Tag Archives: recession

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:

tfr4017

tfrchanges

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

6 Comments

Filed under In the news

Update: Adjusted divorce risk, 2008-2014

Quick update to yesterday’s post, which showed this declining refined divorce rate for the years 2008-2014:

On Twitter Kelly Raley suggested this could have to do with increasing education levels among married people. As I’ve reported using these data before, there is a much lower divorce risk for people with BA degrees or higher education.

Yesterday I quickly (but I hope accurately) replicated my basic model from that previous paper, so now I can show the trend as a marginal effect of year holding constant marital duration (from year of marriage), age, education, race/ethnicity, and nativity.*

2014 update

This shows that there has been a decrease in the adjusted odds of divorce from 2008 to 2014. You could interpret this as a continuous decline with a major detour caused by the recession, but that case is weaker than it was yesterday, looking at just the unadjusted trend.

If it turns out that increase in 2010-2012 is related to the recession, it’s not so different from my original view — a recession drop followed by rebound, it’s just that the drop is less and the rebound is more, and took longer, than I thought.  In any event, this should undermine any effort to resuscitate the old idea that the recession caused a decline in divorce by causing families to pull together during troubled times.

This does not contradict the results from Kennedy and Ruggles that show age-adjusted divorce rising between 1980 and 2008, since I’m not trying to compare these ACS trends with the older data sources. For time beyond 2008, they wrote in that paper:

If current trends continue, overall age-standardized divorce rates could level off or even decline over the next few decades. We argue that the leveling of divorce among persons born since 1980 probably reflects the increasing selectivity of marriage.

That would fit the idea of a long-term decline with a stress-induced recession bounce (with real-estate delay).

Alternative interpretations welcome.

* This takes a really long time for Stata to compute on my sad little public-university computer because it’s a non-linear model with 4.8 million cases – so please don’t ask for a lot of different iterations of this figure. I don’t have my code and output cleaned up for sharing, but if you ask me I’ll happily send it to you.

4 Comments

Filed under In the news

Divorce rate plunge continues

When I analyzed divorce and the recession in this paper, I only had data from 2008 to 2011. Using a model based on the predictors of marriage in 2008, I thought there had been a drop in divorces associated with the recession in 2009, followed by a rebound back to the “expected level” by 2011. So, the recession reduced divorces, perhaps temporarily.

That was looking iffy when the 2013 data showed a big drop in the divorce rate, as I reported last year. With new data now out from the 2014 American Community Survey, that story is seeming less and less adequate. With another deep drop in 2014, now it looks like divorce rates are on a downward slide, but in the years after the recession there was a bump up — so maybe recession-related divorces (e.g., those related to job loss or housing market stressors) took a couple years to materialize, producing a lull in the ongoing plunge. Who knows.

So, here is the latest update, showing the refined divorce rate — that is, the number of divorces in each year per 1,000 married people in that year.*

divorce rates.xlsx

Lots to figure out here. (As for why men and women have different divorce rates in the ACS, I still haven’t been able to figure that out; these are self-reported divorces, so there’s no rule that they have to match up [and same-sex divorces aren’t it, I think.])

For the whole series of posts, follow the divorce tag.

* I calculate this using the married population from table B12001, and divorces in the past year from table B12503, in the American Factfinder version of the ACS data.

2 Comments

Filed under In the news

Fewer births and divorces, more violence: how the recession affected the American family

I wrote this for The Conversation. Read the original here.

Observers may be quick to declare social trends “good” or “bad” for families, but such conclusions are rarely justified. What’s good for one family – or group of families – may be bad for another. And within families, interests do not always align. Divorce is “bad” for a family in the sense of breaking it apart, but it may be beneficial, or even essential, for one or both partners or their children.

This kind of ambiguity makes it difficult to assess what kind of impact the recent recession and its aftermath had on families. But for researchers, at least, it offers a lot of job security – so many questions, so much going on. In any case, here’s where we stand so far.

The effect of the Great Recession on family trends in the United States has been dramatic with regard to birth rates and divorce, and has been strongly suggestive of family violence, but less clear for marriage and cohabitation.

Marriage rates declined, and cohabitation rates increased, but these trends were already underway, and the recession didn’t alter them much. When trends don’t change direction it’s difficult to identify an effect of a shock this broad. However, with both birth rates and divorce, clear patterns emerged.

Birth rates: a sharp drop
The most dramatic impact was on birth rates, which dropped precipitously, especially for young women, as a result of the economic crisis. How do we know? First, the timing of the fertility decline is very suggestive. After increasing steadily from the beginning of 2002 until late 2007, birth rates dropped sharply. (The decline has since slowed for some groups after 2010, but the US still saw record-low birth rates for teenagers and women ages 20-24 as late as 2012.)

Second, the decline in fertility was steeper in states with greater increases in unemployment. Although we don’t have the data to determine which couple did or did not have a child in response to economic changes, this pattern supports the idea that financial concerns convinced some people to not have a child.

That interpretation is supported by the third trend: the fertility drop was more pronounced among younger women – and there was no drop at all among women over 40. That may mean the fertility decline represents births postponed by families that intend to have children later – an option older women may not have – which fits previous research on economic shocks.

It seems likely that people who are on the fence about having a baby can be swayed by perceived financial hardship or uncertainty. From research on 27 European countries, we know that people with troubled family financial situations are more likely to say they are unsure whether they will meet their stated childbearing goals – that is, economic uncertainty doesn’t change their familial aims but may increase uncertainty in whether they will be met.

However, some births delayed inevitably become births foregone. Based on the effect of unemployment on birth rates in earlier periods, it appears a substantial number of young women who postponed births will end up never having children. By one estimate, women who were in their early 20s during the Great Recession are projected to have some 400,000 fewer lifetime births and an additional 1.5% of them will never have a birth.

Divorce rates: a counter-intuitive reaction
In the case of divorce, the pattern is counter-intuitive. Although economic hardship and insecurity adds stress to relationships and increases the risk of divorce, the overall divorce rate usually drops when unemployment rates rise.

Researchers believe that, like births, people postpone divorces during economic crises because of the costs of divorcing – not just legal fees, but also housing transitions (which were especially difficult in the Great Recession) and employment disruptions.

My own research found that there was a sharp drop in the divorce rate in 2009 that can reasonably be attributed to the recession. But, as we suspect will be the case with births, there appears to have been a divorce-rate rebound in the years that followed.
Domestic violence: a spike along with joblessness
Family violence has become much less common since the 1990s. The reasons are not entirely clear, but they certainly include the overall drop in violent crime, improved response from social service and non-governmental organizations, and improvements in women’s relative economic status. However, when the recession hit there was a spike in intimate-partner violence, coinciding with the sharp rise in men’s unemployment rates (I show the trends here).

As with the other trends, it’s hard to make a case based on timing alone, but the evidence is fairly strong that the economic shock increased family stress and violence. For example, one study showed that mothers were more likely to report spanking their children in the months when consumer confidence fell. Another study found a jump in abusive head trauma cases during the recession in several regions. And there have been many anecdotal and journalist accounts of increases in family violence, emerging as early as 2009. Are these direct results of the economic stress or mere correlation? It’s hard to say for sure.

The ultimate impact of these trends on American families will likely take years to emerge. The recession may have affected the pattern of marriage in ways we don’t yet understand – how couples selected each other, who got married and who didn’t – and may create measurable group of marriages that are marked for future effects as yet unforeseen. Like the young adults who entered the labor market during the period of high unemployment and whose career trajectories will be forever altered unfavorably, how these families bear the scars cannot be predicted. Time will tell.

5 Comments

Filed under Research reports

What a recovery looks like (with population growth by age)

If you don’t account for population growth, I don’t get what you’re saying with these employment numbers. I’ll show a simple example, but first a little rundown on Friday’s jobs report.

Here is how CNN Money played the jobs report:

cnn-jobs

What does it mean, this loss and gain of jobs, returning finally to where we started? Four paragraphs under that happy headline, CNN did points out:

Given population growth over the last four years, the economy still needs more jobs to truly return to a healthy place. How many more? A whopping 7 million, calculates Heidi Shierholz, an economist with the Economic Policy Institute.

So what does “Finally!” mean? The Wall Street Journal ran the headline, “Jobs Return to Peak, but Quality Lags.” On 538 it was, “Women returned to prerecession levels of employment in 2013. Men remain hundreds of thousands of jobs in the hole:”

538-jobs

The Center on Budget and Policy Priorities showed how much better the previous recoveries were:

cbpp-jobs

That’s a good comparison. And CBPP mentioned population growth, too:

…payroll employment has finally topped its level at the start of the recession. Still, with essentially no net job growth since December 2007 but a growing working-age population, many more people today want to work but don’t have a job.

It’s not that no one mentions population growth, it’s that they still lead with the “top line” number. And they all have that horizontal line at the raw number of jobs when the recession started as the benchmark. I don’t know why.

Maybe in some crazy economics world the absolute number of jobs is what really matters for evaluating a recovery, and that explains the fixation on that horizontal line. From a social perspective what matters is the proportion of people with jobs. I could see the logic if you had a finite number of employers that never change, where you could literally count up the jobs at two points in time, and see who added and who subtracted from their payrolls (this is why retail chains report “same-store” trends, so the statistics aren’t confounded by the changing number of stores). But we have zillions of employers, constantly changing and moving around — largely in response to population changes. So that static image seems pointless.

In perspective

So here are some charts to put the recession and recovery in slightly better perspective. These all use the Bureau of Labor Statistics’ Current Population Survey from March 2003 to March 2013 (from IPUMS), the household survey used to track the labor force. I use ages 15 and older, and combine people in school (up to age 24) with those employed (not how most people do it, but a lot of people went to school, or stayed in school, because of the bad job market, and it doesn’t make sense to count them as not simply not employed). The survey excludes people in institutions, like prisons, and on-base military personnel.

To show the basic issue, here are the changes in the non-institutionalized population, age 15+, along with the number of them employed or in school — showing absolute changes relative to 2008, the peak employment year.

popjobs1

The 15+ population increased almost 12 million from 2008 to 2013. People employed or in school was not yet back to 2008 levels in March 2013. So a basic population adjustment is the least you can ask for (and we get that from the BLS with the employment-population ratio, which as of May was up less than one percent in the last 3.5 years, but it’s not the headline number).

What about age shifts? You don’t expect extreme age composition changes in 5 years, but there are different employment trends at different ages, so those affect how many employed people we are short. Here are the trends in work/school, by age and sex:

popjobs2

This makes it look like the 30-49s that are getting crushed. The 50+ community’s gains, however,are deceptive — their population is increasing. In fact, the population of people 30-49 declined 5% during this decade, while the population 50+ increased almost 30%. The younger people have increased their schooling rates, but their population has also grown. If you look at the employment/school rates, you see that among men, it is the younger groups that have done worst:

popjobs3

Women clearly are doing better (partly because in the 20-29 range they’re going to school more). It is amazing that employment rates didn’t fall at all over age 60. This could be because the population increase in that group is all in Baby Boomers just hitting their sixties, but I reckon it’s also people delaying retirement compensating for unemployment.

Now that we have age-specific work/school rates, and population changes, we can easily calculate how many people in each age group would have to be in work/school to get to the number implied by applying the peak-year 2008 rates to the population in each year. Sorry this one is so ugly: I made the last bar for each group pink to show the bottom line, where each group stands in 2013 relative to 2008:

popjobs4

Worst off are the 20-something men, down more than a million worker/students in 2013. Interestingly, women are only better off in the 20-something and 50+ ranges.

Finally, if you sum these figures you get the total, age-adjusted losses, by sex since 2008, as of March 2013:

popjobs5

And that’s your bottom line. The job/school losses stood at 3.3 million for men and 2.4 million for women as of March 2013.*

Really, there are no huge surprises here. In fact, the total population change is not a bad rough adjustment, especially for the short term. But there are some interesting nuances here. And with all the data and computers we have these days, let’s adjust for age and sex.

*I don’t say that’s how many “jobs” we need, because I don’t think “jobs” exist — are created, destroyed, shipped overseas, etc. I think there are employed people, people getting jobs, losing jobs, etc. I don’t see how a “job” exists absent a worker in it (and no, a listing is not a job until they fill it). So we don’t need to “create jobs” after a recession, what we need to do is “hire people.” Pet peeve.

6 Comments

Filed under Uncategorized

Silver linings divorce trend

In yesterday’s LA Times story on my divorce paper, reporter Emily Alpert Reyes and her editors focused on the rebound, headlining it, “Divorces rise as economy recovers, study finds.” I had been focused on whether the drop from 2008 to 2009 could really be attributed to the recession. Their decision made good journalistic as well as analytical sense. (The story was re-written by the websites Daily Mail, PBS Newshour, and Huffington Post.)

So what does the increase say about the “silver linings” interpretation of the divorce trend? That was the idea, pitched by Brad Wilcox, that the drop he observed in 2008 from 2007 (using vital statistics data) reflected the fact that “many couples appear to be developing a new appreciation for the economic and social support that marriage can provide in tough times.” There was, and is, no evidence for this that I am aware of.

I think that the rebound in divorce undermines the silver linings theory. However, I can’t swear the theory is wrong. It hasn’t been tested.

But when I was Googling for stories on this yesterday I found this 2009 CBS news report, which accidentally illustrates the problem with silver linings. The story was called “Recession Bright Spot? Divorce Rate Drops.” It featured the Levines, in which the husband lost his job, and the marriage suddenly was in trouble (like a block building suddenly collapsing):

cbs-divorceThen, the couple pulls together, and it looks like they’re going to make it: “If they can get through this, they can get through just about anything.”

The story was a Wilcox plant, featuring him saying, “What we’re seeing is some people are postponing divorce because home values have dropped. For others, the recession has led to a new sense of togetherness.” (In my paper, incidentally, divorce was more common in states with higher foreclosure rates.)

And the reporter noted, as evidence, “There were almost 20,000 fewer divorces in 2008 than 2007.” As I noted at the time, divorce fell at least that much in most years, so that’s meaningless manipulation of reporters’ demographic ignorance by Wilcox. Anyway, that’s not the point. The point is, this couple was doing fine before the recession! So the recession caused him to lose his job, and then their marriage was in trouble, and then they pulled through. So how, exactly, was the recession reducing divorce?

And yet my analysis shows the recession probably did reduce divorce in the aggregate (just not in their case). My suspicion remains that the recession increased stress and conflict within marriages, like CBS’s couple. It probably raised the Levines’ odds of divorce, even if not quite up to 1.0. There is just a lot of evidence at the individual level that job loss increases the odds of divorce (here are three studies). Lots of people — and relationships — had to have been made miserable by the recession.

If that is true, then was the drop in divorce rates good or bad? Was it a silver lining? You have to think about the continuum of marriages — from happy to sad — and who is affected. People who are bouncing around between kinda happy and kinda sad aren’t likely considering the cost of a lawyer yet. Not like those that have hit bottom. But if the cost of divorce — legal fees, real estate, relocation, or whatever — actually delays or forestalls some divorces, it’s probably the ones that are closest to actually occurring for which the outcome changes. That is, the almost-most miserable marriages.

If the recession made more people miserable, and yet fewer got divorced, divorce was more selective. Think of grant funding: when times are tight, more people apply but fewer are funded, so the ones that do are the best of the best (ideally). And the number of good ones not funded goes up. With marriages in a recession, more are miserable, yet the bar for divorcing is raised (or lowered) by the costs relative to income. So there are more miserable marriages not ending in divorce. Obviously, God thinks this is good, because he has no patience for our petty divorce excuses (which explains Wilcox’s interpretation).

One obvious possibility is that family violence increases when more miserable marriages produce fewer divorces. There was a spike in intimate partner violence in 2008 and 2009, the years men’s unemployment rates jumped. (We will address this and related issues at an American Sociological Association special session this year.)

It is very common, yet wholly unjustified, to always assume falling divorce rates are good. As I argued before: We simply do not know what is the best level of divorce to maximize the benefits of good marriage while mitigating the harms caused by bad marriage.

6 Comments

Filed under In the news

Divorce drop and rebound: paper in the news

My paper on divorce and the recession has been accepted by the journal Population Research and Policy Review, and Emily Alpert Reyes wrote it up for the L.A. Times today. (The paper is now online.)

latimes-divorce

Married couples promise to stick together for better or worse. But as the economy started to rebound, so did the divorce rate.

Divorces plunged when the recession struck and slowly started to rise as the recovery began, according to a study to be published in Population Research and Policy Review.

From 2009 to 2011, about 150,000 fewer divorces occurred than would otherwise have been expected, University of Maryland sociologist Philip N. Cohen estimated. Across the country, the divorce rate among married women dropped from 2.09% to 1.95% from 2008 to 2009, then crept back up to 1.98% in both 2010 and 2011.

To reach the figure of 150,000 fewer divorces, I estimated a model of divorce odds based on 2008 data (the first year the American Community Survey asked about divorce events). Based on age, education, marital duration, number of times married, race/ethnicity and nativity, I predicted how many divorces there would have been in the subsequent years if only the population composition changed. Then I compared that predicted trend with what the survey actually observed. This comparison showed about 150,000 fewer than expected over the years 2009-2011:

divorce-fig2

Notice that the divorce rate was expected to decline based only on changes in the population, such as increasing education and age. That means you can’t simply attribute any drop in divorce to the recession — the question is whether the pace of decline changed.

Further, the interpretation that this pattern was driven by the recession is tempered by my analysis of state variations, which showed that states’ unemployment rates were not statistically associated with the odds of divorce when individual factors were controlled. Foreclosure rates were associated with higher divorce rates, but this didn’t hold up with state fixed effects.

So I’m cautious about the attributing the trend to the recession. Unfortunately, this all happened after only one year of ACS divorce data collection, which introduced a totally different method of measuring divorce rates, which is basically not comparable to the divorce statistics compiled by the National Center for Health Statistics from state-reported divorce decrees.

Finally, in a supplemental analysis, I tested whether unemployment and foreclosures were associated with divorce odds differently according to education level. This showed unemployment increasing the education gap in divorce, and foreclosures decreasing it:

Microsoft Word - Divorce PRPR-revision-revision.docx

Because I didn’t have data on the individuals’ unemployment or foreclosure experience, I didn’t read too much into it, but left it in the paper to spur further research.

Aside: This took me a few years.

It started when I felt compelled to debunk Brad Wilcox’s fatuous and deliberately misleading interpretation of divorce trends — silver lining! — at the start of the recession, which he followed up with an even worse piece of conservative-foundation bait. Unburdened by the desire to know the facts, and the burdens of peer review, he wrote in 2009:

judging by divorce trends, many couples appear to be developing a new appreciation for the economic and social support that marriage can provide in tough times. Thus, one piece of good news emerging from the last two years is that marital stability is up.

That was my introduction to his unique brand of incompetence (he was wrong) and dishonesty (note use of “Thus,” to imply a causal connection where none has been demonstrated), which revealed itself most egregiously during the Regenerus affair (the full catalog is under this tag). Still, people publish his un-reviewed nonsense, and the American Enterprise Institute has named him a visiting scholar. If they know this record, they are unscrupulous; if they don’t, they are oblivious. I keep mentioning it to help differentiate those two mechanisms.

Check the divorce tag and the recession tag for the work developing all this.

2 Comments

Filed under Me @ work, Research reports