Sampling and Collection in the Occupational
Employment Statistics (OES) Program
Dixie Sommers and Laurie Salmon
Occupational Information Development Advisory Panel
May 4, 2011
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
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Data available from OES
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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
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)
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
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
Standard classifications used
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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)
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Industry classificationNAICS example
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21 Mining, Quarrying, and Oil and Gas Extraction
211 Oil and Gas Extraction
2111 Oil and Gas Extraction
21111 Oil and Gas Extraction
211111 Crude Petroleum and Natural Gas Extraction
211112 Natural Gas Liquid Extraction
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
Occupational classification
2010 SOC structure
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23 Major groups
97 Minor groups461 Broad occupations
840 Detailed occupations
Occupational classification
SOC Example
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Major group 41-0000 Sales and related occupations
Minor group 41-2000 Retail sales workersBroad occupation 41-2020 Counter and rental clerks and parts salespersons
Detailed occupations
41-2021 Counter and rental clerksReceive orders, generally in person, for repairs, rentals, and services. May describe available options, compute cost, and accept payment.
41-2022 Parts salespersonsSell spare and replacement parts and equipment in repair shop or parts store.
Occupational classification SOC Manual provides approved
modifications to the structure Delineation below the detailed
occupation level permitted Add digits to the code
– 11-3031 Financial Managers– 11-3031.01 Treasurers and Controllers
OMB recommends that those needing extra detail use the O*NET structure
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
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)
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OES methodology Sample design Data collection cycle Estimation
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OES sample design 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
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
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
Data collection cycle Full sample collected over 3-year
cycle Two collection panels per year Reference dates of May and
November
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OES Survey Operations OMB clearance Operational structure Data collection and processing
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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 periods23
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
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
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
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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
OES survey forms Unstructured forms
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
OES survey forms All forms
Request employment in the occupation by wage intervals
Wage intervals used to estimate wage means, medians, and percentiles
Data collection Mailing
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 email) Provide paper payroll listing
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
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Data collection Response mode varies by
establishment size
Response rates for most recent panel 77.7 percent of establishments 69.5 percent of employment
OES estimation methods
Use three years of data (six panels) May 2010 data based on these panels:
May 2010 November 2009May 2009 November 2008May 2008November 2007
Employment estimation Sample weight adjustment Benchmarked to industry employment level
from external source
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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
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
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Contact InformationDixie Sommers
Assistant Commissioner, Office of Occupational Statistics and Employment Projections
[email protected] Laurie Salmon
Supervisory Economist, Division of Occupational Employment Statistics 202-691-5701
www.bls.gov/oes