Tag Archives: recession

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.

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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.

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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 online in the Maryland Population Research Center working paper collection.

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.

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Divorce recession drop rebound, with the 2012 rate

Note: Technical addendum added.

The Census Bureau’s American Community Survey is the best annual national data source for marital events. The 2012 data came out recently, and I don’t believe anyone else has published a divorce rate for 2012. The refined divorce rate – the number of divorces per 1,000 married people – was 19.0 in 2012. Here is the trend since the ACS starting counting divorces:

divrat08-12

What does this mean? It’s a shame the ACS didn’t start counting marital events till 2008, because it means we can’t put that year’s high rate in context. Was it (a) a spike up, suggesting divorce was a leading indicator for the recession; (b) part of a consistent decline, suggesting the the years since have been a pretty substantial increase from the historical trend; or, (c) a data anomaly.*

To put this in the context of the larger trend doesn’t really help answer the question, since we switched from vital records to a national survey, and had a decade with no national statistics in between:

divrate40-12

So, it’s a mystery. My preferred interpretation is still that the recession caused a decline in divorces because disgruntled people were tied up in other crises, couldn’t sell their houses, or couldn’t afford to move out, followed by a rebound of accumulated divorces to our current level.

I published a working paper suggesting this [now forthcoming in Population Research and Policy Review], in which I use 2008 predictors of divorce and estimate that 4% fewer divorces occurred through 2011 compared to what would have been expected had the determinants of divorce not changed in the subsequent years.

My blog series on divorce includes previous reports on rates, and attempts to predict divorce rates using Google searches.

Technical addendum

To replicate my rates for 2012, you start here at the FactFinder, then get the number of married people by sex (ACS Table B12001) and the number of people who got divorced in the 12 months before the survey (ACS Table S1251) — you can enter the table numbers into the search box. There is a slight problem with this, however. Some people who say they got divorced in the past 12 months also say they are currently married (presumably remarried already). Those people are counted twice in the denominator of the FactFinder-based divorce rate — once as divorced people and once as currently married. If you download the public-use file and count those people only once in the denominator, the divorce rate rises by .02 per 1,000 (or 2 people per 100,000) — but this would not change the figures above at the level of precision reported. However, the public-use files produce slightly different estimates than the FactFinder files anyway, because the latter are based on the Census Bureau’s complete file not a subsample, so I use those even though they produce this tiny under-estimate of the divorce rate.

Secondly, what about the difference in divorce rates between men and women? This is a survey, not a vital records count, and there is no way to verify with the now-missing spouses whether they also consider themselves divorced. Maybe they weren’t legally married, or they didn’t really get legally divorced. So there are several possibilities: (a) lots of lesbian divorces, which is unlikely given the small number of lesbian marriages (but note we don’t know the sex of the spouse who is no longer in the household so we can’t distinguish homogamous from heterogamous divorces); (b) women are more likely to describe a breakup as a divorce for reasons unknown; (c) something funky with the survey weights (unweighted divorce rates from the public-use file also show the disparity, but it’s 20% smaller), or; (d) something funky with the sampling.

Who knows! If you are reading this and considering a new career — or a new direction in your existing career — consider becoming a family demographer and helping us figure it out.

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Maybe the recession increased violence after all

I have organized a special session for the American Sociological Association meetings next August titled, “Hard Times, Gender, and Families,” featuring the research of S. Philip Morgan, Margaret Michele Gough, Krista Perreira and Kristen Harknett. This is blurb for the session:

The Great Recession altered the gender dynamics within families in ways we are only beginning to understand. Some trends were accelerated for reasons that are not positive, while others may have been slowed or even reversed. This subject is vexing for researchers because it involves adjudicating between the effects of underlying conditions, long-term trends, and short-term shocks. In the past several years we have seen new research on how labor market conditions affect family violence, the gender division of labor, and fertility decisions. However, we have as yet no overarching theory of how this recession – or economic shocks in general – helped shape gender within families. In this session a panel of researchers who have done empirical work in this area broaden their focus to address this general question.

I hope to see you there (San Francisco, August 16-19).

Violence

Violence will be just part of that discussion, but that’s the subject of today’s update. I’ve gone back and forth a little on this question of the recession and violence as I come across different information:

In that last post I was skeptical the recession increased violence because of falling violence numbers for 2010, which seemed wrong for the recession story, including this trend in intimate-partner homicide from New York State:

Now that we have another year of national data on intimate partner violence, I’m leaning back toward the recession-increased-violence story. Look at 2008 and 2009 in this trend:

ipv-trend

Writing in 2011 I couldn’t believe that 2010 would already be showing declines from any recession-induced spike in violence. And unemployment rates actually peaked in 2010, so that’s reasonable. But 2008 and 2009 were the years with the greatest increases in men’s unemployment rates, and the big jump in the sex difference in unemployment rates:

ue-sex

So if intimate partner violence is partly triggered by men’s economic hardship and insecurity — with some gender-difference dynamic (say, within couples) — the sex difference might make sense. Just a thought. No conclusion yet, but since I’ve been posting on the subject I thought an update was in order. Maybe by next August will know more.

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Breaking through the Wilcoxian ceiling of nonmarital births

Finishing off right-wing family think-tank recognition week.

In the first post I pointed out the right-wing foundations gave their academic and think-tankian foot-soldiers more than $5 million over three years to prop up conservative family ideals. In the second post I ridiculed Brad Wilcox’s unsupported assertion that “the nation’s retreat from marriage may have bottomed out.” He based that on the fact that marriage rates did not fall in 2010 or 2011 after the very steep drop in 2009. (Thank G-d for small favors.)

Today is a quick one to point out the even worse distortion in the second half of Wilcox’s sunny-side post. He wrote:

In the wake of the Great Recession, nonmarital childbearing has accounted for 41 percent of all births from 2008 to the present. This is the first time in at least 40 years that the percentage of children being born outside of wedlock has remained stable for five years.

That kind of trend-line bottom feeding reminds me of the basketball announcer’s patter as the player steps to the free-throw line: “He’s only 71 percent from the line on the season, but he’s three-for-four so far tonight.”

Anyway, it’s worse than that because of the way demography works. To give away the conclusion: after 2008 births shifted dramatically to older women as younger women’s fertility rates fell. Older women have lower unmarried childbearing rates. So the overall unmarried-birth rate didn’t rise much even as the unmarried-birth rate in each age group continued to rise.

You gotta love demography. Here are the trends.

Note I’m using the Census Bureau’s American Community Survey data, which asks a giant national sample of women each year if they’ve had a baby in the past 12 months. If gives rates a little different from the trend Wilcox showed, which was based on vital registry data submitted by the states to the CDC. I use this because it’s easy to break births out by age and marital status for each year. (Unfortunately, the IPUMS data archive I use doesn’t have the 2012 file up yet, and the Census website was shut down by Wilcox’s friend Mike Lee and his GOP colleagues.)

Anyway. First, here are the percent of births to mothers who are not married, the total and by age group, shown as changes from 2006. Wilcox is talking about the relatively flat “total” trend from 2008 to 2012.

wilcox-blog-debunk-1

In these data the total trend is upward for whatever reason having to do with the data source, but it doesn’t matter because the point is the same. The amazing thing is that by 2011 the total increase is smaller than the increase for each age group! That is, from 2006 to 2011, the percentage of all births that were to unmarried women increased 2.6 percent, but the increase was steeper for each specific group — up to a 4.3 percent increase for women in their 20s. (Some “enduring appeal of marriage”!)

How is this possible? It happened because births shifted from younger to older women, as we’ve known since 2011. And older women are much more likely to be married when they have children. Here’s how big that difference is:

wilcox-blog-debunk-2Twenty-something women are almost twice as likely to be unmarried when they have babies as those in their 30s and 40s. And here’s how big the change was in who was having babies from 2008 forward:

wilcox-blog-debunk-3Wow! Women in their 40s had 80,000 more babies in 2011 than they did in 2006. Those in their 20s had 134,000 less. Remember the women in their 20s were also the ones who had the steepest increase in nonmarital births rates. That means that among this group it was married women who cut their birth rates — probably deliberately postponing births because they have a biological clock buffer and could afford to hold off till (they hoped) the economy picked up. Meanwhile, the older crowd, who are on a long march toward higher birth rates, couldn’t fit that delay into their plans, so their birth rates didn’t fall.

So, back to Wilcox to see how this new evidence fits his triumphal conclusion:

But the enduring appeal of marriage for most Americans may also be part of the story for both of the trends noted above. For the vast majority of Americans, marriage remains an integral part of the American Dream. … The enduring appeal of marriage may translate into a floor for the marriage rate, insofar as a substantial share of Americans remain committed to tying the knot [see the last post], and a ceiling for the nonmarital childbearing rate, insofar as a substantial share of Americans remain committed to having their children in wedlock.

Of course a “substantial share remain committed” to marriage. No one would suggest otherwise. But the ceiling/floor story is just a (pontifical) fantasy. If the percentage of women at every age having their births while not married has continued to increase — regardless of whether the overall percentage is pretty flat for a few years — then we have to conclude the story he tells is complete baloney.

(Follow my Brad Wilcox stories under the National Marriage Project tag even though he’s blogging for the Institute for Family Studies now. As long as IFS operates out of the same post office box as Brad’s shell foundation, I’m not giving them their own tag.)

ADDENDUM: I should have discussed more the differences between these data and the vital statistics. Elizabeth Gregory, author of Ready: Why Women Are Embracing the New Later Motherhood, sent the following chart using the NCHS data. This appears to confirm that, although the number of births are different, the trends by age after 2008 are very similar to what I reported from the ACS data.
20131004-085555.jpg

ADDITIONAL ADDENDUM: The ACS reports more births than NCHS, because ACS asks about the “previous 12 months,” which goes back to, for example, June for interviews in June, so that can be up to 13 months. Also, ACS respondents on average are interviewed 6 months after they gave birth, so they skew older than the NCHS data. I don’t know if these two differences account for the difference between my numbers from ACS and those sent by Elizabeth Gregory. But I think the point remains that the stall in non-marital births is probably an artifact of the shift to older-age births during the recession.

Sources:

ACS births 2011: Census version (not available during shutdown); Wayback Machine version.

Census Powerpoint report on differences with NCHS: Census version (not available during shutdown); Wayback Machine version.

 

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Percent describing themselves as “lower class” hits 40-year high

Yipes. Have you seen the General Social Survey responses to the CLASS question lately?

Since 1972, they’ve asked,

If you were asked to use one of four names for your social class, which would you say you belong in: the lower class, the working class, the middle class, or the upper class?

The responses have been pretty stable, with close to an even split between working and middle, and tails of 5% or less in upper and lower. But not anymore:

gss-classIt might not look that dramatic. But let me zoom in on that red line for you:

gss-lower-class

 

I’m sure some of you (like those who have written books on this question) will be able to explain this beyond: wow, this recession made more people poor. The official poverty rate today is about where it was back when “lower class” was at 4%.

 

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