Tag Archives: divorce

Vasectomy reversal, divorce, and American optimism

That would be a good title for a longer essay (feel free to use it).

“Studies suggest that up to 6% of such men will request vasectomy reversal,” wrote the authors of a chapter in Clinical Care Pathways in Andrology. “Divorce with remarriage is by far the most common reason for vasectomy reversal.”

So, when in the divorce process do people start Googling “vasectomy reversal”? Is it men with younger girlfriends, considering leaving their wives? Women considering marrying a divorced man? Divorced couples considering another round of kids?

I don’t know, but Google does, or they could if they looked into it. I’ve only gotten as far as the strong relationship between searches for “vasectomy reversal” and state divorce rates:

vasectomy-divorce

I like to think of it as the optimism rooted in the American spirit. We always look forward to the next renewal, the next reboot, rebranding, or escape. Not because I really think it’s true, I just like to think of it that way.

The Google data is from their Trends tool, the divorce data is from the ACS via IPUMS.org.)


(This is a return to an old post, in which I first noticed this relationship, with new data. Now I think divorce per population makes more sense for Google correlations, rather than divorce per married population, which I used before.)

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The liberalization of divorce attitudes proceeds apace

The 2016 Gallup poll results on what is morally acceptable versus morally wrong came out over the summer, and they show that U.S. attitudes toward divorce continue to grow more positive. The acceptable attitude has gained 5 points in the last 5 years:

divorcegallup

This parallels results from the General Social Survey, which asks, “Should divorce in this country be easier or more difficult to obtain than it is now?” The latest GSS is still 2014, but it also shows a marked increase in the liberal easier view over the same time period:

divorcegss

See more under the divorce tag.

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Life table says divorce rate is 52.7%

After the eternal bliss, there are two ways out of marriage: divorce or death.

I have posted my code and calculations for divorce rates using the 2010-2012 American Community Survey as an Open Science Framework project. The files there should be enough to get you started if you want to make multiple-decrement life tables for divorce or other things.

Because the American Community survey records year of marriage, and divorce and widowhood, it’s perfectly set up for a multiple-decrement life table approach. A multiple-decrement life table uses the rate of each of two exits for each year of the original state (in this case marriage), to project the probability of either exit happening at or after a given year of marriage. It’s a projection of current rates, not a prediction of what will happen. So, if you write a headline that says, “your chance of divorce if you marry today is 52.7%,” that would be too strong, because it doesn’t take into account that the world might change. Also, people are different.

The divorce rate of 52.7% can accurately be described like this: “If current divorce and widowhood rates remain unchanged, 52.7% of today’s marriages would end in divorce before widowhood.” Here is a figure showing the probability of divorce at or after each year of the model:

div-mdlt

So there’s 52.7% up at year 0. Marriages that make it to year 15 have a 30% chance of eventually divorcing, and so on.

Because the ACS doesn’t record anything about the spouses of divorce or widowed people, I don’t know who was married to whom, such as age, education, race-ethnicity, or even the sex of the spouse. So the estimates differ by sex as well as other characteristics. I estimated a bunch of them in the spreadsheet file on the OSF site, but here are the bottom lines, showing, for example, that second or higher-order marriages have a 58.5% projected divorce rate and Blacks have a 64.2% divorce rate, compared with 52.9% for Whites.

div-mdlt-tab

(The education ones should be taken with a grain of salt because education levels can change but this assumes they’re static.)

Check the divorce tag for other posts and papers on divorce.

The ASA-style citation to the OSF project would be like this:  Cohen, Philip N. 2016. “Multiple-Decrement Life Table Estimates of Divorce Rates.” Retrieved (osf.io/zber3).

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Has your marriage lasted 50 years? Congratulations, you’re old

Just kidding: Congratulations, you’re old and have had a long marriage.

The Washington Post magazine has a feature out today called “The secret to a long-lasting marriage.” I don’t have a general comment on it, because I only made it to the third paragraph, and it’s probably worth reading.

But the third paragraph is funny:

They have beaten the odds of death and divorce: Of all current U.S. marriages, only 7 percent have reached the 50-year mark, according to the National Center for Family and Marriage Research at Bowling Green State University.

It is certainly true that making it to the 50-year mark of marriage means you have beaten the odds of death and divorce. But that 7% figure has nothing to do with it, because it includes people who got married yesterday!

Here is the breakdown of when people got married, among people married right now (in the 2014 American Community Survey, which has to be the source for that statistic):

yrmar14

So the statistic is correct: only 7% of currently married people have been married for 50 years or more. Good for them! To bad for all those other people they were born so recently.

It’s all in the denominator. Sure, 50-year marrieds are rare, but compared to what?

With the ACS we can answer a more relevant question, which is this: among living people whose most recent marriage was 50 years ago or more, what is their current marital status? This is a little more encouraging: half are still married.

mars50p

So let’s restate the original congratulatory message like this:

They have beaten the odds of death and divorce: Of all people who tied the knot 50 or more years ago, and who haven’t yet died, only 50% percent have made it this far without divorcing or becoming widowed, according to the American Community Survey.

Many happy returns.

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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.

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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.

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How we really can study divorce using just five questions and a giant sample

It would be great to know more about everything, but if you ask just these five questions of enough people, you can learn an awful lot about marriage and divorce.

Questions

First the questions, then some data. These are the question wordings from the 2013 American Community Survey (ACS).

1. What is Person X’s age?

We’ll just take the people who are ages 15 to 59, but that’s optional.

2. What is this person’s marital status?

Surprisingly, we don’t want to know if they’re divorced, just if they’re currently married (I include people are are separated and those who live apart from their spouses for other reasons). This is the denominator in your basic “refined divorce rate,” or divorces per 1000 married people.

3. In the past 12 months, did this person get divorced?

The number of people who got divorced in the last year is the numerator in your refined divorce rate. According to the ACS in 2013 (using population weights to scale the estimates up to the whole population), there were 127,571,069 married people, and 2,268,373 of them got divorced, so the refined divorce rate was 17.8 per 1,000 married people. When I analyze who got divorced, I’m going to mix all the currently-married and just-divorced people together, and then treat the divorces as an event, asking, who just got divorced?

4. In what year did this person last get married?

This is crucial for estimating divorce rates according to marriage duration. When you subtract this from the current year, that’s how long they are (or were) married. When you subtract the marriage duration from age, you get the age at marriage. (For example, a person who is 40 years old in 2013, who last got married in 2003, has a marriage duration of 10 years, and an age at marriage of 30.)

5. How many times has this person been married?

I use this to narrow our analysis down to women in their first marriages, which is a conventional way of simplifying the analysis, but that’s optional.

Data

I restrict the analysis below to women, which is just a sexist convention for simplifying things (since men and women do things at different ages).*

So here are the 375,249 women in the 2013 ACS public use file, ages 16-59, who were in their first marriages, or just divorced from their first marriages, by their age at marriage and marriage duration. Add the two numbers together and you get their current age. The colors let you see the basic distribution (click to enlarge):

2011-2013 agemar figures.xlsx

The most populous cell on the table is 28-year-olds who got married three years ago, at age 25, with 1068 people. The least populous is 19-year-olds who got married at 15 (just 14 of them). The diagonal edge reflects my arbitrary cutoff at age 59.

Divorce results

Now, in each of these cells there are married people, and (in most of them) people who just got divorced. The ratio between those two frequencies is a divorce rate — one specific to the age at marriage and marriage duration. To make the next figure I used three years of ACS data (2011-2013) so the results would be smoother. (And then I smoothed it more by replacing each cell with an average of itself and the adjoining cells.) These are the divorce rates by age at marriage and years married (click to enlarge):

2011-2013 agemar figures.xlsx

The overall pattern here is more green, or lower divorce rates, to the right (longer duration of marriage) and down (older age at marriage). So the big red patch is the first 12 years for marriages begun before the woman was age 25. And after about 25 years of marriage it’s pretty much green, for low divorce rates. The high contrast at the bottom left implies an interesting high risk but steep decline in the first few years after marriage for these late marriages. This matrix adds nuance to the pattern I reported the other day, which featured a little bump up in divorce odds for people who married in their late thirties. From this figure it looks like marriages that start after the woman is about 35 might have less of a honeymoon period than those beginning about age 24-33.

To learn more, I go beyond those five great questions, and use a regression model (same as the other day), with a (collapsed) marriage-age–by–marriage-duration matrix. So these are predicted divorce rates per 1000, holding education, race/ethnicity, and nativity constant (click to enlarge)**:

2011-2013 agemar figures.xlsx

The controls cut down the late-thirties bump and isolate it mostly to the first year. This also shows that the punishing first year is an issue for all ages over 35. The late thirties just showed the bump because that group doesn’t have the big drop in divorce after the first year that the later years do. Interesting!

Sigh

Here’s where the awesome data let us down. This data is very powerful. It’s the best contemporary big data set we have for analyzing divorce. It has taken us this far, but it can’t explain a pattern like this.

We can control for education, but that’s just the education level at the time of the most recent survey. We can’t know when she got her education relative to the dates of her marriage. Further, from the ACS we can’t tell how many children a person has had, with whom, and when — we only know about children who happen to be living in the household in 2013, so a 50-year-old could be childfree or have raised and released four kids already. And about couples, although we can say things about the other spouse from looking around in the household (such as his age, race, and income), if someone has divorced the spouse is gone and there is no information about that person (even their sex). So we can’t use that information to build a model of divorce predictors.

Here’s an example of what we can only hint at. Remarriages are more likely to end in divorce, for a variety of reasons, which is why we simplify these things by only looking at first marriages. But what about the spouse? Some of these women are married to men who’ve been married before. I can’t how much that contributes to their likelihood of divorce, but it almost certainly does. Think about the bump up in the divorce rate for women who got married in their late thirties. On the way from high divorce rates for women who marry early to low rates for women who marry late, the overall downward slope reflects increasing maturity and independence for women, but it’s running against the pressure of their increasingly complicated relationship situations. That late-thirties bump may have to do with the likelihood that their husbands have been married before. Here’s the circumstantial evidence:

2011-2013 agemar figures.xlsx

See that big jump from early-thirties to late-thirties? All of a sudden 37.5% of women marrying in their late-thirties are marrying men who are remarrying. That’s a substantial risk factor for divorce, and one I can’t account for in my analysis (because we don’t have spouse information for divorced women).

On method

Divorce is complicated and inherently longitudinal. Marriages arise out of specific contexts and thrive or decay in many different ways. Yesterday’s crucial influence may disappear today. So how can we say anything about divorce using a single, cross-sectional survey sample? The unsatisfying answer is that all analysis is partial. But these five questions give us a lot to go on, because knowing when a person got married allows us to develop a multidimensional image of the events, as I’ve demonstrated here.

But, you ask, what can we learn from, say, the divorce propensity of today’s 40-year-olds when we know that just last year a whole bunch of 39-year-olds divorced, skewing today’s sample? This is a real issue. And demography provides an answer that is at once partial and powerful: Simple, we use today’s 39-year-olds, too. In the purest form, this approach gives us the life table, in which one year’s mortality rates — at every age — lead to a projection of life expectancy. Another common application is the total fertility rate (watch the video!), which sums birth rates by age to project total births for a generation. In this case I have not produced a complete divorce life table (which I promised a while ago — it’s coming). But the approach is similar.

These are all synthetic cohort approaches (described nicely in the Week 6 lecture slides from this excellent Steven Ruggles course). In this case, the cohorts are age-at-marriage groups. Look at the table above and follow the row for, say, marriages that started at age 28, to see that synthetic cohort’s divorce experience from marriage until age 59. It’s neither a perfect depiction of the past, nor a foolproof prediction of the future. Rather, it tells us what’s happening now in cohort terms that are readily interpretable.

Conclusion

The ACS is the best thing we have for understanding the basic contours of divorce trends and patterns. Those five questions are invaluable.


* For this I also tossed the people who were reported to have married in the current year, because I wasn’t sure about the timing of their marriages and divorces, but I put them back in for the regressions.

** The codebook for my IPUMS data extraction is here, my Stata code is here. The heat-map model here isn’t in that code file, but this these are the commands (and the margins command took a very long time, so please don’t tell me there’s something wrong with it):

logistic divorce i.agemarc#i.mardurc i.degree i.race i.hispan i.citizen
margins i.agemarc#i.mardurc

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