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Strengths and Weaknesses of Occupational Employment Statistics From the BLS

June 29, 2015 by Gwen Burrow

This article is part of series of blog posts that details the strengths and weaknesses of prominent labor market data sources. Find the whole series here.

The Occupational Employment Statistics (OES) program estimates employment and wages for most occupations by industry or sector at the national, state, metropolitan statistical area (MSA), metropolitan statistical division, and non-MSA levels in the 50 states and the District of Columbia. These estimates are accompanied by national industry staffing patterns. OES accounts for 1.2 million establishments and 62% of national employment, including railroad, but excluding military, agriculture, fishing, forestry, private households, self-employment, and others.

Strengths

  • OES has estimates for specific industries, including national industry-specific occupational employment and wage estimates.
  • OES has estimates for individual states, including cross-industry occupational employment and wage estimates for individual states.
  • OES has estimates for 586 metropolitan and nonmetropolitan areas, including 380 metropolitan statistical areas (MSAs) and 34 metropolitan divisions which make up 11 of the MSAs.

Weaknesses

  • OES is merely a survey and is not based on administrative records like Quarterly Census of Employment and Wages (QCEW) from the BLS; for these reasons the numbers aren’t as comprehensive as most industry data.
  • Not all metropolitan and nonmetropolitan areas have information for all occupations.
  • Only 62% of employment is covered in the OES survey (compared to the 98% of wage-and-salary jobs captured by QCEW), which excludes all industries under NAICS 11 (agriculture, forestry, fishing, and hunting) except for logging, support activities for crop production, and support activities for animal production.
  • The OES survey takes up to three years to complete, so the BLS states that it is less useful for measuring change in job counts or wages over time. An apparent increase in wages, for example, could just as likely be due to different businesses responding to the survey in one year, changes in the occupational, industrial, and geographical classification systems, changes to collection or estimation methods, or changes to other methodologies in the survey.
  • Industry data is generally available only at the national level, though the OES program has made some industry-specific OES estimates for individual states available for research purposes (beginning with the May 2012 estimates).

How EMSI Incorporates OES

OES is our primary source of occupation data, but we compensate for OES’s general weaknesses and lack of valid historical data by utilizing stronger, more accurate industry employment counts from QCEW, County Business Patterns (CBP), and American Community Survey (ACS), among others. We then apply a regionalized staffing pattern to the industry data to show the distribution of jobs by occupation. We derive this staffing pattern from OES occupation data and apply it to both our current-year data and our historic data, thus producing more reliable occupation counts.

About EMSI Data

EMSI’s comprehensive labor market dataset removes suppressions, includes proprietors, and is available for all counties and ZIP codes, creating a more complete picture of regional economies. This data gives you valuable insight on occupation growth and decline, industry trends, educational program completions, and lots more—all presented in a way that real people can understand. In addition to the US, EMSI offers thorough data for Canada and the UK, as well as France, Brazil, and Australia.

EMSI collects data from more than 90 public sources, harmonizes it, and delivers it so you can use it effectively. To learn more about EMSI data, visit our data page or contact us. Follow EMSI on Twitter (@DesktopEcon) or check us out on LinkedIn and Facebook.

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Gwen Burrow

Reach out at gburrow@economicmodeling.com

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