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:

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.

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).

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).

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.

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:

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.

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* 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.

Demographic Intelligence, low bar edition

U.S. marriage rates are falling generally, so that’s the real news. And it’s important. In fact, one classic projection has the rate hitting zero at 2042. But the news shenanigans are in the prediction business.

I first wrote here about Demographic Intelligence, a profit-making venture founded by Brad Wilcox (full file). They prey on companies’ ignorance about demography and the news media’s desire to stay ahead of the story, making ridiculous claims like “99% accuracy” in their forecasts. Here’s an update.

In a Washington Post Wonkblog entry meaninglessly titled, “Why parents should stop hoping their kids will get married,” we read:

“Millennials are such a big generation, we’re going to have more people of prime marriage age in the next five years than we’ve had at any time in U.S. history. For that alone, we’d expect an uptick in marriage rates,” said Sam Sturgeon, president of Demographic Intelligence.

Setting aside the knowledge-sucking obsession with generational marketing terms, let’s just hold the president of a company with “demographic” in the title to a slightly-higher-than-complete-nonsense standard of demographic intelligence. The median age at marriage is now 28 (combining men and women). At that age there were 4.3 million people in 2013. That is actually the highest number of people ever at the median age at marriage. For example, in 1900, when the median age at marriage was 24, there were only 1.5 million people that age. Wow!

However, intelligent demographer Sturgeon said “for that alone, we’d expect an uptick in marriage rates.” And marriage rates are based on population size. that 4.3 million people at age 28 in 2013 was only 1.35% of the population, while the 1.5 million people at age 24 in 1900 was 1.96% of the population. In fact, the pattern is the opposite of what Sturgeon said: we have never had fewer people — proportionately — in the prime marrying age. Double wow!

Here is the population distribution by age from 1900 to 2013, from the IPUMS.org online table maker (try it, it’s easy!). The color coding helpfully shows where the number is above average (red) versus below average (blue). I’ve highlighted the five-year age interval that contains the median marriage age for each decade:

That the marriage rate is falling — Sturgeon’s expert prediction (see below) is that it will reach an all-time low in 2016 (as it has in 16 of the last 33 years) — is in large part driven by this age composition trend.

How accurate is that forecast?

Demographic Intelligence boasts “99% accuracy” in its wedding forecasts. And these forecasts, they say, are very useful:

This unique forecast is especially valuable as the federal marriage statistics are usually released 12 to 24 months after the date to which they apply, making official data of limited usefulness to the wedding industry. Our forecast is available 24 months before weddings happen, thereby offering a tremendous value to companies that focus on weddings and ancillary businesses.

Now, I’m all in favor of wasting the wedding industry’s money, but I don’t like deceiving the public. So I have to tell you: for every year from 2001 to 2012, if you had simply used last year’s marriage rate to predict this year’s, you would have averaged 98.3% accuracy. That is the deer-in-headlights method of forecasting. In fact, the deer-in-the-headlights forecast for 2012 — that is, assuming no change from 2011 — yields an astonishing accuracy of 99.87% (see below). Not bad! I’ll sell that to you for just 98% of what Demographic Intelligence is charging (except you’re already paying for my services, so you’re welcome).

Of course, demographers like projections, and I’m no exception. It is frustrating that official marriage statistics lag “real time” so much more than other important statistics, such as the unemployment rate or the number of named storms per season. That’s why in 2013 I announced a marriage forecast contest to predict the 2012 marriage rate, and provided some trends in key variables for you to experiment with (in a spreadsheet here): Google searches for wedding invitations, bridal showers, and wedding gifts; the unemployment rate, the Index of Consumer Sentiment, and the number of women ages 20-39:

There was so little interest in my contest (go figure), that I never got around to updating the results. So here goes. We now know from official statistics that there were 2,131,000 marriages in 2012, which, for a population of 313,914,040, yields a marriage-per-1000 rate of 6.788, down from 6.797 in 2011. Using different combinations of these variables, I generated projections using linear regressions. As I noted, the no-change performed very well, at 99.87% accuracy. But the winning model was actually the one that used the Google search trends only, which predicted 2,133,647 weddings, an astonishing 99.88% accurate. If Google is not using their data to get filthy rich — oh wait.

Anyway, in this exercise I’m just predicting the next year in the series — it gets a little trickier if you want to go four years out. And demographic projections are a serious science. But this prediction business is just wasting money and confusing people.