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

Data available from OES

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

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)  

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 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 23 Major groups 97 Minor groups 461 Broad occupations 840 Detailed occupations

Occupational classification SOC Example Major group 41-0000 Sales and related occupations Minor group 41-2000 Retail sales workers Broad occupation 41-2020 Counter and rental clerks and parts salespersons Detailed occupations 41-2021 Counter and rental clerks Receive orders, generally in person, for repairs, rentals, and services. May describe available options, compute cost, and accept payment. 41-2022 Parts salespersons Sell 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)

OES methodology Sample design Data collection cycle Estimation

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

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

OES Survey Operations OMB clearance Operational structure Data collection and processing

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

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

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 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

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 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 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

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 2009 May 2009 November 2008 May 2008 November 2007 Employment estimation Sample weight adjustment Benchmarked to industry employment level from external source

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

Dixie Sommers Assistant Commissioner, Office of Occupational Statistics and Employment Projections 202-691-5701 Sommers.Dixie@bls.gov Laurie Salmon Supervisory Economist, Division of Occupational Employment Statistics 202-691-5701 Salmon.Laurie@bls.gov www.bls.gov/oes