Unemployed or Underemployed?
This post summarizes the differences between Unemployed and Underemployed, national and state, and the various occupations in the USA. Then we get into some data as it relates to me, and end with my POV on the Tech Recession in 2024
Unemployment U-3
In the US we hear a bunch about the Unemployment rate, which is defined and tracked by the US Bureau of Labor Statistics (BLS). Their definition for Unemployed is “do not have a job, have actively looked for work in the prior 4 weeks, and are currently available for work” – bls.gov. They get their data by conducting the Current Population Survey (CPS). The CPS measures the extent of unemployment in the country, conducted in the United States every month since 1940. There are about 60,000 eligible households in the sample for this survey, and it includes all 50 states and Washington DC.
Note that 60,000 households number in CPS. Recently that is about 260,000 people, or about 0.08% of the total US population of about 340 million. Roughly speaking employed people as percent of total population varies by state, around 55-68%
source: https://www.bls.gov/opub/ted/2024/annual-average-unemployment-rates-decreased-in-6-states-in-2023.htm
Underemployment U-6
Underemployment is a more broad term that loosely means anyone who is willing and able to take a full time job. This includes people who are training, working part-time, and are just discouraged.
Specifically the BLS offers data related to Underemployment under the term U-6 data
“Total unemployed, plus all persons marginally attached to the labor force, plus total employed part time for economic reasons, as a percent of the civilian labor force plus all persons marginally attached to the labor force“
Compare to the official unemployment rate, U-3 which is defined
“Total unemployed, as a percent of the civilian labor force“
source: https://www.bls.gov/news.release/empsit.t15.htm
And BLS defines
“The marginally attached are those persons not in the labor force who want and are available for work, and who have looked for a job sometime in the prior 12 months, but were not counted as unemployed because they had not searched for work in the 4 weeks preceding the survey”
source: https://www.bls.gov/cps/lfcharacteristics.htm#discouraged
Data Fall 2024, U-3 vs U-6
U-3 National Data – 4.1% Oct 2024 – Unemployment
U-6 National Data – 7.7% Oct 2024 – Underemployment
U-3 California Data – 5.1% avg 2023-Q4 to 2024-Q3. 4.5% avg 2022-Q4 to 2023-Q3
U-6 California Data – 10.0% avg 2023-Q4 to 2024-Q3. 8.9% avg 2022-Q4 to 2023-Q3
source: https://www.bls.gov/lau/stalt.htm
Table: Alternative measures of labor underutilization by state, fourth quarter of 2023 through third quarter of 2024 averages (percent)
| Area | Measure | |||||
|---|---|---|---|---|---|---|
| U-1 | U-2 | U-3 | U-4 | U-5 | U-6 | |
| State | ||||||
| Total, all states | 1.4 | 1.9 | 3.9 | 4.2 | 4.8 | 7.4 |
| Alabama | 0.7 | 1.4 | 2.8 | 3.0 | 3.3 | 4.7 |
| Alaska | 1.3 | 2.3 | 4.7 | 5.2 | 6.0 | 7.9 |
| Arizona | 1.1 | 1.5 | 3.6 | 3.8 | 4.6 | 7.2 |
| Arkansas | 1.1 | 1.4 | 3.5 | 3.8 | 4.4 | 6.1 |
| California | 2.0 | 2.7 | 5.1 | 5.4 | 6.2 | 10.0 |
| Colorado | 1.3 | 1.5 | 3.9 | 4.0 | 4.6 | 7.6 |
| Connecticut | 1.4 | 2.3 | 3.7 | 3.8 | 4.3 | 7.2 |
| Delaware | 1.3 | 1.7 | 3.6 | 3.8 | 4.6 | 7.2 |
| District of Columbia | 2.3 | 2.3 | 5.2 | 5.4 | 6.0 | 8.1 |
| Florida | 1.0 | 1.5 | 3.0 | 3.3 | 4.0 | 6.3 |
| Georgia | 1.0 | 1.5 | 3.2 | 3.6 | 4.3 | 6.8 |
| Hawaii | 1.2 | 1.2 | 3.0 | 3.1 | 3.9 | 6.4 |
| Idaho | 1.0 | 1.7 | 3.5 | 3.7 | 4.2 | 6.5 |
| Illinois | 2.1 | 2.5 | 4.9 | 5.2 | 6.0 | 8.6 |
| Indiana | 1.0 | 1.9 | 4.1 | 4.4 | 5.1 | 7.7 |
| Iowa | 0.7 | 1.5 | 2.9 | 3.0 | 3.7 | 5.5 |
| Kansas | 1.1 | 1.6 | 3.3 | 3.5 | 3.8 | 6.0 |
| Kentucky | 1.5 | 1.8 | 4.9 | 5.1 | 5.7 | 8.2 |
| Louisiana | 1.6 | 2.1 | 4.2 | 4.5 | 5.1 | 7.6 |
| Maine | 0.6 | 1.0 | 2.8 | 2.9 | 3.5 | 6.3 |
| Maryland | 1.4 | 1.6 | 3.7 | 4.0 | 4.6 | 6.8 |
| Massachusetts | 1.4 | 2.1 | 4.0 | 4.2 | 4.9 | 7.1 |
| Michigan | 1.7 | 2.0 | 4.2 | 4.4 | 5.3 | 7.7 |
| Minnesota | 1.0 | 1.6 | 3.3 | 3.4 | 3.8 | 6.2 |
| Mississippi | 1.0 | 1.0 | 2.8 | 3.0 | 3.5 | 5.3 |
| Missouri | 1.0 | 1.6 | 3.6 | 3.8 | 4.1 | 6.0 |
| Montana | 0.8 | 1.5 | 3.3 | 3.5 | 4.0 | 6.2 |
| Nebraska | 0.5 | 1.4 | 2.8 | 2.9 | 3.5 | 5.6 |
| Nevada | 2.0 | 2.3 | 5.0 | 5.4 | 6.1 | 9.0 |
| New Hampshire | 0.8 | 1.3 | 2.6 | 2.7 | 3.2 | 5.2 |
| New Jersey | 2.1 | 2.4 | 4.5 | 4.8 | 5.3 | 8.1 |
| New Mexico | 1.6 | 1.9 | 4.0 | 4.2 | 4.8 | 7.4 |
| New York | 1.9 | 2.4 | 4.4 | 4.6 | 5.6 | 8.2 |
| North Carolina | 1.4 | 1.8 | 3.4 | 3.6 | 4.1 | 6.7 |
| North Dakota | 0.8 | 1.3 | 2.9 | 3.0 | 3.5 | 4.9 |
| Ohio | 1.2 | 1.8 | 4.1 | 4.2 | 4.9 | 7.3 |
| Oklahoma | 1.1 | 1.8 | 3.6 | 3.8 | 4.5 | 7.0 |
| Oregon | 1.4 | 1.6 | 4.0 | 4.2 | 5.1 | 8.0 |
| Pennsylvania | 1.2 | 1.7 | 3.4 | 3.5 | 4.1 | 6.4 |
| Rhode Island | 1.9 | 2.7 | 4.5 | 4.6 | 5.1 | 7.6 |
| South Carolina | 1.4 | 1.8 | 4.1 | 4.3 | 5.0 | 6.9 |
| South Dakota | 0.4 | 1.0 | 1.9 | 1.9 | 2.1 | 3.3 |
| Tennessee | 1.4 | 1.3 | 3.2 | 3.6 | 4.1 | 5.8 |
| Texas | 1.4 | 1.8 | 4.0 | 4.2 | 4.7 | 7.5 |
| Utah | 0.9 | 1.4 | 3.6 | 3.8 | 4.4 | 6.8 |
| Vermont | 0.6 | 1.1 | 2.2 | 2.3 | 2.9 | 4.4 |
| Virginia | 1.0 | 1.4 | 3.1 | 3.2 | 3.7 | 6.0 |
| Washington | 1.7 | 2.3 | 4.9 | 5.2 | 5.8 | 9.2 |
| West Virginia | 1.5 | 1.8 | 3.9 | 4.3 | 4.6 | 6.5 |
| Wisconsin | 0.7 | 1.4 | 3.0 | 3.1 | 3.5 | 5.5 |
| Wyoming | 1.0 | 1.3 | 3.0 | 3.1 | 3.4 | 5.4 |
| Selected substate area | ||||||
| Los Angeles County | 2.4 | 3.1 | 5.7 | 6.0 | 6.8 | 11.8 |
| New York City | 2.7 | 2.6 | 5.2 | 5.5 | 6.5 | 9.6 |
Occupations and Industry Sectors
Sometimes in the unemployment data you see numbers broken down by industry, like here
https://www.bls.gov/emp/tables/employment-by-major-industry-sector.htm
BLS has about a dozen top level industries it tracks as well as hundreds of industries that are under those top level ones, identified with NAICS numbers (000000 format).
https://www.bls.gov/iag/tgs/iag_index_naics.htm
Top Level Industry examples that I identify with are “Information” or “Professional and business services“.
To view high level industry data by time, over last 20 years, look at https://www.bls.gov/charts/employment-situation/employment-levels-by-industry.htm
To see high level industry data by state
https://www.bls.gov/charts/state-employment-and-unemployment/industry-employment-by-state.htm
BLS separately tracks hundreds of Occupation Titles and codes (00-0000 format). There are 867 using 2018 SOC system. https://www.bls.gov/soc/
Since 2022, OEWS program uses the 2018 Standard Occupational Classification (SOC) system. A downloadable XLS file of May 2021 OEWS occupations with definitions is now available – https://www.bls.gov/oes/soc_2018.htm
https://www.bls.gov/oes/occupation_definitions_m2021.xlsx
Sometimes you will see it referred to as “2023 National Employment Matrix title”.
You can even type and match to more specific job titles, then see which occupation code they relate to https://data.bls.gov/projections/nationalMatrixHome?ioType=o
Its important to focus on occupation, not industry, when viewing from individual’s POV. Most of the unemployment data on bls.gov does not separate by occupation. And when it is, it is high level occupation.
To see numbers for different occupations in different industries,
First view the https://www.bls.gov/emp/tables/industry-occupation-matrix-industry.htm
which shows the industry sectors.
Then Click on the the top link TE1000 to see data table showing actual 2023 unemployment numbers by OCCUPATION.
https://data.bls.gov/projections/nationalMatrix?queryParams=TE1000&ioType=i
Click on “2023 Employment” in the table header to sort by that column, to see the most popular occupations.
The 2023 employment is 167,849k or 168 million for all occupations
Occupation Titles I identify with include “Computer and mathematical occupations 15-0000″ and “Computer and information systems managers 11-3021″.
The 2023 employment is 5,417k for Computer and mathematical occupations 15-0000, 3.2% of all occupations
The 2023 employment is 613k for Computer and information systems managers 11-3021, 0.37% of all occupations
Therefore about 3.6% (6M out of 168M total) of employment jobs are occupations I identify with (15-0000 and 11-3021)
I wish I could get the 15-000 occupation granularity for other stats, like U-3 and U-6, but I could not find it.
BLS API
BLS does have an api, and can easily retrieve JSON data via GET/POST, but it is limited to certain types of requests. I was specifically interested in finding employment data by occupation as I mentioned earlier, but could not.
https://www.bls.gov/developers/api_signature_v2.htm
curl -i -X POST -H 'Content-Type: application/json' -d '{"seriesid":["LNU04000248", "LNU05000248", "LEU0254555900", "APU0000701111"], "startyear":"2002", "endyear":"2012"}' https://api.bls.gov/publicAPI/v2/timeseries/data/
I did find out about Series ID Formats from https://www.bls.gov/help/hlpforma.htm
I also found an easy way to generate Series ID from Labor Force Statistics from the CPS https://data.bls.gov/PDQWeb/ln
ex:
LNU04000248: Men White All Origins 50 to 54 years All educational levels N/A Unemployment rate Not Seasonally Adjusted Monthly
LNU05000248: Men White All Origins 50 to 54 years All educational levels N/A Not in labor force Not Seasonally Adjusted Monthly :
More Definitions and Links
Labor force is either people employed, or unemployed (ones are jobless, looking for a job, and available for work).
Must be 16 or older to be considered as part of the labor force
So if jobless and not looking (but want a job and are available), NOT in labor force.
Or if jobless and looking but unavailable (hospital, armed forces, etc), not in labor force.
Full time is 35 hours or more per week; part time is 1 to 34 hours per week.
Involuntary part time – people who want to work full time but cannot for economic reasons (unable to find full time work)
https://usafacts.org/articles/is-there-a-labor-shortage-in-the-us
Here’s more on U-3 vs U-6 https://www.investopedia.com/articles/investing/080415/true-unemployment-rate-u6-vs-u3.asp
“September 2020, the U-3 unemployment rate was 7.9%. The U-6 rate was 12.8%.”
Tech Recession in 2024
People keep asking, “Why can’t you find a job, the unemployment rate is low?”
As a Techie in California, I am having an incredibly hard time finding a decent job. For about a year I’ve applied to hundreds of jobs and am barely getting interviews. I hear stories from managers that say they are getting a thousand applications for every tech job posting. I hear stories that tech companies prioritize those who have previously worked for them. And so on.
So how is it that we have a historically good (low) unemployment rate yet I cannot get a decent job?
I had to dig in the data to find out, and wrote this as a result. What I learned and detailed above is that the Underemployment rate (U-6) is about double the Unemployment rate (U-3) for California.
I think Underemployment is a better metric for measuring the job market from individuals perspective, it makes me feel better. I also learned that the occupations I identify with as a techie are only 3.6% of the total, so even if there is 30% or even 50% unemployment in my occupations, it would barely affect the state or national numbers.
Anecdotal evidence and the following also help explain why I cannot get a decent job, which I summarize to be these reasons
- Inflation And Higher Interest Rates
- Economic Downturn And Recession Fears
- The AI Factor
- Pandemic Over Hiring
- Outsourcing And Offshoring
Sources
- 2024-11-25 https://finance.yahoo.com/news/six-figure-job-market-faces-151536711.html
- 2024-11 https://www.businessinsider.com/white-collar-recession-hiring-slump-jobs-tech-industry-applications-rejection-2024-11
- 2024-10-2 https://callmerohit.medium.com/analysing-tech-layoffs-which-roles-were-hit-hardest-40c1de969380
- 2024-9-20 https://www.reddit.com/r/ITCareerQuestions/comments/1flwe9v/how_long_do_you_guys_think_the_tech_recession/
- 2024-8-19 https://www.forbes.com/sites/emilsayegh/2024/08/19/the-great-tech-reset-unpacking-the-layoff-surge-of-2024/
- 2023-12-22 https://www.reddit.com/r/economy/comments/18oqzp9/why_is_the_us_unemployment_rate_so_poorly/
