Is the “institution” still in decline if the incidence of marriage rebounds, but only at older ages?
The crash scenario – showing marriage ending around 2050, is there to show where the 1950-2014 trajectory is headed (it’s also a warning against using linear extrapolation to predict the future). The rebound scenario is intended to show how unrealistic the “revive marriage culture” people are. The taper scenario emerges as the most likely alternative; in fact, it’s grown more likely since I first made the figure a few years ago, as you can see by the 2010-2014 jag.
So let’s consider the tapering scenario more substantively — what would it look like? One way to get a declining marriage rate is if marriage is increasingly delayed, even if it doesn’t become less common; people still marry, but later. (If everyone got married at age 99, we would have universal marriage and a very low refined marriage rate.) I give some evidence for this scenario here.
These trends are presented with minimal discussion; I’m not looking at race/ethnicity or social class, childbearing or the recession; I’m not discussing divorce and remarriage and cohabitation, and I’m not testing hypotheses. (This is a list of research suggestions!) To make the subject more enticing as a research topic (and for accountability), I’ve shared the Census data, Stata code, and spreadsheet file used to make this post in this OSF project. You can use anything there you want. You can also easily fork the project — that is, make a duplicate of its contents, which you then own, and take off on your own trajectory, by adding to or modifying them.
For some context, here is the trend in percentage of men and women ever married, by age, from 1960. (“Ever married” means currently married, separated, divorced, or widowed.) This clearly shows both life-course delay and lifetime decline, but delay is much more prominent, at least so far. Even now, almost 90% of people have been married by age 60 or so, while the marriage rates for people under 35 have plummeted.
People become ever-married when they get first-married. We measure ever-married prevalence from a survey question on current marital status, but first-marriage incidence requires a question like the American Community Survey asks, “In the past 12 months, did this person get married?” Because they also ask how many times each person has been married, you can calculate a first marriage rate with this ratio:
Until recently it hasn’t been easy to measure first-marriage across all ages; now that we have the ACS marital events data (since 2008) we can. This allows us to look at the timing of first marriage, which means we can use current age-specific first-marriage rates to project lifetime ever-married rates under current conditions.
Here are the first-marriage rates for men and women, by age. Each set of bars shows the trend from 2008 to 2016. The left side shows men, by age; the right side shows women, by age; the totals for men and women are in the middle. This shows that first-marriage rates have fallen for men and women under age 35, but increased for those over age 35. The total first-marriage rate has rebounded from the 2013 crater, but is still lower than 2008.
This is a short-range trend, 9 years. It could be recession-specific, with people delaying marriage because of hardships, or relationships falling apart under economic stress, and then hurrying to marry a few years later. But it also fits the long-term trend of delay over decline.
The overall rates for men and women show that the 2014-2016 rebound has not brought first-marriage rates back to their 2008 level. However, what about lifetime odds of marriage? The next figure uses women’s age-specific first-marriage rates to project lifetime odds of marriage for three years: 2008, the 2013 crater, and 2016. This shows, for example, that at 2008 rates 59% of women would have married by age 30, compared with 53% in both 2013 and 2016.
The 2013 and 2016 lines diverge after age 30, and by age 65 the projected lifetime ever-married rates have fully recovered. This implies that marriage has been delayed, but not forgone (or denied).
Till now I’ve shown age and sex-specific rates, but haven’t addressed other things that might changed in the never-married population. Finally, I estimated logistic regressions predicting first-marriage among never married men and women. The models include race, Hispanic origin, nativity, education, and age. In addition to the year and age patterns above, the models show that all races have lower rates than Whites, Hispanics have lower rates than non-Hispanics, foreign-born people have higher rates (which explains the Hispanic result), and people with more education first-marry more (code and results in the OSF project).
To see whether changes in these other variables change the story, I used the regressions to estimate first-marriage rates at the overall mean of all variables. These show a significant rebound from the bottom, but not returning to 2008 levels, quite similar to the unadjusted trends above:
This is all consistent with the taper scenario described at the top. Marriage delayed, which reduces the annual marriage rate, but with later marriage picking up much of the slack, so that the decline in lifetime marriage prevalence is modest.
* The refined marriage rate is the number of marriages as a fraction of unmarried people. This is more informative than the crude marriage rate (which the National Center for Health Statistics tracks), which is marriages as a fraction of the total population. In this post I use what I guess you would call an age-specific refined first-marriage rate, defined above.