The Young and the Jobless? It Matters That Generational Data Are Muddled

We think we have a pretty good idea of who and what we are. Xers, Boomers, Yers, Millennials, et al.

But it turns out that the data are less precise than we might like. This might not matter so much to those under consideration. After all, 1986, 1987, etc, who cares?

The issue is that how we are defined demographically, may have a profound impact on what we see, hear and learn. This, in turn, can shape the way we buy, vote and think for the rest of our lives. It determines what offers we receive - in securities, housewares, apps and cars - what music we listen to and how we then prioritize. All of which may have profound influences on how assets are allocated and resources apportioned.

In other words, figuring out how to define where we fit in the greater scheme of big data may well shape our future. So, being aware of the implications of what we are seeing on our various screens matters. Because it may hold the key to our individual and collective future. Which means that who owns and manages personal data is significant. As is getting it right. JL

Josh Zumbrun reports in Real Time Economics:

The differences between millennials, Generation X and baby boomers determine not only the shows on our screens and the content of our websites, but the nature of our jobs and the geography of our cities.

Good data on generations is hard to find.

Millennial or not? Actress Dakota Fanning, born in 1994, almost certainly makes the cut. But what about those born in 1995 or 2000 or 2003?

Associated Press

The differences between millennials, Generation X and baby boomers determine not only the shows on our screens and the content of our websites, but the nature of our jobs and the geography of our cities.
We’re generation-obsessed, but two key flaws muddy generational comparisons: Some 110 million Americans were born in years that fall between clear generational divides and data agencies fail to track generations over time.
1) Generation What?
One hindrance is that researchers use inconsistent years to date generations because there aren’t any official, semi-official or even pseudo-official definitions. The generation known as millennials is defined as beginning with births in 1978 or 1980 or 1981 or 1982 or 1983 or 1985. And the last birth year of the millennial generation is variously placed at 1994 or 1995 or 2000 or 2003. If you’re in your 20s, you’re almost definitely a millennial. But the periphery is undefined.

Between every generation there are gaps where researchers use different dates. All told, about 110 million Americans were born in years that are not consistently assigned to one generation or another — or about 35%.
But we could fix that. A number of agencies could step forward and create demarcations around U.S. generations. The Census Bureau makes a study of the U.S. population and is in a position to identify shifts. The Bureau of Labor Statistics knows the ins and outs of the U.S. workforce. The National Bureau of Economic Research, a nonprofit research organization with which many of the nation’s leading economists claim affiliation, steps in to sort through the numbers and provide dates around the recessions and recoveries of the U.S. economy.
The great benefit of NBER’s declarations are not that its dates are indisputable. The value of NBER’s chronology is that it creates a standard that researchers can use to compare apples to apples, even if one could have small quibbles. It’s crystal-clear that the economy experienced a sharp recession in 2008 and 2009 just as it’s crystal-clear a new generation of Americans was born after World War II.
2) How Do Young Adults Then Compare With Young Adults Now?

If you want to see the unemployment rate of people who were ages 25 to 34 in 2011, you can do so with a few quick clicks. But if you want to see the historical unemployment rate for people born in the 1980s, you can’t do it unless you have the statistical skills and stamina to dig through microdata.
If the U.S. had official dates for its generations, the data agencies could begin releasing data for different generations over time. When the Bureau of Labor Statistics releases unemployment rates by age, it’s also releasing unemployment rates by birth year. The unemployment rate for 20-to-24-year-old workers is 10.5%. And 25-to-34-year-old workers have unemployment of 6.2%.
Phrased in terms of birth year, people born from 1990 to 1994 have an unemployment rate of 10% and those born from 1980 to 1989 have 6.2% unemployment. As it happens, these are roughly the birth years that some researchers assign to millennials.

So the unemployment rate of the young is always higher than the unemployment rate of the old, an example of a life-cycle effect. But how has the labor market varied for different generations? What is the cohort effect? The existing surveys ask the right questions. But their data simply isn’t sorted this way, even though it’s a topic of keen interest from both academics and the general public.
The Labor Department is reluctant to release data with samples that are too narrow. Releasing statistics for people born in a single year may be too much to ask. But releasing statistics in five-year blocks, for example, would create much larger samples. Such data would allow for easy comparisons of unemployment rate and wages over time of people born in 1981 to 1985 versus those born in 1976 to 1980. This could yield interesting insights into the differing outcomes for people who were just beginning their careers when recession struck versus those who already had a strong foothold into the labor market.
If generations were clearly delineated, and high-quality statistics were made available to track their process, much of the low-quality rubbish about generations would