Labor Market Information Methodology and uses

Part 2

Dennis ReidBureau of Labor Statistics San Francisco Regional

OfficeOctober 2014

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Bureau of Labor Statistics The BLS is the principal fact-finding agency for

the Federal Government in the broad field of labor economics and statistics

The BLS mission is to collect, process, analyze and disseminate data

BLS is an independent statistical agency. It serves its diverse user communities by providing products and services that are objective, timely, accurate, and relevant.

Users include the American public, Congress, Federal agencies, state and local governments, businesses, labor organizations

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Fed/State Cooperative Programs

Partnership with eight States & GuamContract: LMI & OSHS Cooperative

Agreements

BLS → States– $, procedures, sample selection, systems, manuals,

training (OSHS: 50% funding by law)

– Ensure consistency across all states

States → BLS– Collect, process and edit the data– Analyze/publish State and area data

BLS ↔ States– Policy collaboration via Workforce Information Council

and Program Policy Councils

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Labor Force Programs Overview

BLS and the Federal/State Cooperative Programs

Comparison of programs NAICS (North American Industry Classification System)

QCEW (Quarterly Census of Employment & Wages “ES-202”)

CES (Current Employment Statistics)

OES (Occupational Employment Statistics)

CPS (Current Population Survey)

LAUS (Local Area Unemployment Statistics)

JOLTS (Job Openings and Labor Turnover Survey)

OSHS (Occupational Safety & Health Statistics)

Comparison of Labor Force and OSHS Programs

QCEW CES OES CPS LAUS JOLTS SOII CFOI

Data Collected by

States & BLS BLS States & BLS ROs Census BureauInput from CPS, CES,

UIBLS States and BLS States and BLS

Data Collected from

Establishments Establishments Establishments HouseholdsInput from CPS, CES,

UIEstablishments Establishments various sources

Estimate or Universe Count?

Universe Estimate Estimate Estimate Estimate Estimate Estimate Universe

Frequency of Collection

Quarterly for monthly data

Monthly Semi-Annual Monthly Monthly Monthly Annual on a flow basis

Frequency of Publication

Quarterly & Annual

Monthly Annual Monthly Monthly Monthly Annual Annual

Major Data Types Published

UI covered employment &

wages by industry

Nonfarm employment, hours, hourly earnings by

industry

Occupational employment &

wages by area and industry

Civilian labor force, employment,

unemployment, Unemp. rate for

the nation

Civilian labor force, employment,

unemployment, Unemp. rate for

States & local areas

Nonfarm job openings, hires, and separations by industry and

region

Workplace Injuries and Illnesses

Workplace Fatalities

Geographic Detail Published

County, MSAs, State, USA

MSAs, State, USA

MSAs, State, USA USA

Cities & towns 25,000+, County, LMA, MSA, State, Census Division &

Region

Census Region and USA

USA and most States

MSAs, State, USA

Demographic Detail Published

None Women Workers NoneExtensive

Demographic Detail

None NoneGender, age, race/ethnicity

Gender, age, race/ethnicity

Are Data Benchmarked?

No, QCEW is a benchmark

Yes, to QCEW Yes, to QCEW No Yes, to CPS Yes, to CES Yes, to QCEWNo, CFOI is a universe count

Major Uses Sample frame & benchmark

Economic Indicator

Foreign Labor Certification,

Planning training & educational programs

Economic IndicatorEconomic Indicator, Allocation of funds

Economic Indicator

Workplace safety programs

Workplace safety programs

Time from Reference Period to 1st BLS Publication

6 months or more

USA- 3 weeks; States- 5 weeks; MSAs- 7 weeks

10 months 3 weeksStates- 5 weeks; Areas- 7 weeks

4-6 weeks after reference month

10 months 8 months

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Current Employment Statistics (CES)

www.bls.gov/ces for National data

www.bls.gov/sae for State & Area data

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CES - Basic Theory

Need data quicker than QCEW, so use a sample

Core assumption:

Changes in the sample represent changes in the universe

Estimate monthly change based on sample change

Benchmark once a year to “true” universe of 8.5+ total nonfarm establishments in US

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CES Time Series

CES produces monthly estimates for:All Employees

– Average Hourly Earnings – Average Weekly Hours – Average Weekly Earnings

Production/Non-supervisory Workers– Average Hourly Earnings – Average Weekly Hours – Average Weekly Earnings

Women Workers (national only)

CES estimates are produced for:Nation as a whole50 StatesAll Metropolitan Statistical Areas

Many states also produce estimates by county

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CES Data Items Concepts

CES is a survey of nonfarm establishments, not households, not farms.

All Employees is a count of payroll jobs. It is not a count of employed persons.

Persons holding two payroll jobs are counted twice in CES

All Employees is a count by location of the job, not residence of the employee.

Reference period: Pay period with 12th of month

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Hours & Earnings Concepts

CES hours and earnings are for production workers within an industry. (And for All Employees as well, since 2007)

AHE is a useful measure of the rate of change of wages in a given industry.

AHE is a measure of monetary compensation only. AHE is not a measure of total compensation costs.

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CES Data CollectionData are collected primarily by BLS

BLS Data Collection Centers (DCCs) In Atlanta, Kansas City, Dallas, Fort Walton Beach, Chicago

States can opt to collect data for key/sensitive reporters

Collected via a variety of methods: TDE (Touchtone Data Entry): respondents call

800# and punch in data on touchtone phone

CATI (Computer Assisted Telephone Interview): we call respondents

Mail: via a “BLS-790 shuttle form”

Electronically: Fax, FTP, diskette, website

Distribution of Sample by Collection Mode

1993

2000

Mail 87%

CATI 4%

TDE 8% Other 1%

Mail 16% CATI 5%

TDE 59%

Tape/disk 7%

FAX 7%

EDI 6%

Other 4%

CATI 25%

TDE 3%

FAX 5%

EDI 42%

Web 21%

2014

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The CES Universe

Total nonfarm establishments in the USA

Over 8.5 million establishments

Primary source of CES universe data: LDB (Longitudinal Data Base) file from the QCEW program.

CES selects its sample from the LDB

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The CES Sample

Probability sample design (completed in 2003)

Sample is drawn to represent industries in each State’s economy.

The larger the sample unit, the greater the chance of selection into the CES sample.

Smaller sample units are given larger weights than larger sample units.

The national sample is approximately 555,000 establishments (in ~145,000 UI accounts).

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CES Estimation

CES universe is split into industry-based “estimating cells” Estimating cells are based on industry (e.g. construction,

retail)

National, State, and MSAs each have their own separate estimating cell structure (and are NOT additive)

Estimates are made at the estimating cell level

CES estimation assumes that changes in the sample mirror changes in the universe If the sample employment grows by 3%,

we estimate that the universe employment grows by 3%.

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CES Benchmarking CES estimates the change each month, but

we need to calibrate the series sometime. Errors creep in when you do estimates (bias, sampling &

nonsampling error)

The “Benchmark” is done annually A benchmark is a complete count of All

Employees in each CES estimating cell.

The annual benchmark also serves as a quality check on the CES estimates.

QCEW is the primary input for the All Employee benchmark;

all other CES data types have no benchmark.

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CES Data Uses

Input to monetary policy decisions Watched by Federal Reserve when setting rates

Input to fiscal policy decisions

Estimate government revenue and spending NOTE: Revenue Departments are often more

concerned with level of employment rather than month-to-month change.

Input to other economic time series GDP, Index of Leading and Coincident

Indicators LAUS estimates Local and regional economic indicators

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CES: Major Changes

March 2006: Restructuring proposal BLS proposal was to centralize the rest of

data collection and all estimation

Resulting actions:

Centralized collectionStates retained estimation, with control totals

(mid-2009 implementation)

February 2010: Restructuring in 2011 Budget Centralization of estimation:

Implemented as of March 2011 estimation cycle

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Current Population Survey (CPS)

www.bls.gov/cps for BLS data

www.bls.census.gov/cps joint Census – BLS site

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Differences between the CPS and the other Labor Force

programs

CPS is not a Federal/State program A joint effort by BLS and Census (since 1959)

CPS provides only national totals, there are no geographic breakouts LAUS provides geographic detail of the labor force,

employment, unemployment and the unemployment rate

CPS is a household survey Household surveys are residency-based

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Highlights of CPS Methodology

Primary indicator of unemployment

Monthly survey of 60,000 households

Universe is the civilian noninstitutional population

Survey conducted in person and by telephone by 2,000 interviewers using laptop computers

Usually one respondent per household

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CPS Methodology, continued

Most questions refer to the week including the 12th of the month (reference week)

A household is surveyed for 4 months, out for 8 months, and then surveyed again for 4 months

Typically, data are released the 1st Friday of the next month, along with CES

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Limitations of CPS Data Relatively small sample limits the

reliability of detailed estimates

Self classification by respondents can lead to misclassification

The use of proxy responses also can contribute to nonsampling error (proxy: one household member providing data for another)

0.2% month to month change in theunemployment rate can be detected.

Less than that? “virtually unchanged”

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Labor Force Concepts used in theCurrent Population Survey

civilian noninstitutional population

civilian labor force

employed unemployed

not in the labor force

Do not want a job now

Want a job now

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Labor Force Concepts

Civilian Noninstitutional Population 16 years and older Not in the armed forces Not in an institution

Civilian Labor Force The “pool” of available workers

A subset of the Civilian Noninstitutional Population

All persons who are either employed or unemployed

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Employed

Employed persons are those who, during the week of the 12th:

Worked at all for at least one hour for pay or profit, OR

Self-employed, OR

Worked at least 15 hours without pay in a family business or farm, OR

Had jobs, but were temporarily absent

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The CPS concept of “employed” is broader than CES or OES

The CPS definition of “employed” includes: Farm workers Workers in private households Self employed Workers temporarily absent without pay

(LWOP) Unpaid family workers

CPS is a count of persons, whileCES, OES, and QCEW are a count of jobs

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Unemployed

The unemployed are persons who, during the reference week of the 12th:

Were not employed, Were available for work during the week, and Actively looked for work within the last 4 weeks

Also included as unemployed are persons who were waiting to be called back to a job which they had been laid off

Note: CPS does not ask about or use UI data

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Not in the Labor Force

Persons who are neither employed nor unemployed are classified as “not in the labor force”

Some examples:• Retirees• Homemakers• The ill or disabled• Marginally attached and discouraged

workers(who want a job now)

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CPS Types of Data Available

Sex, age, race, Hispanic ethnicity, education

Marital status, family type, and presence of children

Occupation, industry, and class of worker

Part-time/full-time, length of workweek, absences from work

Duration and reason for unemployment Foreign born, veteran status, disability

status Usual weekly earnings

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Major Users of CPS Data

Federal, State, and local government agencies

Businesses Labor organizations Academic researchers Media General public

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Local Area Unemployment Statistics (LAUS)

www.bls.gov/lau

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LAUS Concepts:

LAUS uses CPS concepts and definitions for employed, unemployed, and not in the labor force.

Product: Civilian Labor Force, Employment, Unemployment and Unemployment rate. For LOCAL geographies, not nation as a whole

The reference week is the week including the 12th of the month (not the pay period).

Geographic reference is by place of residence (not place of work).

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Geographic Areas

Census regions and divisions All states, D.C., and Puerto Rico Combined statistical areas Metropolitan statistical areas Metropolitan divisions Micropolitan statistical areas Small labor market areas Counties and county equivalents Cities with populations of 25,000 or more Nearly all cities and towns in New England

Approximately 7,300 areas in total

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Comparison of LAUS to CPS

LAUS Not a survey

Produces estimates for state and substate areas

Uses 3 different estimating procedures depending on geographic level

Produces no demographic or occupational data

CPS Survey of households

Produces estimates for the nation as a whole

Uses only 1 estimating procedure - household survey

Produces detailed data including demographic, and occupational data

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Comparison of LAUS to CES

LAUS Employment

By place of residence

Count of persons

Calendar week of the 12th

Include unpaid absences

No industry data

Includes ag., self-employed, private household, and unpaid family workers

CES Employment

By place of work

Count of jobs

Pay period including the 12th

Exclude unpaid absences

Detailed industry data

Limited to nonfarm wage and salary jobs

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Does drawing UI benefits = “unemployed”?Not necessarily

UI claimant …

Can be employed Benefits are limited Job leavers are ineligible Entrant and re-entrants are not eligible Some unemployed delay filing, or never

file at all

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LAUS Inputs

LAUS uses as input data from six sources:

CES employment estimates QCEW employment counts (if CES not available) Unemployment Insurance (UI) claims data Census Bureau data

- Annual and Decennial

- For population levels and agricultural employment

The CPS household survey Data from the Railroad Retirement Board

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LAUS Estimating Procedures

LAUS uses three different estimating procedures depending on the geographic areas being estimated:

1 Regression models for states

Some states model a metro area/division & respective Balance Of State (BOS)

2 Handbook method for labor market areas

3 Disaggregation for counties, cities, towns

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Why use three different estimating procedures?

Use of CPS household survey would be ideal for all estimates. But…

CPS includes only 60,000 households nationwide

Insufficient for creating reliable estimates for states or smaller geographic areas

CPS is used as one input to LAUS estimates

BLS uses three techniques for estimation

Each is the best available for the level of geographic detail being estimated

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1-Regression Models for Statewide

Employment model

− CPS− CES

Unemployment model

− CPS− UI Claims

Model Inputs:

From these 2 model outputs, the unemployment rate and the Civilian Labor Force can be derived.

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2-Handbook Method for Labor Market Areas

Why?

CPS sample simply isn’t large enough.

What?

The handbook method is simply 2 aggregations of available data items adding up to

(1) total employment and

(2) total unemployment

(Called “handbook” method because it was originally performed by paper and pencil in handbooks.)

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Handbook Method, continued

Ingredients? Employment

CES employment (adjusted for residency, multiple job holding and unpaid absences)

Self-employed, unpaid family worker, and private household employment

Agricultural employment

Unemployment UI continued claims (less claimants with earnings)

Estimates of UI claimants who have exhausted benefits

Estimate of new and re-entrant unemployed

Last step: Force additivity to statewide

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3-Disaggregation for Smaller Areas

Disaggregation breaks down Labor Market Area (LMA) estimates into its component counties, cities, and towns.

Two Disaggregation methods:– Population and claims based (preferred

method)– Census-share *

* Only three states use this (including California)

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Uses of LAUS DataKey indicator of local economic

conditions

By state and local governments for planning and budgetary purposes

Indication of need for local employment and training services and programs

Determine eligibility of state and local areas for Federal assistance programs

Input to formulae which allocate funds to local areas

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LAUS data are Politically Sensitive

LAUS data are used as an input to various allocation formulas which distribute Federal funds to local areas based on need.

The higher the unemployment rate, the bigger the slice of the pie the area gets in Federal assistance.

For this reason, LAUS data are produced using strict procedures.

Unlike CES, there is no “analyst judgment” in the production of LAUS estimates.

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LAUS data are used to allocate funds for many Federal Assistance Programs

Examples:

Agency Program Funding

ETA Worker Training $ 1.77 Billion

FEMA Food and Shelter $ 120 Million

Commerce- Public Works $ 112 Million

EDA Programs

Grand Total, All Programs: $ 114.6 Billion

ARRA: ANOTHER $144 Billion

Contact Information

Dennis ReidAssistant Regional Commissioner

San Francisco415-625-2260

reid.dennis@bls.gov