Tag Archives: demography

The Coming Divorce Decline, Socius edition

“The Coming Divorce Decline, ” which I first posted a year ago, has now been published by the journal Socius.  Three thousand people have downloaded it from SocArXiv, I presented it at the Population Association, and it’s been widely reported (media reports), but now it’s also “peer reviewed.” Since Socius is open access, I posted their PDF on SocArXiv, and now that version appears first at the same DOI or web address (paper), while the former editions are also available.

Improvement: Last time I posted about it here I had a crude measure of divorce risk with one point each for various risk factors. For the new version I fixed it up, using a divorce prediction model for people married less than 10 years in 2017 to generate a set of divorce probabilities that I apply to the newly-wed women from 2008 to 2017:

…the coefficients from this model are applied to newly married women from 2008 to 2017 to generate a predicted divorce probability based on 2017 effects. The analysis asks what proportion of the newly married women would divorce in each of their first 10 years of marriage if 2017 divorce propensities prevailed and their characteristics did not change.

The result looks like this, showing the annual probability falling from almost 2.7% to less than 2.4%:

divprobnewlyweds

The fact that this predicted probability is falling is the (now improved) basis for my prediction that divorce rates will continue to decline in the coming years: the people marrying now have fewer risk factors. (The data and code for all this is up, too).


Prediction aside: The short description of study preregistration is “specifying your plan in advance, before you gather data.” You do this with a time-stamped report so readers know you’re not rejiggering the results after you collect data to make it look like you were right all along. This doesn’t always make sense with secondary data because the data is already collected before we get there. However, in this case I was making predictions about future data not yet released. So the first version of this paper, posted last September and preserved with a time stamp on SocArXiv, is like a preregistration of the later versions, effectively predicting I would find a decline in subsequent years if I used the same models — which I did. People who use data that is released on a regular schedule, like ACS, CPS, or GSS, might consider doing this in the future.


Rejection addendumSociological Science rejected this — as they do, in about 30 days, with very brief reviews — and based on their misunderstandings I made some clarifications and explained the limitations before sending it to Socius. Since the paper was publicly available the whole time this didn’t slow down the progress of science, and then I improved it, so I’m happy about it.

Just in case you’re worried that this rejections means the paper might be wrong, I’m sharing their reviews here, as summarized by the editor. If you read the current version you’ll see how I clarified these points.

* While the analyses are generally sensible, both Consulting Editors point out the paper’s modest contribution to the literature relative to Kennedy and Ruggles (2014) and Hemez (2017). The paper cites both of these papers but does not make clear how the paper adds to our understanding derived from those papers. If the relatively modest extension in the time frame in this paper is sociologically consequential, the paper does not make the case clearly.

* There is more novelty in the paper’s estimates of the annual divorce probability for newly-married women (shown in Table 3 and Figure 3), based on estimating a divorce model for the most recent survey year, and then applying the coefficients from that model to prior years. This procedure was somewhat difficult for the readers to follow, but issues were raised, most notably the question of the sensitivity of the results to the adjustments made. As one CE noted, “Excluding those in the first year of marriage is problematic as newlyweds have a high rate of divorce. Also, why just married in the last 10 years? Consider whether married for the first time vs remarried matters. Also, investigate the merits of an age restriction given the aging of the population Kennedy and Ruggles point to.”

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Against the generations, with video

I had the opportunity to make a presentation at the National Academies to the “Committee on the Consideration of Generational Issues in Workforce Management and Employment Practices.” If you’ve followed my posts about the “generation” terms and their use in the public sphere you understand how happy this made me.

The committee is considering a wide array of issues related to the changing workforce — under a contract from the Army — and I used the time to address the uses and misuses of cohort concepts and analysis in analyzing social change.

In the introduction, I said generational labels, e.g., “Millennials”:

encourage what’s bad about social science. It drives people toward broad generalizations, stereotyping, click bait, character judgment, and echo chamber thinking. … When we give them names and characters we start imposing qualities onto populations with absolutely no basis, or worse, on the basis of stereotyping, and then it becomes just a snowball of clickbait confirmation bias. … And no one’s really assessing whether these categories are doing us any good, but everyone’s getting a lot of clicks.

The slides I used are here in PDF. The whole presentation was captured on video, including the Q&A.

From my answer to the last question:

Cohort analysis is really important. And the life course perspective, especially on demographic things, has been very important. And as we look at changes over time in the society and the culture, things like how many times you change jobs, did you have health insurance at a certain point in your life, how crowded were your schools, what was the racial composition of your neighborhood or school when you were younger — we want to think about the shadow of these events across people’s lives and at a cultural level, not just an individual level. So it absolutely is important. … That’s a powerful way of thinking and a good opportunity to apply social science and learn from it. So I don’t want to discourage cohort thinking at all. I just want to improve it… Nothing I said should be taken to be critical of the idea of using cohorts and life course analysis in general at all.

You know, this is not my most important work. We have bigger problems in society. But understanding demographic change, how it relates to inequality, and communicating that in ways that allow us to make smarter decisions about it is my most important work. That’s why I consider this to be part of it.

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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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