Post on 11-Jan-2016
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