Please sit wherever you would like

1
Welcome

• Please sit wherever you would like

2
Word on the street is you been askin a lotta
questions about LMI
3
LMI.. What you should know

• Presented by.
• Bill McNeece
• MS Dept of Employment Security

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LMI

• What is it?
• Where does it come from?
• How can you use it?

5
One Popular Opinion
L
argely
M
ade Up
I
nformation
6
But, seriously, folks
L
abor
What is it Really?
M
arket
I
nformation
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The Textbook Definition

• A dynamic and systematic approach to workforce
  data designed to meet the changing needs of our
  customers.

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In Laymans Terms

• Or, to put it more simply
• Basically, its any data or analysis that relates
  to the workforce.

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LMI ????????????
WHO NEEDS 'IT ? ! ?
Unfortunately, you do
LMI data is the gas that fuels the ALMIS Data
Base engine
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Whats our goal today?

• To help YOU.
• Navigate thru the LMI Lingo
• Understand the Data Sources
• Avoid Heartburn and Keep Your
  Sanity

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Your Training Modules Today

• Learning the Lingo
• Who Makes this Stuff Up?
• Avoiding Heartburn

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Ready to get started?

• Lets take a look at the first module

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Feel Bombarded with Acronyms?
Americans DO love their acronyms!
But sometimes it makes things hard to understand
BLS
EIEIO
ALMIS
LMI
CPI
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Did you know?

• Acronym is actually an ACRONYM itself!
• Abbreviations
• Created
• Routinely
• Once every
• New
• York
• Minute

15
Before we get very far

• We need to wade through some Alphabet Soup so you
  wont think Im speaking a foreign language
• These are some common acronyms tossed around in
  LMI circles

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Alphabet Soup
BEA Bureau of Economic Analysis BLS Bureau of
Labor Statistics CPI Consumer Price Index CES
Current Employment Statistics
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Alphabet Soup
CPS Current Population Survey ECI Employer
Cost Index ETA Employment Training
Administration
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Alphabet Soup
LAUS Local Area Unemployment Statistics LMA
Labor Market Area MLS Mass Layoff Statistics MSA
Metropolitan Statistical Area NAICS North
American Industry
Classification System
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Alphabet Soup
OES Occupational Employment Statistics PPI
Producers Price Index SIC Standard Industry
Classification SOC Standard Occupational
Classification QCEW Quarterly Census of
Employment
Wages (a.k.a ES 202)
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Alphabet Soup
Any Questions?
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Before we move on, lets take a short break
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Picking up where we left off

• Lets take a look at the next module

A
B
's
C
Of LMI
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LMI Lingo

• Must crawl before we walk
• Well start with some basic terms and concepts
• In other words, all you wanted to know but were
  afraid to ask

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Labor Force Terms Concepts

• Employed
• Worked at least one hour for pay
• During the week that includes the 12th
• Unemployed
• No job attachment
• Available for work actively seeking it
• Can be experienced or a new or re-entrant

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Covered Employment

• This employment tallies workers whose wages have
  been covered for UI purposes (i.e., the
  employer paid unemployment insurance on the wages
  paid to the individual)
• Used only in QCEW data

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EmploymentPlace of work

• An estimate or count of employment based on the
  location of the job regardless of the workers
  residence
• Also called Nonag Wage and Salary or
• Nonfarm Employment
• This counts jobs, not people
• Used in QCEW, OES and CES data

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EmploymentPlace of Residence

• An estimate of employment based on where the
  employee lives, rather than where they work
• This is a count of people not jobs
• Used in calculating the labor force
• Used only in LAUS data

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Labor Force Terms Concepts

• Civilian Labor Force
• 16 years old
• Employed Unemployed
• Does NOT include military personnel

• Unemployment rate
• Unemployed Labor Force
• Expressed as

• Labor Force Participation rate
• Labor Force Working Age Population

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Labor Force Terms Concepts

• Discouraged Workers
• Harder to define and sometimes undercounted.
• Generally are on long-term layoff with no
  immediate prospects.

• Underemployed
• Also hard to define and count.
• Basically can be anyone working below their skill
  level.
• Might be underemployed by choice.

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Labor Force Terms Concepts

• Labor Market Area
• Groups of counties that encompass the county of
  residence and the county of work.

• Defined by
• Commuting patterns
• The behavior of individuals included in
  American Community Survey, Census and UI claims
  data when compared to other data.

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Covered Wages

• This pertains to the actual wages earned by
  persons working for a covered employer
• In other words, someone for whom unemployment tax
  has been paid
• Used only in QCEW data

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Average Weekly Wages

• A simple average calculated by dividing the total
  wages paid by the number of weeks in the time
  period, then dividing again by the number of
  workers reported
• Found in CES and QCEW data

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Benchmark

• Establishing a new reference point, from which
  estimates are calculated and/or revised, based on
  last known data.
• Very similar to the census process
• Only LAUS CES do this

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Coding Systems

• Why code data?
• Why revise coding structures?
• Types of coding
• Geography
• Industry
• Occupation

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Objectives of Coding Systems

• Often designed to meet specific labor program
  needs
• Ideally, a single system would meet all
  programmatic needs
• Updating should be timely and cost-effective

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Geographic Coding Systems

• Only one major system in common usage
• FIPS Federal Information Processing System
• Developed by U.S. Office of Management and Budget
  (OMB)
• Commonly used by almost all federal and local
  agencies
• Consists of codes for states, MSAs, counties and
  cities, townships, etc.
• Some GIS software applications use FIPS

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Industry Coding Systems

• Types
• Standard Industrial Classification (SIC)
• North American Industrial Classification System
  (NAICS)

• Shifting from SIC to NAICS
• Conversion now complete
• Benefits
• Program impacts

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WHY NAICS?

• Six-digit system, instead of four
• Instead of 10 major industry groups, there are 20
  industrial sectors.
• More consistent with other international systems
  and other classification systems used by BEA.

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Occupational Coding Systems

• DOT Dictionary of Occupational Titles
• Phased out in 2002 2003
• OES Occupational Employment Statistics
• SOC Standard Occupational Code
• ONET Occupational Information Network

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ONet Crosswalks

• AIM Apprenticeship Information Manager
• 1990 Census occupations
• CIP Classification of Instructional Programs
• DOT Dictionary of Occupational Titles
• GOE Guide for Occupational Exploration
• MOC Military Occupation Codes
• Office of Personnel Management occupations
• SOC Standard Occupational Classification

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LMI Lingo
Any Questions?
42
Next on our agenda is

Who makes this stuff up?
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Just where do the numbers come from?
Mostly from BLS programs
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Just who or what IS BLS?

• Contrary to popular opinion, they are NOT the
  Bureau of Lying Sapsuckers!
• In reality, they are the BUREAU OF LABOR
  STATISTICS, an arm of the US Department of Labor

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As states, why are we involved with a Federal
agency?

• They operate what is known as the Federal/State
  Cooperative Programs
• Under these, they provide the funding for our
  base statistical programs

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Historical Background

• BLS has been around in one form or another for
  over a hundred years.
• However, they only took control over the LMI
  programs in the mid-1970s
• They provide both funding and technical support

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LMI Produces lots of different
stuff

• Does BLS control ALL our LMI programs?
• Not in most states. They are only responsible
  for FIVE basic statistical programs. Anything
  else is funded and controlled by some other entity

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Which five does BLS control?

• QCEW
• CES
• LAUS
• OES
• MLS

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There you go with the acronyms again!

• In plain English, tell me what those stand for
• And while youre at it, tell me a little bit
  about each of them

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Okay, lets begin with QCEW

• Its official name is the Quarterly Census of
  Employment Wages
• Its commonly called ES 202 because the original
  report it was required to produce was Employment
  Security Report Number 202

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What exactly does the QCEW program produce?

• Detailed quarterly employment and payroll
  information for all employers covered under UI
  law.
• Annual information on changes in industry codes
  that occur during the year

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Data Sources for QCEW

• UI quarterly contribution reports
• UCFE federal agency employment reports
• Comes to ALMIS DB via EQUI report

• Supplementary employer surveys by state LMI
  offices
• Multiple establishment detail (MWR)
• Industrial coding (annual refile survey)
• Follow-ups triggered by edits

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How does QCEW differ from other programs?

• Unlike LAUS, QCEW counts JOBS not PEOPLE
• Jobs are counted at the work site
• Its the only program that lists total wages paid

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Uses of QCEW Data

• Employment benchmark for all BLS federal/state
  employer survey programs CES, OES OSHA
• Critical for Bureau of Economic Analysis
• Personal income
• State and national domestic product

• Local planning
• Only consistent source of county employment and
  wages by industry
• Any employment analysis requiring detailed data

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QCEW Limitations Changes

• Some employment for large firms may be reported
  in the wrong areas (MWRs)
• Some firms report total number of employees in a
  quarter as employment for each month
• QCEW is not a time series
• No wedging of changes by industry or area from
• Annual refile survey
• Changes in multi-establishment reporting
• Shift to NAICS Break in series

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QCEW Chronology

• Data files produced QUARTERLY
• Once completed they are NOT revised
• Changes in industry designation only done ANNUALLY

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QCEW
Any Questions?
58
Next on the agenda
The CES Program
Which stands for Current Employment Statistics
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What is it?

• The Current Employment Statistics program is a
  monthly employer survey conducted by the states
  in cooperation with BLS.
• The survey provides a sample from which estimates
  of employment, hours and earnings by industry
  group are calculated

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Data Sources for CES

• Begins with covered employment from QCEW
  supplemented with non-covered adjustments

• The monthly employer survey is used to estimate
  current monthly levels of employment by industry

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What does it produce?

• Today, the CES program produces employment, hours
  and earnings estimates for all states and MSAs.
• It is the largest survey of its kind, with a
  nationwide sample of over 400,000 firms!

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Coverage Differences Between CES QCEW

• The following categories of workers are
  included in CES estimates but not in QCEW
• Full commission salespersons
• Elected and appointed government officials
• Teachers in summer months who are paid on
  12-month contracts

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CES Limitations Changes

• Sample size limits state area industry detail
• Sum of states employment does not equal national
  total
• Estimates for many sub-state areas are not funded
• Though accuracy exceeds that of other economic
  data, benchmark revisions still cause criticism
• Earnings are for production workers not
  available for many state industries

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CES Chronology

• Data produced MONTHLY
• Current month is PRELIMINARY, previous month is
  REVISED
• Entire calendar year data set is benchmarked and
  revised ANNUALLY
• Benchmark revisions include prior year, also
• Hours and earnings data are revised monthly but
  NOT BENCHMARKED

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Current Employment Statistics
Any Questions?
66
Moving right along

• We come to

The OES Program
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Occupational Employment Statistics (OES)
The OES Program

• An annual employer survey which produces
  employment and wage-rate estimates by occupation
  and industry for states and areas
• Program began in 1971 in 15 states with BLS and
  ETA sharing responsibility with the states
• When BLS took total federal responsibility for
  the program, all 50 states began to participate

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OES
The OES Program

• In 1996, the following changes were made
• Sample increased to be the largest of any
  employer survey
• Wage rates were added for all states sub-state
  areas
• All industries surveyed each year, rather than
  every 3rd year

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OES Staffing Estimates

• Employment by occupation is tallied for each
  industry sector

• Staffing ratios are developed representing each
  occupations share of each industry sectors
  employment

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OES Wage Rate Estimates

• Data tallied by wage ranges
• Wage-rate averages generated using weighted
  system of averaging
• Prior-year data aged using the Employer Cost
  Index

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OES Limitations

• Since it is voluntary, low response rates can
  make it less reliable in some industry sectors
• Estimates for sub-state areas dependent on
  sample size and response rates
• Wages are tallied by range
• Sample size limits state area industry detail
  in many cases

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Recent Program Changes

• Conversion to new SOC codes
• Change in sampling frequency of certainty units
  (large employers)

• Cognitive analysis of survey forms, to assist in
  edits
• Asking employers for data in other quarters
  (split survey)

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OES Chronology

• Surveys done in Spring and Fall
• Data processed all year long

• New estimates released annually
• Data do not undergo revisions or benchmarking
  once released

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Occupational Employment Statistics
Any Questions?
75
State and Area Occupational Projections

• A very important byproduct of the OES data
• NOT a BLS funded project
• Money comes from Employment Training
  Administrationanother branch of the US
  Department of Labor

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State Area Occupational Projections

• Produces both the INDPRJ and IOMATRIX data sets
• Short-term up to 2 years
• Long-term roughly 10 years

• In some states unit may also be responsible for
  occupational wage data
• Substate areas vary widely from state to state

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Projections Chronology

• New data sets now released twice a year
• Short term and long term projections not
  necessarily released at same time

• Release times vary widely from state to state
• Data are not subject to benchmark revisions

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The fourth BLS program is
LAUS
which stands for ________________________________
Local Area Unemployment Statistics
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Just what is LAUS?

• The name can be misleading since it deals with
  more than just unemployment data, such as the
  often-quoted unemployment rate.

• The Local Area Unemployment Statistics program is
  a multi-layered process that produces labor
  force, employed and unemployed estimates by place
  of residence

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What does the LAUS program produce?

• Estimates of total civilian labor force,
  employed, unemployed and unemployment rate for
  all states, MSAs, counties, and other similar
  areas, adjusted to place of residence

81
Betcha didnt know

• Estimation method varies depending on the type of
  geography
• U.S. data comes directly from the monthly Current
  Population Survey
• Statewide data (since 1986) comes from a
  regression model developed by BLS
• County level data are apportioned out of the
  statewide data using a handbook method

82
Why do methods vary?

• CPS allows for more detailed information at the
  national level, such as data by gender, race, age
  group, etc.
• CPS was used for larger states at one time, but
  trend was erratic and regression model was
  instituted in late 1980s
• Regression models are not reliable for smaller
  areas, such as counties and cities

83
Sub-state LAUS Estimates

• Handbook method used to apportion out county
  level estimates from statewide totals
• Population-claims method used where possible for
  estimates of larger cities
• Census-share method used for smaller cities and
  sub-county estimates when claims data are not
  available

84
How do LAUS estimates differ from others?

• Includes agricultural workers, self employed and
  others excluded by CES QCEW
• CES QCEW estimate JOBS at work site LAUS
  estimates PEOPLE at place of residence

85
LAUS Limitations

• Limited statistical measures of reliability
• Handbook methodology assumes local areas follow
  national trends
• Estimates for employment are probably more
  accurate than for unemployment
• No detailed data, such as gender, age, etc.

86
Recent Program Changes

• Major changes in methodology
• Many cities and MSAs altered or added
• Many areas changed significantly

• Error in BLS provided software has led to delays
• Break in series between 1999 and 2000 due to
  changes

87
LAUS Chronology

• Data produced monthly
• Current month is PRELIMINARY, previous month
  is REVISED
• Entire calendar year data set is benchmarked
  and revised ANNUALLY
• Benchmark revisions may include prior years, also

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Local Area Unemployment Statistics
Any Questions?
89
Last
(but not necessarily least)
we come to
the MLS Program
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Mass Layoff Statistics

• Began life as PMLPC in the early 80s
• Intent was to track serious layoffs and closings
  by industry using UI claims data
• Not very useful for Rapid Response
• Good post-occurrence analytical tool
• Many states dont have enough activity to publish
  data

91
BLS Programs
Any Questions?
92
Okay..That covers the BLS generated stuff..
What about all the other data sets in the ALMIS
DB?
93
Other data sets

• Occupational licensing data Sources vary by
  state
• Census data (www.census.gov)
• Most can be downloaded in Excel format
• State data center can be helpful
• Training provider and completer data Sources
  vary by state

94
Other data sets

• Income data downloadable from BEA web site.
• Crosswalk tables Direct from National Crosswalk
  Data Center in Iowa
• Employer database provided via contract with
  InfoUSA updates automatic
• URL links to other states

95
Okay I dig the data now, but how do I keep it
all straight without going postal and doing
something crazy?
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Fair question...
and it leads to our last module..
Avoiding Heartburn
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Top Three Tips

1. Get a handle on Benchmarking procedures
2. Understand the data flow
3. Understand the BLS vs ETA issues

98
To elaborate...

• Know the timing of data sets from BLS
• Know who provides, when and in what format
• Dont be blind-sided by revisions

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Benchmarking

• Know the time frame for benchmarking for CES and
  LAUS
• Understand the scope
• Double check data to insure it is the most
  current benchmark

100
BLS vs ETA

• Realize they dont like each other very much
• Understand the turf wars
• Dont expect them to cooperate and make your life
  easier

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Almost done
Any Questions?
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Th-th-th-thats all folks!
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Applause !!
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For further assistance contact
Bill McNeece Special Projects LMI Department
- MS Department of
Employment Security Phone 601
321 6249 E-mail bmcneece_at_mdes.ms.gov NO EXTRA
CHARGE !!