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 classification

NAICS 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 periods

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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 Information

Dixie SommersAssistant Commissioner, Office of Occupational Statistics and

Employment Projections 202-691-5701

Sommers.Dixie@bls.gov

Laurie SalmonSupervisory Economist, Division of Occupational Employment Statistics

202-691-5701Salmon.Laurie@bls.gov

www.bls.gov/oes