Fertility trends explained, 2017 edition

Not really, but some thoughts and a bunch of figures on the 2017 fertility situation.

There was a big drop in the U.S. fertility rate in 2017. As measured by the total fertility rate (TFR), which is a projection of lifetime births for the average woman based on one year’s data, the drop was 3.1%, from 1.82 projected births per woman to 1.76. (See this measure explained, and learn how to calculate it yourself, in my blockbuster video, “Total Fertility Rate.”) To put that change in perspective, here is the trend in TFR back to 1940, followed by a plot of the annual changes since 1971:



That drop in 2017 is the biggest since the last recession started. In fact, we have seen no drop that big that’s not associated with a time of national economic distress, at least since the Baby Boom. In 2010, I noted that the drop in fertility at that time preceded the official start of the recession and the big unemployment spike. There is now some more systematic evidence (pointed out by Karen Benjamin Guzzo) that fertility falls before economic indicators turn down. Which makes this New York Times headline a little funny, “US Births Hit a 30-Year Low, Despite Good Economy.” This is a pretty solid warning sign, although not definitive, of an economic downturn coming in the next year or so. (On the other hand, maybe it’s a Trump effect, as people are just freaking out and not thinking positively about the future; something to think about.)

Whatever the role of immediate economic conditions, the long-term trend is toward later births, which is generally going to mean fewer births — both because people who want later births tend to want fewer births, and because some people run out of time if they start late. And that is not wholly separable from economic factors, of course. People (especially women) delay childbearing to improve their economic situation, as they improve their economic situation when they delay births (if they have the right suite of economic opportunities). To show this trend, I’ve been updating this figure for a few years (you’ll find it, and a description, in my book Enduring Bonds).

change in birthrates by age 1989-2016.xlsx

The real reason I made this figure was to highlight the interconnected nature of teen births. Birth rates for teens have fallen dramatically, but it’s been along with drops among younger women generally, and increases among older women — it’s about delaying births overall. Note, however, that 2017 is the first time since the depths of the last recession that birth rates fell for all age groups except women over age 40.

So, sell stock now. But it is hard to know for sure what’s a local temporal reaction and what’s just the way things are going nowadays. For that it’s useful to compare the U.S. to other countries. The next figure shows the U.S. and 15 other hand-picked countries, from World Bank data. Rising fertility in the decade before the last recession wasn’t so unusual. We are a little like Spain and France in this figure, who had rising fertility then and falling now. But Germany and Japan are still rising, at least through 2016. All this is at below-replacement levels (about 2.0), meaning eventually these rates lead to population decline, in the absence of immigration. The figure really shows the amazing fertility transformation of the last half century, especially in giant countries like China, India, and Brazil. Who would have thought we’d live to see Brazil have lower fertility rates than the U.S.? It’s been that way for more than a decade (click to enlarge).

country fertilitiy trends.xlsx

Anyway, it’s my position that our below-replacement fertility levels are themselves nothing to worry about at present. There are still lots of people who want to move here (or, there were before Trump). And we can live with low fertility for a long time before the population starts to decline in a meaningful way. Eventually it will be a good idea to stop perpetual population growth anyway, so we may as well start working on it. This is better than trying to shape domestic policy to increase birth rates.

That said, there is an argument that Americans are having fewer children than they want to because of our stone age work-family policies, especially poor family leave support and the high costs of good childcare. I’m sure that’s happening to some degree, but it’s still the case that more privileged people, who should be able to overcome those things more readily — people with college degrees and Whites — have lower fertility rates than people who are getting squeezed more. People who assume their kids are going to college are naturally concerned with rising higher education costs, both their own loan payments and their kids’ future payments. So it’s a mixed bag story. Here are the predictors of childbearing for women ages 15-44 in the 2016 American Community Survey. These are the probabilities of having had a birth in the previous 12 months, estimated (with logistic regression) at the mean of all the variables shown.*

birth model simple 2016.xlsx

Interesting that there’s only a small foreign-born fertility edge in this multivariate model. In the unadjusted data, 7.4% of foreign-born versus 6.0% of U.S.-born women had a baby, but that’s mostly accounted for by their age, education, and race/ethnicity.

To summarize: 2017 was a big year for fertility decline (at all but the highest ages), the economy is probably about to tank, and the U.S. fertility rate is still relatively high for our income level, especially for racial-ethnic minorities.

Happy to have your thoughts in the comments. For more, check the fertility tag.

* Here’s the Stata code for the regression analysis. It’s just some simple recodes of the ACS data from IPUMS.org. Start with a file of women ages 15-44, with the variables you see here, and then do this to it:

recode educd (0/61=1) (62/64=2) (65/90=3) (101/116=4), gen(edcat)
label define edlbl 1 "Less than high school"
label define edlbl 2 "High school graduate", add
label define edlbl 3 "Some college", add
label define edlbl 4 "BA or higher", add
label values edcat edlbl
gen raceth=race
replace raceth=4 if race==5 | race==6 /* now 4 is all API */
replace raceth=5 if hispan>0
drop if race>5
label define raceth_lbl 1 "White"
label define raceth_lbl 2 "Black", add
label define raceth_lbl 3 "AIAN", add
label define raceth_lbl 4 "API", add
label define raceth_lbl 5 "Hispanic", add
label values raceth raceth_lbl
egen agecat=cut(age), at(15(5)50)
gen forborn=citizen!=0
gen birth=fertyr==2
logit birth i.agecat i.raceth i.forborn i.edcat i.marst [weight=perwt]
margins i.agecat i.raceth i.forborn i.edcat i.marst

14 thoughts on “Fertility trends explained, 2017 edition

  1. “That said, there is an argument that Americans are having fewer children than they want to because of our stone age work-family policies, especially poor family leave support and the high costs of good childcare.”

    That argument runs into real headwind when comparing the US TFR vs. European countries, all of which have very generous welfare benefits of all kinds, and also, virtually without exception (France might be one) also have lower TFRs.


  2. What effect does housing have on fertility choice? I am seeing substantial anecdotal evidence that worsening affordability and corresponding lack of supply of a certain housing typology (ground oriented, multi-bedroom, private yard) is leading to deferred fertility. The denser urban markets are seeing widespread school closures as family housing forms are upsized to non-family friendly designs or are simply not being built at all.


  3. Fertility decline may be beneficial in the short term — but there are almost no cases of fertility returning to replacement level after a long term pattern of low fertility is established. I’m not sure this is a trend to be seriously complacent about as most of us seem to be. The argument that children endanger our climate is partly true but it has more to do with the western way of life than the presence of another person. We all know the statistics — north americans are about 8% of the world’s population but generate 50% of the planet’s garbage and consume more than 35% of it’s GNP. A more fruitful discussion it seems to me would be how to have somewhat larger families but not expect or demand the kind of lifestyle we assume should be normal. There are many good things about smaller populations but having more than a third of it being over 65 may not be sustainable in the long run and should we not be considering the long run? Once the baby boomers (my generation) start seriously dying off the increasingly diminishing pool of families or just people in general will not be experienced as an unqualified good. I don’t think gov’t policies by themselves will necessarily change anything. Singapore, Russia and Japan have all had huge policy initiatives to poke fertility. But this is mostly, I think, cultural. I taught for 20 years in university and saw in that time girls graduating in increasing numbers, having quite a bit more professional success and a lot lot less personal ‘success’ in that they had diminishing chances for having a marriage or family.


  4. Clarification question. In your last figure (Conditional Probability of Having a Birth) your x-axis label says “Probability of having a birth, at the mean of other variables.” In your Stata syntax for the margins command, there is no atmeans option declared. Are you measuring the probabilities using

    margins i.agecat i.raceth i.forborn i.edcat i.marst, atmeans

    to calculate Predicted Probabilities at the Means as per your graph, or are you using

    margins i.agecat i.raceth i.forborn i.edcat i.marst

    from your example syntax and calculating the Average Adjusted Predicted Probability which uses the given values except for the variable of interest? I’m guessing results won’t change dramatically, but just wanted to clarify.


    1. I calculated it using the code shown. I think I did some tests once and found the same results with atmeans, so I used that term to describe them. I guess it’s the case with some models.


  5. That argument runs into real headwind when comparing the US TFR vs. European countries, all of which have very generous welfare benefits of all kinds, and also, virtually without exception (France might be one) also have lower TFRs.


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