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Labor Market Information Methodology and uses Part 2 Dennis Reid Bureau of Labor Statistics San Francisco Regional Office October 2014.

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Presentation on theme: "Labor Market Information Methodology and uses Part 2 Dennis Reid Bureau of Labor Statistics San Francisco Regional Office October 2014."— Presentation transcript:

1 Labor Market Information Methodology and uses Part 2 Dennis Reid Bureau of Labor Statistics San Francisco Regional Office October 2014

2 2 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

3 3 Fed/State Cooperative Programs Partnership with eight States & Guam Contract: 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

4 4 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)

5 Comparison of Labor Force and OSHS Programs QCEWCESOESCPSLAUSJOLTSSOIICFOI Data Collected by States & BLSBLSStates & BLS ROsCensus Bureau Input from CPS, CES, UI BLSStates and BLS Data Collected from Establishments Households Input from CPS, CES, UI Establishments various sources Estimate or Universe Count? UniverseEstimate Universe Frequency of Collection Quarterly for monthly data MonthlySemi-AnnualMonthly Annualon a flow basis Frequency of Publication Quarterly & Annual MonthlyAnnualMonthly 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 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 NoneWomen WorkersNone Extensive Demographic Detail None Gender, age, race/ethnicity Are Data Benchmarked? No, QCEW is a benchmark Yes, to QCEW NoYes, to CPSYes, to CESYes, to QCEW No, CFOI is a universe count Major Uses Sample frame & benchmark Economic Indicator Foreign Labor Certification, Planning training & educational programs Economic Indicator Economic Indicator, Allocation of funds Economic Indicator 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 months3 weeks States- 5 weeks; Areas- 7 weeks 4-6 weeks after reference month 10 months8 months

6 6 Current Employment Statistics (CES) www.bls.gov/ces for National data www.bls.gov/sae for State & Area data

7 7 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

8 8 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 whole 50 States All Metropolitan Statistical Areas Many states also produce estimates by county

9 9 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 12 th of month

10 10 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.

11 11 CES Data Collection Data 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

12 Distribution of Sample by Collection Mode 1993 2000 2014

13 13 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

14 14 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).

15 15 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%.

16 16 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.

17 17 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

18 18 CES: Major Changes March 2006: Restructuring proposal  BLS proposal was to centralize the rest of data collection and all estimation  Resulting actions: Centralized collection States retained estimation, with control totals (mid-2009 implementation) February 2010: Restructuring in 2011 Budget  Centralization of estimation: Implemented as of March 2011 estimation cycle

19 19 Current Population Survey (CPS) www.bls.gov/cps for BLS data www.bls.census.gov/cpsjoint Census – BLS site

20 20 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

21 21 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

22 22 CPS Methodology, continued Most questions refer to the week including the 12 th 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 1 st Friday of the next month, along with CES

23 23 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 the unemployment rate can be detected. Less than that? “virtually unchanged”

24 24 Labor Force Concepts used in the Current Population Survey civilian noninstitutional population civilian labor force employedunemployed not in the labor force Do not want a job now Want a job now

25 25 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

26 26 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

27 27 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, while CES, OES, and QCEW are a count of jobs

28 28 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

29 29 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)

30 30 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

31 31 Major Users of CPS Data Federal, State, and local government agencies Businesses Labor organizations Academic researchers Media General public

32 32 Local Area Unemployment Statistics (LAUS) www.bls.gov/lau

33 33 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).

34 34 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

35 35 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

36 36 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

37 37 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

38 38 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

39 39 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

40 40 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

41 41 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.

42 42 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.)

43 43 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

44 44 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)

45 45 Uses of LAUS Data Key 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

46 46 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.

47 47 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

48 Contact Information Dennis Reid Assistant Regional Commissioner San Francisco 415-625-2260 reid.dennis@bls.gov


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