Ah, the Occupational Employment Quarterly (OEQ), it used to be the only game in town. Ridiculed by David Traver so many years ago, superseded by Job Browser Pro (JBP), and obsoleted by the Occupational Requirements Survey (ORS) joined by the Occupational Employment and Wage Statistics (OEWS). I have labeled the OEQ statistical trash, mostly because it is. But the OEQ does have a cadre of devotees that cling to it like a plank of balsa wood adrift in a sea storm. What's wrong with the OEQ? I am so glad that you asked.
The OEQ is well-known for its use of the equal distribution method of calculating job numbers. The Seventh Circuit labels that methodology as preposterous. Alaura v. Colvin. As Kevin Liebkemann points out in Job Incidence Numbers in Social Security Disability Claims: ACase Study and Analysis, even SkillTRAN publicly derides the OEQ as using a preposterous equal distribution methodology in its SkillTRAN Process for Estimating Employment Numbers (citing the later decision in Hill v. Colvin).
In Woods v. Bisignano, the Ninth Circuit affirmed the vocational witness's patent use of the OEQ using the equal distribution method. Judge Nelson concurring states that a categorical rule excluding testimony based on the equal distribution method runs afoul of Biestek v. Berryhill. Woods is wrong and so is Judge Nelson. Job numbers in Standard Occupational Classification (SOC) groups with very few DOT codes leads to results that are absurd. Consider telemarketers -- one sedentary semi-skilled DOT code. The Occupational Outlook Handbook disagrees. Telemarketers typically have short-term on-the-job training. The 2018 ORS dataset describes telemarketers as having up to 1 month of training in 50.3% of jobs. Equal distribution should require an explanation -- every single time it is used. The Seventh Circuit is right.
But let us assume that Judge Nelson is right, the equal distribution method is not so inherently flawed that there do exist some circumstances where it might be reasonable to use it. Let's play along. Ask the witness this question:
What is the data source that US Publishing uses to estimate job numbers stated in the OEQ?
The first page of the OEQ II 3.2 states that column 4 sets out the "current employment for this occupation." The last page of the OEQ 3.2 states that
- All data are estimates from government sources including the U.S. Department of Labor, Division of Occupational Employment Statistics and of the Local Area Unemployment Statistics.
The US Publishing web site invokes the 2010 decennial census. Clearly US Publishing has not updated its page or claim to use the 2020 decennial census. Nowhere does US Publishing claim to use the Current Population Survey or any other data source. Nor the US Publishing recognize that the OES is now the OEWS. A rose by any other name is still a rose and the OEWS and the OEWS data is found at www.bls.gov/oes/.
Since we know the US Publishing relied on OES/OEWS data from the OEQ and from the web page, we can compare and contrast the gross job number cited by the OEQ to the OEWS. A sample:
Occupation |
OEQ total
employment 4th
Qtr. 2024 |
OEWS total employment 2024 |
Credit
Authorizers, Checkers, and Clerks SOC 43-4041 |
63,662 |
11,960 |
Order Clerks 43-4151 |
216,280 |
83,420 |
Couriers and
Messengers SOC 43-5021 |
232,941 |
71,920 |
Word
Processors and Typists SOC 43-9022 |
258,841 |
36,020 |
Office Clerks,
General SOC 43-9061 |
2,351,948 |
2,510,550 |
Electrical
and Electronic Equipment Assemblers SOC 51-2022 |
179,597 |
261,140 SOC 51-2028 (includes SOC
51-2022 and SOC 51-2023) |
Inspectors,
Testers, Sorters, Samplers, and Weigher SOC 51-9061 |
727,005 |
591,180 |
Helpers—Production
Workers SOC 51-9198 |
273,294 |
167,490 |
Production
Workers, All Other SOC 51-9199 |
813,370 |
277,060 |
Cleaners of
Vehicles and Equipment SOC 53-7061 |
395,474 |
373,960 |
Packers and
Packagers, Hand SOC 53-7064 |
676,479 |
601,440 |
Stock Clerks
and Order Fillers SOC 43-5081 |
2,009,370 |
2,779,530 Stockers and Order Fillers SOC 53-7065 |
The numbers are not reconcilable. Most of the occupations selected off the top of my head are so far off that they are clearly unreliable.
That is strike two against the OEQ. US Publishing uses equal distribution based on the number of exertion-skill DOT codes resident in the SOC code. US Publishing's stated source for job numbers does not support the job numbers stated. Of the 867 codes in the 2018 SOC, 485 have at least some change from the 2010 SOC. US Publishing and its OEQ have not kept up nor paid attention to the combination of two SOC detailed groups into a single reported group (51-2028) in the current dataset.
The OEQ as it is currently constituted needs to die.
___________________________
Suggested Citation:
Lawrence Rohlfing, What's Wrong with the OEQ -- Attacking Its Foundation and Methodology, California Social Security Attorney (August 27, 2025) https://californiasocialsecurityattorney.blogspot.com
The author has been AV-rated since 2000 and listed in Super Lawyers since 2008.

