Uh Oh… Employment Data is Actually Worse then 1980s! A Fourth Way of looking at the data.

I enjoy reading  “The Numbers Guy” column in the WSJ, but today, guest writer Cari Tuna really hit it out of the park with her piece on a problem in statistical analysis called  Simpson’s Paradox. Cari reports that the paradox is under-stating the severity of unemployment data.

A few weeks ago, I wrote a piece of three ways to look at the DOL employment data. Now, a fourth view emerges because of Simpson’s Paradox.

First, what is the paradox? Here’s Wikipedia’s version:

Simpson’s paradox (or the Yule-Simpson effect) is an apparent paradox in which the successes of groups seem reversed when the groups are combined. This result is often encountered in social and medical science statistics, and occurs when frequency data are hastily given causal interpretation; the paradox disappears when causal relations are derived systematically, through formal analysis.

Or, more simply (my version): Sometimes, because one subgroup of data can be much larger than another group, the total average looks better (or worse) than what’s really going on.

For unemployment, what Cari reported is that for college graduates and high school graduates, employment is really worse than the 80’s, but the total average doesn’t reflect this reality on the ground. Consider this:

Total Unemployment 25 and Older
1983: 8.5%
2009: 8.2%

For College Grads
1983: 3.6%
2009: 4.9%

For High School Dropouts:
1983: 13.6%
2009: 14.9%

And there’s the paradox at work, both College grads and High School dropouts are worse off, but the total unemployment data does not reflect the reality. Why? There are more college grads today (1/3rd of the working population) vs. 1983 (1/4 of the working population), which skews comparisons between the 2 recessions!

The WSJ article is good reading. It should be noted that the analysis was done by Henry Farber , an economist from Princeton found here.


Jeremy Shapiro is an executive in HR at a leading financial services firm, working on talent analytics. Formerly a Senior Vice President of the Hodes iQ Talent Management Suite at Bernard Hodes Group and is a co-author of the HR metrics book Ultimate Performance. Jeremy has coached hundreds of companies in recruiting and HR technology solutions across industries and sizes. Jeremy is a frequent speaker and author on HR technology topics and HR Business Intelligence topics, such as SHRM, IHRIM, the Human Capital Institute, HR.com and more. He is a frequent contributor to articles and whitepapers on HR Business Intelligence. Jeremy holds a Masters of Science in Information Systems from NYU and a B.A in Economics from Rutgers University. Specific topics of research include HR metrics, talent management technology, and next generation recruiting technologies.

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2 comments on “Uh Oh… Employment Data is Actually Worse then 1980s! A Fourth Way of looking at the data.
  1. Mitch Golden says:

    I don’t think it makes sense to say that things are worse than the 1980s based on this “paradox”. Suppose the government could institute a policy that would double the percentage of the population that has a college degree. Suppose too that the unemployment rate among college grads went from 5% to 6%, while nothing happened to the hs grads.

    Would you say that the population is worse off? Unemployment goes down, more of the population is educated, but this one metric is worse.

    • measuringtalent says:

      Hey! Thanks for reading the post 🙂 The title/post was actually mostly to provoke I suppose. I’ve been tearing down the DOL unemployment rate announcements recently because I’ve seen many attempts to compare today to past recessions (poorly), and skimming over the details of any statistic. Unemployment % doesn’t tell us a ton about the health of a society in a business cycle, but I think sometimes the stat is carried in the news along with “the sky is falling”.

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