Tag Archives: generations

Fertility trends and the myth of Millennials

The other day I showed trends in employment and marriage rates, and made the argument that the generational term “Millennial” and others are not useful: they are imposed before analyzing data and then trends are shoe-horned into the categories. When you look closely you see that the delineation of “generations” is arbitrary and usually wrong.

Here’s another example: fertility patterns. By the definition of “Millennial” used by Pew and others, the generation is supposed to have begun with those born after 1980. When you look at birth rates, however,  you see a dramatic disruption within that group, possibly triggered by the timing of the 2009 recession in their formative years.

I do this by using the American Community Survey, conducted annually from 2001 to 2015, which asks women if they have had a birth in the previous year. The samples are very large, with all the data points shown including at least 8,000 women and most including more than 60,000.

The figure below shows the birth rates by age for women across six five-year birth cohorts. The dots on each line mark the age at which the midpoint of each cohort reached 2009. The oldest three groups are supposed to be “Generation X.” The three youngest groups shown in yellow, blue, and green — those born 1980-84, 1985-89, and 1990-94 — are all Millennials according to the common myth. But look how their experience differs!

cohort birth rates ACS.xlsx

Most of the fertility effect on the recession was felt at young ages, as women postponed births. The oldest Millennial group was in their late twenties when the recession hit, and it appears their fertility was not dramatically affected. The 1985-89 group clearly took a big hit before rebounding. And the youngest group started their childbearing years under the burden of the economic crisis, and if that curve at 25 holds they will not recover. Within this arbitrarily-constructed “generation” is a great divergence of experience driven by the timing of the great recession within their early childbearing years.

You could collapse these these six arbitrary birth cohorts into two arbitrary “generations,” and you would see some of the difference I describe. I did that for you in the next figure, which is made from the same data. And you could make up some story about the character and personality of Millennials versus previous generations to fit that data, but you would be losing a lot of information to do that.

cohort birth rates ACS.xlsx

Of course, any categories reduce information — even single years of age — so that’s OK. The problem is when you treat the boundaries between categories as meaningful before you look at the data — in the absence of evidence that they are real with regard to the question at hand.

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Two examples of why “Millennials” is wrong

When you make up “generation” labels for arbitrary groups based on year of birth, and start attributing personality traits, behaviors, and experiences to them as if they are an actual group, you add more noise than light to our understanding of social trends.

According to generation-guru Pew Research, “millennials” are born during the years 1981-1997. A Pew essay explaining the generations carefully explains that the divisions are arbitrary, and then proceeds to analyze data according to these divisions as if are already real. (In fact, in the one place the essay talks about differences within generations, with regard to political attitudes, it’s clear that there is no political consistency within them, as they have to differentiate between “early” and “late” members of each “generation.”)

Amazingly, despite countless media reports on these “generations,” especially millennials, in a 2015 Pew survey only 40% of people who are supposed to be millennials could pick the name out of a lineup — that is, asked, “These are some commonly used names for generations. Which of these, if any, do you consider yourself to be?”, and then given the generation names (silent, baby boom, X, millennial), 40% of people born after 1980 picked “millennial.”

“What do they know?” You’re saying. “Millennials.

Two examples

The generational labels we’re currently saddled with create false divisions between groups that aren’t really groups, and then obscure important variation within the groups that are arbitrarily lumped together. Here is just one example: the employment experience of young men around the 2009 recession.

In this figure, I’ve taken three birth cohorts: men born four years apart in 1983, 1987, and 1991 — all “millennials” by the Pew definition. Using data from the 2001-2015 American Community Surveys via IPUMS.org, the figure shows their employment rates by age, with 2009 marked for each, coming at age 26, 22, and 18 respectively.

milemp

Each group took a big hit, but their recoveries look pretty different, with the earlier cohort not recovered as of 2015, while the youngest 1991 group bounced up to surpass the employment rates of the 1987s by age 24. Timing matters. I reckon the year they hit that great recession matters more in their lives than the arbitrary lumping of them all together compared with some other older “generations.”

Next, marriage rates. Here I use the Current Population Survey and analyze the percentage of young adults married by year of birth for people ages 18-29. This is from a regression that controls for year of age and sex, so it can be interpreted as marriage rates for young adults (click to enlarge).

gens-marriage

From the beginning of the Baby Boom generation to those born through 1987 (who turned 29 in 2016, the last year of CPS data), the marriage rate fell from 57% to 21%, or 36 percentage points. Most of that change, 22 points, occurred within the Baby Boom. The marriage experience of the “early” and “late” Baby Boomers is not comparable at all. The subsequent “generations” are also marked by continuously falling marriage rates, with no clear demarcation between the groups. (There is probably some fancy math someone could do to confirm that, with regard to marriage experience, group membership by these arbitrary criteria doesn’t tell you more than any other arbitrary grouping would.)

Anyway, there are lots of fascinating and important ways that birth cohort — or other cohort identifiers — matter in people’s lives. And we could learn more about them if we looked at the data before imposing the categories.

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