1. Highlights from the May 2016 Occupational Employment Statistics data
Audrey Watson
Economist
Occupational Employment Statistics
June 6, 2017

2. Occupational Employment Statistics
Employment and wage estimates by occupation
Joint BLS/state program
Employer/establishment survey
Sample comes from state unemployment insurance (UI) database
Statistically representative by industry and area
Total sample size 1.2 million business establishments, collected over 3-year period
Sample covers approximately 81 million jobs, representing 58 percent of U.S. employment

3. Coverage and classification
Excludes private households and most of agricultural sector
Also excludes military and self employed
Within federal government, includes executive branch and U.S. Postal Service only (excludes legislative and judicial branches)
Industries defined by North American Industry Classification System (NAICS)
Occupations defined by Standard Occupational Classification (SOC) system

4. Data elements produced
Data by occupation for over 800 occupations:
Employment
Mean and percentile wages
(both hourly and annual for most occupations)
Measures of sampling error

5. Estimates available
Cross-industry occupational employment and wage estimates by geographic area
Nearly 600 metropolitan and nonmetropolitan areas
States, District of Columbia, and selected U.S. territories
Nation
Industry-specific estimates—national level only
Over 430 industry aggregations
National estimates by ownership (public/private)
Estimates for STEM and non-STEM occupations
Estimates by typical entry-level educational requirement

6. DOL uses of OES data Within BLS: Foreign Labor Certification
Occupational employment projections
Occupational Outlook Handbook
Occupational injury and illness incidence rates
Employment Cost Index
Foreign Labor Certification
Service Contract Act
CareerOneStop
O*NET
Employment Standards Administration

7. State uses of OES data Assisting employers:
By improving the alignment of education and training with the needs of business
In helping to build a skilled workforce to meet hiring demands
In making business location decisions
In selecting wage/pay scales relative to local competitive levels
Assisting career counselors with reemployment and job placement for students, job seekers, and dislocated workers
Assisting economic development with labor supply for business recruitment

8. Other users of OES data
Federal government: Center for Medicare and Medicaid Services, President’s Pay Agent, Bureau of Economic Analysis
Private sector/individuals: Human resources professionals, students, job seekers, guidance and career counselors, academic researchers, media

9. Accessing OES data Main OES data page: www.bls.gov/oes/tables.htm
Each type of data (national, state, metropolitan/nonmetropolitan area, industry, ownership) available in separate XLS files or on HTML pages
“All data” file available in XLS or TXT format
Data search tool:
Create customized tables using most recent data

10. Highlights from the May 2016 OES data

11. Construction laborers was the largest construction and extraction occupation

12. Elevator installers and repairers was the highest paying construction and extraction occupation

13. Petroleum and coal products manufacturing was the highest paying manufacturing industry for production occupations

14. Most registered nurses worked in general medical and surgical hospitals

15. San Jose was the highest paying area for STEM occupations

16. The San Jose area had high concentrations of several computer occupations

17. Nearly 37 percent of employment was in occupations that typically require postsecondary education for entry

18. Arkansas and North Dakota had the highest shares of occupations that typically require a postsecondary nondegree award for entry

19. Retail salespersons and cashiers were the largest occupations

20. Several of the largest public sector occupations were related to education

21. Occupational Employment Statistics
Audrey Watson
Economist
Occupational Employment Statistics