1. Sampling and Collection in the Occupational Employment Statistics (OES) Program
Dixie Sommers and Laurie Salmon
Occupational Information Development Advisory Panel
May 4, 2011

2. Overview Data available from OES Uses and users of OES data
Standard classifications used
OES sample design
OES survey operations
OES estimation methods
Special OES tabulations for O*NET

3. Data available from OES

4. Occupational Employment Statistics
Employment and wages for over 800 occupations
Cross-industry estimates for
The Nation
States, District of Columbia, and selected territories
Over 580 metropolitan and nonmetropolitan areas
National estimates by specific industries
Estimates by ownership
Published annually with May reference date
May 2010 data to be published May 17, 2011

5. Data items available Employment Hourly and annual mean wages
Hourly and annual wages by percentile
10th, 25th, median, 75th, 90th percentiles
Measure of sampling error
Employment and mean wage percent relative standard errors (PRSEs)

6. Uses and users Employers and Human Resources professionals
Compare pay to data for their industry or area
Understanding occupational employment and wages in making location and expansion decisions
Academic researchers
Understanding the structure of the labor market
Understanding wages
Media and general public

7. Uses and users Career and job search information
Students and job seekers
Guidance and career counselors
Policy and program uses
E.g., wages for Foreign Labor Certification
Staffing patterns uses
Preparing employment projections
O*NET sampling design to identify industries with concentrations of employment in occupations being surveyed

8. Standard classifications used

9. Industry classification
North American Industrial Classification System (NAICS)
Establishments are classified according to the goods or services the establishment produces
Issued by Office of Management and Budget
Jointly developed by U.S., Canada, and Mexico
U.S. Economic Classification Policy Committee chaired by Census Bureau
Revised every five years (2002, 2007, 2012)

10. Industry classification
NAICS example
21 Mining, Quarrying, and Oil and Gas Extraction
211 Oil and Gas Extraction
2111 Oil and Gas Extraction
21111 Oil and Gas Extraction
Crude Petroleum and Natural Gas Extraction
Natural Gas Liquid Extraction

11. Occupational classification
Standard Occupational Classification (SOC)
Workers and jobs are classified into occupations based on the work performed
Issued by Office of Management and Budget
Standard Occupational Classification Policy Committee chaired by BLS
Established SOC Classification Principles and Coding Guidelines
Revised 2000 and 2010
Next revision planned for 2018

12. Occupational classification
2010 SOC structure
23 Major groups
97 Minor groups
461 Broad occupations
840 Detailed occupations

13. Occupational classification
SOC Example
Major group
Sales and related occupations
Minor group
Retail sales workers
Broad occupation
Counter and rental clerks and parts salespersons
Detailed occupations
Counter and rental clerks
Receive orders, generally in person, for repairs, rentals, and services. May describe available options, compute cost, and accept payment.
Parts salespersons
Sell spare and replacement parts and equipment in repair shop or parts store.

14. Occupational classification
SOC Manual provides approved modifications to the structure
Delineation below the detailed occupation level permitted
Add digits to the code
Financial Managers
Treasurers and Controllers
OMB recommends that those needing extra detail use the O*NET structure   

15. Occupational classification
All Federal agencies publishing occupational data for statistical purposes required to use SOC
Increases data comparability across Federal programs
SOC developed for statistical purposes only
Non-statistical purposes play no role in SOC development
OMB will not modify the SOC to meet requirements of non-statistical programs

16. Using industries and occupations together
The combination of industry and occupation can further define the work
E.g., retail salesperson may work selling cars and may need to drive. Others may work in stores and need to stand.
OES provides these data
Distribution of an occupation’s employment by industry
Distribution of an industry’s employment by occupation (staffing pattern)

17. OES methodology
Sample design
Data collection cycle
Estimation

18. OES sample design Universe and sample sizes Sampling frame
Unemployment insurance list of employers
Covers 98 percent of wage and salary jobs
Industry, county and employment level for each establishment
Supplemented by other sources for industries not covered by state unemployment insurance
Mainly Federal government and railroads
Universe and sample sizes
Universe size of about 8 million establishments
1.2 million establishments in OES sample

19. OES sample design Sample stratification
By metropolitan and non-metropolitan area
By industry strata
Generally 4-digit NAICS, some 5-digit NAICS
By ownership for certain sectors
Education and hospitals by state government, local government, and private ownership

20. OES sample design Sample allocation for each stratum
Include all large establishments
“Certainty units”
Improves sample efficiency
For all other units
Based on expected variability and stratum size
Minimum number of sample units

21. Data collection cycle Full sample collected over 3-year cycle
Two collection panels per year
Reference dates of May and November

22. OES Survey Operations OMB clearance Operational structure
Data collection and processing

23. OMB clearance OMB clearance to conduct the survey Requires
Description of purpose and uses
No duplication of other federal data sources
Detailed sample description
Description of respondent burden hours and cost
Response rate targets
Use of standard classification systems
Description of collection methods
Public comment periods

24. Operational structure
Federal-State Cooperative Program
BLS National and Regional offices
State Workforce Agencies
BLS responsibilities
Concepts and procedures
Sample design and selection
Survey form design, printing and mailing
Data capture and estimation systems
Produce and publish estimates
Data quality assurance
Training and technical assistance
Confidentiality policy and procedures
Funding

25. Operational structure
State workforce agency responsibilities
Address refinement of sample units
Data collection, including non-response follow-up
Data processing and editing
Occupational coding
Estimates review and publication
Protect data confidentiality

26. OES survey forms Developed through cognitive and field testing
For all types of establishments
Verify known information about the establishment: employment, industry
Request contact information for follow-up

27. OES survey forms Structured forms
For medium size and larger establishments
Specific to individual industries or groups of industries
Lists occupations commonly found in the industry
Includes occupation definitions
Employer determines how SOC codes relate to establishment’s job categories

28. OES survey forms Unstructured forms Open-ended format
For smaller establishments
For all non-responding establishments in the third follow-up mailing
Open-ended format
No occupations listed on form
Employer reports by own job categories
Data coded to SOC by state or regional office staff

29. OES survey forms All forms
Request employment in the occupation by wage intervals
Wage intervals used to estimate wage means, medians, and percentiles

30. Data collection Mailing Response mode options
Includes form, letter, information sheet
Second and third mailings to non-respondents
Response mode options
Complete paper form and mail back
Complete form online
Phone response
Fax response
Provide electronic payroll file (mail or )
Provide paper payroll listing

31. Data collection Improving response rates Pre-notification postcards
Telephone follow-up
Flexibility in reporting mode
Web site for respondents
Why respondent’s data are important
Provide publications
Confidentiality pledge
Training data collectors on reluctance aversion

32. Data collection Response mode varies by establishment size
Response rates for most recent panel
77.7 percent of establishments
69.5 percent of employment

33. OES estimation methods
Use three years of data (six panels)
May 2010 data based on these panels:
May November 2009
May November 2008
May 2008 November 2007
Employment estimation
Sample weight adjustment
Benchmarked to industry employment level from external source

34. OES estimation methods
Wage estimation using wage interval data
BLS National Compensation Survey data used to estimate mean wages in each interval
BLS Employment Cost Index used to “age” wages collected in earlier panels
Wages estimation using wage rate data
Direct computation of means, medians, and percentiles
Wage rate data for in certain sectors
Federal government, U.S. Postal Service
State government in many states

35. Special tabulations for O*NET
Distribution of occupational employment by 6-digit NAICS
More detailed than published OES data
Shows industries and areas with most employment in the occupation
Useful for targeting sample selection on industries where occupation known to exist

36. Dixie Sommers Assistant Commissioner, Office of Occupational Statistics and Employment Projections Laurie Salmon Supervisory Economist, Division of Occupational Employment Statistics