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Labor Statistics and its Little Secret

Data-Driven Intelligence, Programmatic| Views: 890

Someone misrepresented facts. Again.

‘Unemployment’ vs. ‘Underemployment’

This time it was Senator Sanders during the first Democratic Debate:

African American youth unemployment is 51 percent. Hispanic youth unemployment is 36 percent. // Sen. Bernie Sanders (D-VT)

The mistake: Right numbers. Wrong attribution.

Labor Statistics (provided by EPI): Big Difference between Unemployment and Underemployment
Labor Statistics (provided by EPI): Big Difference between Unemployment and Underemployment // source: own figure

The data is from a recent report prepared by the Economic Policy Institute (EPI). The talk was on ‘unemployment’ while quoting ‘underemployment’.

The difference is quite big.


Labor Statistics: They Are Hard to Tell Apart

Statistics can be ‘framed’ easily. Hence one should be mindful when interpreting them.

#1: Different Sources

Labor market data is provided by governmental organizations (e.g. BLS) as well as independent think tanks (e.g. EPI). Different institutions use different methods to base their numbers on.

#2: Different Data Sets

Both organizations define ‘recent high school graduates’ differently:

  • Bureau of Labor Statistics (BLS): 16-24 years
  • Economic Policy Institute (EPI): 17-20 years

#3: Different Classifications

Even within a consistent and clean data set of a particular organization there are alternative measures of labor underutilization (url).

For example: The BLS uses 6 levels of ‘underutilization’:

  • U-1 – persons unemployed 15 weeks or longer, as a percent of the civilian labor force
  • U-2 – job losers and persons who completed temporary jobs, as a percent of the civilian labor force
  • U-3 [UNEMPLOYED] – total unemployed, as a percent of the civilian labor force (= definition for ‘official unemployment rate’)
  • U-4 – total unemployed plus discouraged workers, as a percent of the civilian labor force plus discouraged workers
  • U-5 – total unemployed, plus discouraged workers, plus all other marginally attached workers, as a percent of the civilian labor force plus all marginally attached workers
  • U-6 [UNDEREMPLOYED] – total unemployed, plus all marginally attached workers, plus total employed part time for economic reasons, as a percent of the civilian labor force plus all marginally attached workers

Intentionally or not, it is easy to mix things up.

'Unemployment' vs. 'Underemployment': confused about the difference
‘Unemployment’ vs. ‘Underemployment’: confused about the difference // source: giphy.com

Reading Between the Lines

All confusion aside, research shows a clear picture: young Americans have a lot of room to grow.

∂ 'Undermployed' = huge potential for recruiting
Bernie’s mishap pointed out a big opportunity: attracting the ‘marginally attached workers’ and the ’employed part time for economic reasons’. // source: own figure

If employers play it smart, they can attract 25 million+ young Americans who are looking for ‘better opportunities’.

An effective way of reaching these audiences will help finding the right talent – even in tight labor markets.


Bottomline:

  • Check your facts & question statistics
  • The pool of potential candidates can be bigger than expected

Additional Reading & Links:

  • Great research work by FactCheck.org (url) – basis for this article
  • Employment status (U.S. // Q2 2015) provided by BLS (url)
  • Bernie Sanders website (url)
  • Ezra Klein & Bernie Sanders interview (url)
  • Bureau of Labor Statistics Glossary (url)

About Spencer Parra

Spencer Parra is the VP of Product Management for advertising and data products at Radancy. In that capacity, Spencer and his team of product managers, program managers, data scientists, and data analysts work to develop products in a data driven mindset. As the leader of Advertising products, he works to bring a holistic full funnel approach to Radancy’s advertising technology stack with Programmatic Jobs at its foundation. Through data products, he tells the story of media performance via Radancy’s Metrics Gateway and helps ensure data is democratized through Radancy’s unified platform. Spencer came to Radancy from the Perengo acquisition in mid 2019 where he served as Lead Product Manager and a member of the founding team. With Perengo, he worked towards the vision of leveraging the same rigor and concepts from ecommerce advertising technology to the recruitment advertising space. Prior to Perengo, Spencer launched and supported in-app advertising products at Criteo as a solutions engineer. Spencer holds a B.S. in Aerospace Engineering from the Massachusetts Institute of Technology.

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