes populism. Plenty wrong in here, but I’m just focusing on my beefs. First, on immigration, they say:

“Europe’s accommodation of refugees fleeing ISIS and the civil war in Syria, has proved a bridge too far.”

Philip Cohen: “Immigration poses challenges to the dominant culture. It’s obviously politically fraught.”

Cut to rioting footage. Narrator: “From Greece to Italy, Germany, France, and the Nordic countries, clashes have erupted. Nationalist politicians are forcing a reckoning with multiculturalism.”

According to my own recording of the interview, however, what I said immediate after, “It’s obviously politically fraught,” was this:

“On the other hand, there’s a great pent-up demand for immigration. There are plenty of people who want to come here. The immigrants who come here tend to be the better off, more highly skilled and educated people from the countries that they’re coming from, contrary to some stereotypes, so they end up strengthening the U.S. economy even as they improve their own wellbeing. So if you can get over all the challenges and conflict that sometimes comes along with rapid immigration, what you end up with is an answer to the population [problem].”

Lesson learned. Not surprising they didn’t use my pro-immigration other hand. I should have anticipated that better and made the other hand the only hand in my comment. However, they had invited me to discuss Millennials and marriage, so I wasn’t prepared for immigration.

The piece has distracted tangents into robots in Japan and the one-child policy in China. I also wasn’t prepared for the one-child policy on that day, but I always have a take ready on that. Here’s what I said, according to my recording:

“One thing to know about China is the birthrate had fallen a lot before the one-child policy. So even if you like the idea … [they interrupted to say they had bumped the focus, so I should start my answer again] …One thing that’s important to realize about China is that population growth had already slowed a lot before the one-child policy started, so they really didn’t need the one-child policy to slow down population growth. And it was quite draconian. It went against what most people wanted for their families. The implementation of it was very repressive. It included forced sterilization, and abortion, and very harsh penalties for people who had extra children. So it was really a human rights disaster.”

In the piece, however, they used the part about forced sterilization and the human rights disaster, but didn’t use where I said, “they really didn’t need the one-child policy to slow down population growth” — and replaced it with voice-over that said, “overpopulation compelled the Communist government to force a one-child policy on the populous.” So they took out something true and added something false.

To see how wrong that it, here is the trend in total fertility rate (births per woman) from 1960 to 2016. This shows how much birth rates had come down in China under policies that promoted smaller families along with women’s healthcare, education, and employment, by the time China implemented the one-child policy in 1980:

china-1980-tfr

I put India and Nigeria on the chart to show how successful China already was relative to other large, poor countries with high fertility in the 1960s. There was no demographic justification for the one-child policy, and the fact that it became draconian and repressive is a clue to how out of step it was with the family lives of the Chinese people.

The reason this matters is not particularly important for the Fox News piece, but it’s very important to understand that progress on reducing fertility is better achieved through empowerment and development than through command and repression. Now that we’re seeing countries interested in increasing fertility, this is important historical context. (Here’s a good review article by Wang Feng, Baochang Gu, and Yong Cai [paywalled | bootlegged])

Anyway, regardless of the implications, it just goes against accuracy and honesty to remove true information for false information.

Anyway anyway, here’s Part 3:

 

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Decadally-biased marriage recall in the American Community Survey

Do people forget when they got married?

In demography, there is a well-known phenomenon known as age-heaping, in which people round off their ages, or misremember them, and report them as numbers ending in 0 or 5. We have a measure, known as Whipple’s index, that estimates the extent to which this is occurring in a given dataset. To calculate this you take the number of people between ages 23 and 62 (inclusive), and compare it to five-times the number of those whose ages end in 0 or 5 (25, 30 … 60), so there are five-times as many total years as 0 and 5 years.

If the ratio of 0/5s to the total is less than 105, that’s “highly accurate” by the United Nations standard, a ratio 105 to 110 is “fairly accurate,” and in the range 110 to 125 age data should be considered “approximate.”

I previously showed that the American Community Survey’s (ACS) public use file has a Whipple index of 104, which is not so good for a major government survey in a rich country. The heaping in ACS apparently came from people who didn’t respond to email or mail questionnaires and had to be interviewed by Census Bureau staff by phone or in person. I’m not sure what you can do about that.

What about marriage?

The ACS has a great data on marriage and marital events, which I have used to analyze divorce trends, among other things. Key to the analysis of divorce patterns is the question, “When was this person last married?” (YRMARR) Recorded as a year date, this allows the analyst to take into account the duration of marriage preceding divorce or widowhood, the birth of children, and so on. It’s very important and useful information.

Unfortunately, it may also have an accuracy problem.

I used the ACS public use files made available by IPUMS.org, combining all years 2008-2017, the years they have included the variable YRMARR. The figure shows the number of people reported to have last married in each year from 1936 to 2015. The decadal years are highlighted in black. (The dropoff at the end is because I included surveys earlier than those years.)

year married in 2016.xlsx

Yikes! That looks like some decadal marriage year heaping. Note I didn’t highlight the years ending in 5, because those didn’t seem to be heaped upon.

To describe this phenomenon, I hereby invent the Decadally-Biased Marriage Recall index, or DBMR. This is 10-times the number of people married in years ending in 0, divided by the number of people married in all years (starting with a 6-year and ending with a 5-year). The ratio is multiplied by 100 to make it comparable to the Whipple index.

The DBMR for this figure (years 1936-2015) is 110.8. So there are 1.108-times as many people in those decadal years as you would expect from a continuous year function.

Maybe people really do get married more in decadal years. I was surprised to see a large heap at 2000, which is very recent so you might think there was good recall for those weddings. Maybe people got married that year because of the millennium hoopla. When you end the series at 1995, however, the DBMR is still 110.6. So maybe some people who would have gotten married at the end of 1999 waited till New Years day or something, or rushed to marry on New Year’s Eve 2000, but that’s not the issue.

Maybe this has to do with who is answering the survey. Do you know what year your parents got married? If you answered the survey for your household, and someone else lives with you, you might round off. This is worth pursuing. I restricted the sample to just those who were householders (the person in whose name the home is owned or rented), and still got a DBMR of 110.7. But that might not be the best test.

Another possibility is that people who started living together before they were married — which is most Americans these days — don’t answer YRMARR with their legal marriage date, but some rounded-off cohabitation date. I don’t know how to test that.

Anyway, something to think about.

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Predicted divorce decline rolls on

With the arrival of the 2017 American Community Survey data on IPUMS.org, I have updated my analysis of divorce trends (paper | media reports | data and code).

In the first version of the paper, based on data from 2008 to 2016, I wrote:

Because divorce rates have continued to fall for younger women, and because the risk profile for newly married couples has shifted toward more protective characteristics (such as higher education, older ages, and lower rates of higher-order marriages), it appears certain that – barring unforeseen changes – divorce rates will further decline in the coming years.

I don’t usually make predictions, but this one seemed safe. And now the 2017 data are consistent with what I anticipated: a sharp decline in divorce rates among those under age 45, and continued movement toward a more selective pattern in new marriages.

Here is the overall trend in divorces per 100 married women, 2008-2017, with and without the other variables in my model:

divtrend

With the 2017 data, the divorce rate has now fallen 21% since 2008. To show the annual changes by age, I made this heatmap style table, with shading for divorce rates, rows for years, columns for age, and the column widths proportional to the age distribution (so 15-19 is a sliver, and 50-54 is the widest). The last row shows the sharp drop in divorce rates for women under age 45 in 2017:

2008-2017 divorce marriage.xlsx

To peek into the future a little more, I also made a divorce protective-factor scale, which looks just at newlywed couples in each year, and gives them one point for each spouse that is age 30 or more, White or Hispanic, has BA or higher education, is in a first marriage, and a point if the woman has no own children in the home at the time of the survey. So it ranges from 0 to 9. (I’m not saying these factors have equal importance, but they are all associated with lower odds of divorce.) The gist of it is new marriages increasingly have characteristics conducive to low divorce rates. In 2008 41% of couples had a score of 5 or more, and in 2017 it’s 50%.

mdpf

So divorce rates will probably continue to fall for a while.

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