This area provides a long description of the following programs and data elements. Links are also provided for those who would like shorter more concise descriptions.
Access Data Query
These data present 2001-current employment and wages information as defined in the North American Industry Classification System (NAICS). The data pertain to
workers covered by Wisconsin Unemployment Insurance (UI) laws and Federal civilian workers covered by the Unemployment Compensation for Federal Employees
(UCFE) program. The information for both private and public sector workers are reported to the Bureau of Labor Statistics (BLS) by the Department of Workforce
Development (DWD) as part of the Quarterly Census of Employment and Wages, or ES-202, program.
Wisconsin employers in private industry provide DWD with quarterly tax reports on monthly employment, quarterly total and taxable wages, and contributions for
wage and salaried employees. The Federal Government submits similar reports of monthly employment and quarterly wages for civilian employees, and by State and
local governments. Covered employment reported by these sources provides a virtual census of payroll employment—about 155,000 business establishments and
2.7 million employees. The principal exclusions from UI and UCFE coverage are cited in "Characteristics and Uses of the Data," below.
Quarterly data are presented for the state and counties by ownership and industry and include the Number of units, employment by month, total wages, and
average weekly wage. Annual data are forthcoming.
Characteristics of the Data
These data are compiled as part of the operation of the Quarterly Census of Employment and Wages, or ES-202, program. The data are derived from the
quarterly tax reports submitted to DWD by Wisconsin employers subject to State unemployment insurance (UI) laws and from Federal agencies subject to the
Unemployment Compensation for Federal Employees (UCFE) program. Each quarter, DWD edits, analyzes, and processes the data and sends the information to BLS in
Unemployment Insurance Laws and Coverage
State unemployment insurance programs, the primary source of ES-202 covered employment and wages data, have relatively comprehensive coverage in the United
States labor force. Approximately 96 percent of the wage and salary civilian labor force and 98 percent of nonagricultural employment are covered by State
UI laws, and so are reflected in ES-202 data.
States establish their own unemployment insurance coverage provisions, generally in accordance with the Federal Unemployment Tax Act (FUTA). The FUTA
establishes minimum coverage standards that States must meet to have an approved UI program. FUTA provisions determine which employers are subject to
Federal unemployment insurance taxes and designate certain types of services that must be covered under State UI laws to meet Federal approval. Specific
coverage provisions of State UI laws have been influenced by the FUTA through tax incentives. The incentives allow employers who pay UI contributions under
federally approved State unemployment insurance law to credit their State contributions against a specified percentage of the Federal tax.
Coverage exclusions in the FUTA, however, do not preclude a State from covering the excluded class or category of workers under their own State laws. Many
States have chosen to expand their coverage provisions beyond the FUTA minimum standards in certain areas. A summary of common coverage exclusions is provided
below. Detailed UI coverage information can be found in the Comparison of State Unemployment Insurance Laws
maintained by the U.S. Department of Labor's Employment and Training Administration.
Both Federal and State UI coverage laws are subject to change at any time when existing laws are amended through the legislative process or reinterpreted
through judicial action.
Common Exclusions from UI Coverage
- As defined by Federal and State UI laws, employment is the hiring of workers by others for wages. Self-employed individuals are therefore excluded from
coverage. Incorporated self-employed persons, however, are covered because corporations are recognized as separate legal entities from the individual,
thereby allowing the individual to be an employee of his/her own corporation.
- Some coverage exclusions result from the scope in which an "employer" is defined. The FUTA defines an employer generally as one who has a quarterly
payroll of $1500 in the calendar or preceding year or who has one worker for 20 weeks. Thirty-three States have adopted this definition. Ten States have the
broadest possible coverage by defining an employer as one who has any covered service in their employ. The other States have requirements of fewer than 20
weeks or payrolls other than $1500 in a calendar quarter.
The definition of employer differs for agriculture, domestic service in households, and nonprofit organizations, as noted below.
Agriculture – The FUTA designates coverage of agricultural employers having ten
or more workers in twenty weeks, or a payroll of $20,000 or more in any
quarter. Farm owners/operators are excluded from coverage in all States.
Domestic Service – The FUTA designates coverage of domestic help in private households, social clubs, and college fraternities and sororities that pay
wages of $1000 or more in a quarter.
The FUTA and State UI laws also specify certain categories of employment as not covered. States can choose to extend coverage to a category that is excluded
under the FUTA. Common exclusions across States are noted below.
Minor children employed by their parents, or parents employed by their children, are excluded from coverage in all States.
Railroad workers are excluded from coverage in all States. A special Federal unemployment insurance program administered by the Railroad Retirement Board covers them.
- U.S. Armed Forces military personnel are excluded in all States. They are covered under a separate Federal program, Unemployment Compensation for
Ex-Servicemen (known as the UCX program).
- State and local government elected officials; members of the judiciary, State national and air national guardsmen, temporary emergency employees, and policy
and advisory positions are excluded in most States.
- College and university students employed by the school at which they are enrolled, such as work-study students, are excluded from coverage in all
States. Most States also exclude student nurses and medical interns employed by hospitals as part of their professional training program.
Insurance and real estate agents paid only by commission are excluded from coverage in most States.
Employment and wage data under the ES-202 program have been classified by industry since 1938. An industrial code is assigned to each establishment by
the State agency, based on a description provided by the employer on a questionnaire. If a private or government employer conducts different
activities at various establishments or installations, separate industrial codes are assigned, to the extent possible, to each establishment.
Standard Industrial Classification System (SIC)
Historic data files are available from 1975-2000 in a 2,3,or 4-digit format by county. Due to the advent of NAICS, no SIC based data are available after 2000.
Hardcopy data are available. Please contact Deb Holt if you need assistance.
North American Industry Classification System (NAICS)
The year 2000 data will be the last from the Quarterly Census of Employment and Wages (ES-202) program using the 1987 Standard Industrial Classification (SIC)
system. Beginning with the release of data for 2001, the program will switch to the 2002 version of the North American Industry Classification System (NAICS)
as the basis for the assignment and tabulation of economic data by industry. NAICS is the product of a cooperative effort on the part of the statistical
agencies of the United States, Canada, and Mexico. Due to differences in NAICS and SIC structures, data for 2001 will not be comparable to the
SIC-based data for earlier years.
NAICS uses a production-oriented approach to categorize economic units. Units with similar production processes are classified in the same industry. NAICS
focuses on how products and services are created, as opposed to the SIC focus on what is produced. This approach yields significantly different
industry groupings than those produced by the SIC approach.
Data users will be able to work with new NAICS industrial groupings that better reflect the workings of the U.S. economy. For example, a new industry sector
called Information brings together units that turn information into a commodity with units that distribute the commodity and units that provide information
services. Information's major components are publishing, broadcasting, telecommunications, information services, and data processing. Under the SIC
system, these units were spread across the manufacturing, communications, business services, and amusement services groups. Another new sector of
interest is Professional, Scientific, and Technical Services. This sector is comprised of establishments engaged in activities where human capital is the
More information about NAICS is on-line at http://www.census.gov/epcd/www/naics.html
Verification of Account Information
To ensure the highest possible quality of data, DWD verifies and updates, if necessary, the NAICS, location, and ownership codes of all establishments on a
three-year cycle. Government units in the public administration industry division, however, are verified less frequently. Each year, changes in
establishment classification codes resulting from the verification process are introduced with the data reported for the first quarter. Thus, some data may
not be strictly comparable with those for earlier years.
In general, ES-202 monthly employment data represent the number of covered workers who worked during, or received pay for, the pay period that included
the 12th day of the month. Covered private industry employment includes most corporate officials, executives, supervisory personnel, professionals, clerical
workers, wage earners, piece workers, and part-time workers. It excludes proprietors, the self-employed, unpaid family members, and certain farm and
Workers on paid sick leave, paid holiday, paid vacation, and the like, are included. Workers on the payroll of more than one firm during the period are
counted by each UI subject employer if they meet the employment definition noted above. Workers are counted even though, in the latter months of the year,
their wages may not be subject to unemployment insurance tax. The employment count excludes workers who earned no wages during the entire applicable pay
period because of work stoppages, temporary layoffs, illness, or unpaid vacations.
Employment data reported for Federal civilian employees are a by-product of the operations of DWD in administering the provisions of Title XV of the Social
Security Act -- the program of Unemployment Compensation for Federal Employees. Federal employment data are based on reports of monthly employment and
quarterly wages submitted each quarter to DWD for all Federal installations with employees covered by the Act, except for certain national security
agencies, which are omitted for security reasons.
Employment for all Federal agencies, except the Department of Defense, for any given month is based on the number of persons who worked during or received pay
for the pay period which included the 12th of the month. Installations of the Department of Defense include persons employed on the last workday of the month
plus all intermittent employees -- occasional workers who were employed at any time during the month.
An establishment is an economic unit, such as a farm, mine, factory, or store that produces goods or provides services. It is typically at a single physical
location and engaged in one, or predominantly one, type of economic activity for which a single industrial classification may be applied. Occasionally, a
single physical location encompasses two or more distinct and significant activities. Each activity should be reported as a separate establishment if
separate records are kept and the various activities are classified under different six-digit NAICS codes.
Most employers have only one establishment; thus, the establishment is the predominant reporting unit for employment and wages data. Most employers who
operate more than one establishment in Wisconsin file a Multiple Worksite Report (MWR) each quarter, in addition to their quarterly UI report. The MWR
form is used to collect separate employment and wage data for each of the employer's establishments, which are not detailed on the UI report. Some very
small multi-establishment employers do not file a MWR. When the total employment in an employer's secondary establishments (all establishments other
than the largest) is 10 or fewer, the employer generally will file a consolidated report for all establishments. Also, some employers either cannot
or will not report at the establishment level and thus aggregate establishments into one consolidated unit, or possibly several units, though not at the
For government, the reporting unit is the installation: a single location at which a department, agency, or other government body has civilian employees.
Federal agencies follow slightly different criteria than do private employers when breaking down their reports by installation. They are permitted to combine
as a single statewide unit (1) all installations with 10 workers or fewer and (2) all installations that have a combined total in the State of fewer than 50
workers. Also, when there are fewer than 25 workers in all secondary installations in a State, the secondary installations may be combined and
reported with the major installation. Lastly, if a Federal agency has fewer than five employees in a State, the agency headquarters office (regional
office, district office) serving each State may consolidate the employment and wages data for that State with the data reported to the State in which the
headquarters is located. As a result of these reporting rules, the number of reporting units is always larger than the number of employers (or government
agencies) but smaller than the number of actual establishments (or installations).
Total Wages. Total wages (sometimes called wages or gross wages) for a quarter are the total amount of wages paid or payable
(depending on the wording of the State law) to covered workers for services performed during the quarter, on all the payrolls of whatever type during the
quarter. Bonuses paid are included in the payroll figures. Also included, when furnished with the job, is the cash value of such items as meals, lodging, tips
and other gratuities, to the extent that State laws and regulations provide. Total wages include both taxable and nontaxable wages. Both taxable and
reimbursing subject employers report total wages.
In accordance with policy, data provided to DWD in confidence are not published and are used only for specified statistical purposes. DWD withholds publication
of UI-covered employment and wage data for any industry level when necessary to protect the identity of cooperating employers.
To reduce the effect of data excluded because of late reporting by covered private and government employers, DWD imputes employment and wages for such
employers and includes them in each quarterly report. Corrections to data that may be entered after a report is filed will include replacement of imputations
with reported data to the extent possible. Imputations are calculated at the individual establishment level, normally using historical data reported by the
employer. Sometimes, trends reported by employers in the same industry or information obtained from other sources also are used. If a report remains
delinquent for more than one quarter and research shows that it is still active, the establishment will again be imputed.
Comparison of ES-202 Covered Employment Data With Other Series
The Quarterly Census of Employment and Wage data (ES-202) are available on this website at Employment by Industry Data.
Current Employment Statistics program. BLS and DWD cooperate in the operation of the Current Employment Statistics (CES) program. In this
program, the DWD is responsible for preparing current employment estimates for Wisconsin and its metropolitan labor market areas, while BLS is responsible for
monthly employment estimates for the nation. National estimates are derived from an employer survey of approximately 300,000 nonfarm establishments
nationwide, selected primarily from the ES-202 administrative records of UI-covered employers. The National and State industry CES estimates are then
benchmarked annually to the ES-202 covered employment data. Wisconsin CES estimates of Employment by Industry
are available on this website. Supplemental sources are used in benchmarking industries with non-covered workers.
Differences Between the ES-202 data and the Official CES Estimates include:
Most notable is that the CES data are derived from a survey of nonagricultural establishments, while the ES-202 data are a virtual censusof these establishments.
- The hours and earnings statistics compiled by CES are for production or nonsupervisory workers only. Other minor series published include indexes of
aggregate weekly hours, indexes of aggregate weekly payrolls, average hourly earnings excluding overtime, indexes of employment diffusion, and real average
hourly and average weekly earnings.
- CES data exclude members of the armed forces, the self-employed, proprietors, domestic workers and unpaid family workers. The ES-202 program also has the
same exclusions; but in addition, excludes railroad workers covered by the railroad unemployment insurance system, student workers, and employees of some
small nonprofit organizations. The incorporated self-employed are covered under the ES-202 program, but not in the CES. The ES-202 program also provides
partial information on agricultural industries and employees in private households not available from CES.
Payroll - Under the CES program, payroll is reported for production or nonsupervisory workers who receive pay for any part of the pay period
that includes the 12th of the month. The payroll is reported before deductions. It includes pay for holidays, vacation, sick time, and
overtime. It does not include bonuses (unless earned regularly), retroactive pay, tips, or the cash value of meals, lodging or other payments in
kind. In contrast, the ES-202 program collects compensation for all employeesin the form of wages. Wages are total compensation paid during the calendar
quarter, regardless of when services are performed. The wages include pay for holidays, vacation, sick time, and overtime. Wages include the types of compensation that CES
excludes; namely, all bonuses, stock options, tips, and the cash value of meals and lodging.
- Hours - CES collects the number of hours paid for during the pay period including the 12th of the month. Included are hours paid for leave time and overtime.
ES-202 does not collect any data on hours.
- Employment - CES employment includes workers who worked during, or received pay, for the pay period including the 12th of the month. The ES-202 employment
concept is the same, except ES-202 only collects data on workers covered by UI and UCFE, while CES data include adjustments for noncovered workers.
County Business Patterns. Covered employment data collected through the ES-202 program differ from employment data published in the Census Bureau's County
Business Patterns (CBP) in the following major areas:
- CBP data exclude administrative and auxiliary establishments from "operating" establishment data and include these data at the industry division level only.
ES-202 covered employment, on the other hand, includes data for these establishments at 3 or 4-digit NAICS level.
- CBP excludes agricultural production workers and household workers, some of whom are included in ES-202 covered employment data. CBP also excludes
government installations, all of which are included in ES-202 covered employment.
- Every 5 years, data are collected for all multi-establishment firms within the scope of business and economic censuses and included in the CBP for that year.
Annual updates for multi-establishment firms are obtained from the sample selected for the Company Organization Survey, and data for nonsample
multi-establishment firms are estimated. Annual updates for single establishment firms come from the Internal Revenue Service and the Social
Security Administration. ES-202 covered employment, on the other hand, includes establishment data collected from all active firms, single or
multi-establishment, each quarter.
Uses of the Data
The ES-202 covered employment and wages data are the most complete universe of monthly employment and quarterly wage information by detailed industry at the
national, State, and county levels. They have broad economic significance in evaluating labor market trends and major industry developments, in time series
analyses, and in making industry comparisons.
For example, the ES-202 program outputs are instrumental in determining Federal allocations of program grants to State and local governments. Furthermore,
these outputs serve as the basic source of benchmark information for employment by industry and employment by size of establishment in the Current Employment
Statistics (CES) program, the Occupational Employment Statistics (OES) program, and the Occupational Safety and Health (OSH) Statistics program. The Bureau of
Economic Analysis (BEA) of the Department of Commerce uses ES-202 wage data as a base for estimating a large part of the wage and salary component of personal
income accounts. The Social Security Administration and State governments also use ES-202 data in updating economic assumptions and forecasting trends in
their taxable wage base. Business and public and private research organizations find the ES-202 program one of the best sources available of detailed
employment and wage statistics.
The ES-202 program produces data necessary to both the Employment and Training Administration (ETA) and the various State Employment Security Agencies in
administering the employment security program. The data accurately reflect the extent of coverage of the State unemployment laws and are used to measure:
- UI revenues
- National, State, and local area employment
- Total and taxable wage trends
For specific examples of who uses the ES-202 data and for what purpose, refer to
the following table.
Bureau of Economic Analysis
(National Income and Product Accounts)
County Personal and Per Capita Income
Bureau of the Census
Possible Future Sampling
Employment and Training Administration
Actuarial and Trust Fund Analysis
Insured Unemployment Rate
Extended Benefit Trigger
BLS Directly Collected Surveys
Producer Price Index Sampling
Occupational Safety and Health Statistics Program
Sampling and Benchmarking
Office of Employment and Unemployment Statistics (OEUS) Programs
CES Benchmarking and Estimation Research
Local Area Unemployment Statistics (LAUS) Program's Small Area Employment
OES Sampling and Benchmarking
JOLTS Sampling and Benchmarking
ES-202 Program Office
Publication and Press Releases
Birth/Death and Gross Flow Studies
Other Longitudinal Analysis
Wage Survey Sampling
Wisconsin Employment Security Units
Job Service Sampling for Audits
Wisconsin UI Unit
Computation of General UI Tax Rates
Setting UI Tax Rates for New Employers by Industry
Determination of Maximum Weekly Benefit Amounts
Other State Government
Revenue Department Budget Modeling
Regulatory Use (e.g., Survey Employers by industry)
Measuring Demand for Transportation
Local Economic Planners
Forecasting Demand for Schools, Roads, etc.
Private Sector Planning
Economic Forecasting by Banks
Utilities Measuring Demand by Industry
Insurance Companies Setting Rates by Industry
Econometric Modeling and Forecasting
Articles and Publications
ES-202 data are used by businesses and by public and private research organizations as one of the best sources of detailed employment and wage
statistics for economic forecasting, industry and regional analysis, impact studies, and other uses.
The ES-202 data also are important for a variety of other BLS programs. The Unemployment Insurance Address File, created from ES-202 administrative records
of UI-covered employers, serves as a sampling frame for BLS establishment-based surveys such as the National Compensation Survey, the
Current Employment Statistics program, and the Occupational Employment
Statistics Survey. The data also serve, for example, as the basic source of benchmark information for employment by industry and by
size of establishment in the Current Employment Statistics program, the Occupational Safety and Health Statistics survey, and the Occupational
Employment Statistics Survey.
Custom Tabulations and Confidential Data Requests
When the published employment by industry data do not provide the needed industry nor geographic detail, customers can contact LMI to request a custom
tabulation for detailed geographic areas for economic development and local labor market research. The source for these custom data tabulations is the
Quarterly Census of Employment and Wage program, commonly called the "ES 202". In this program, the DWD collects information from employers each quarter on
their employment, wages, and taxable contributions. For more information, see the
Custom Tabulations and Confidential Data Requests fact sheet.
Content Reviewed: May 2013
Contact: Deb Holt - (608) 266-5321
Access Data Query
The Current Employment Statistics (CES) Survey is a monthly survey of business establishments which provides estimates of employment, hours, and earnings data
by industry for the nation as a whole, all states, and most major metropolitan areas since 1939. The CES survey is a federal-state cooperative endeavor in
which State employment security agencies prepare the data using concepts, definitions, and technical procedures prescribed by the Bureau of Labor
Statistics. In Wisconsin, the cooperating agency is the Bureau of Workforce Information in the Department of Workforce Development.
The CES program provides the most up-to-date picture of employment, hours worked, and earnings by location and industry. This program has evolved from
some of the earliest efforts in the United States to obtain monthly estimates of employment and unemployment. These data not only give a snapshot of the
current employment situation but also, over time, describe cycles of economic expansion and recession.
CES estimates are among the earliest economic information available to analyze current economic conditions. Because of this, CES estimates are heavily used in
both the private and public sector. Below is a short list of some of the uses for CES estimates:
To guide decisions on plant location, sales, and purchases;
To compare your business and the industry or economy as a whole;
To negotiate labor contracts based upon industry or area hourly earnings and weekly hours series;
To determine the employment base of states and areas for bond ratings;
To detect and plan for swings in the business cycle using the average weekly hours series.
To evaluate the economic health of states and areas;
To guide monetary policy decisions;
To assess the growth of industries;
To forecast tax revenue for states and areas;
To measure employment, hours, and earnings as a means of determining growth in
In Wisconsin, there are CES statistics for:
Wisconsin’s Metropolitan Statistical Areas: Wisconsin’s CES program will publish information for twelve MSAs, an increase from the eleven MSAs defined under the 1990 Census.
Appleton (Outagamie and Calumet) **
Eau Claire (Eau Claire and Chippewa)
Fond du Lac **
Green Bay (Brown, Oconto and Kewaunee) *
La Crosse (La Crosse and Houston County MN)
Madison (Dane, Columbia and Iowa) *
Milwaukee-Waukesha-West Allis (Milwaukee, Waukesha, Ozaukee and Washington)
Oshkosh-Neenah (Winnebago) **
* New definition
** New MSA
Technical Notes on CES Employment
Currently, the CES program sample in Wisconsin includes about 7,000 establishments. Probability sampled employers respond to a survey each month
requesting data on total employment, women employed, production or non-supervisory worker employment, gross payroll, associated total hours
worked, and total overtime hours (in manufacturing).
Method of estimation: The employment data are estimated using a "weighted link relative" technique in which a ratio (link relative) of current-month
employment to that of the previous month is computed from a random sample of weighted establishments reporting for both months. The estimates of employment
for the current month are obtained by multiplying the estimates for the previous month by these ratios. In instances where sample may be deficient,
small domain modeling (SDM) may be used to produce employment estimates. The SDM technique is a weighted least square model using up to 4 independent
variables. Hours and earnings data are developed using sample averages for production workers in manufacturing only.
Annual revisions: Employment estimates are adjusted annually to a complete count of jobs, called benchmarks, derived principally from tax reports which are
submitted by employers who are covered under state unemployment insurance (UI) laws. Some additional employment representing employees not covered by the UI
law are also counted. The benchmark information is used to adjust (recalibrate) the monthly estimates between the new benchmark and the preceding one and also
to establish the level of employment for the new benchmark month. Thus, the benchmarking process establishes the level of employment, and the sample is
used to measure the month-to-month changes in the level for the subsequent months.
Seasonal Adjustment: Seasonally adjusted payroll employment totals for states are computed by aggregating independently adjusted series for major industry
sectors. Revisions of historical data for the most recent 5 years are made once a year, coincident with annual benchmark adjustments.
Reliability of the estimates: All estimates from a sample survey are subject to sampling and other types of errors. Sampling error is a measure of sampling
variability--that is, variation that occurs by chance because a sample rather than the entire population is surveyed. Survey data are also subject to
non-sampling errors, such as those that can be introduced into the data collection and processing operations. Estimates not directly derived from
sample surveys are subject to additional errors resulting from the special estimation processes used. The sums of individual items may not always equal
the totals shown in the same tables because of rounding.
Employment estimates: Measures of sampling error and information on recent benchmark revisions for states are available at the BLS web site.
Employment data refer to persons on establishment payrolls who receive pay for any part of the pay period which includes the 12th of the month.
Persons are counted at their place of work rather than at their place of residence; those appearing on more than one payroll are counted on each payroll.
Establishments are classified in an industry on the basis of their principal product or activity in accordance with the North American Industry
Classification System (NAICS) Manual.
Content Reviewed: May 2013
Contact: - Andrea Gabel - (608) 266-6775
Access Data Query
The Local Area Unemployment Statistics (LAUS) program produces the labor force, employment, unemployment, and unemployment rate estimates for around 7,000 areas in the United States. Areas included are all states, counties, Workforce Development Areas, Small Labor Market Areas, Metropolitan Divisions, Combined Statistical Areas, Metropolitan and
Micropolitan Statistical Areas, and cities with a population of at least 25,000 people.
Wisconsin monthly estimates are developed in conjunction with the State’s Department of Workforce Development and the Bureau of Labor Statistics. Estimates are formed using models. Inputs include current and historical data from the Decennial Census, the Current Population Survey (CPS), the Current Employment Statistics (CES) program, the Quarterly Census of Employment and Wages (QCEW) program and the state Unemployment Insurance (UI) system.
The State LAUS model utilizes a monthly Real-Time Benchmarking procedure to the National Current Population Survey (CPS) estimates. The entire nation is divided into 9 Census Divisions. Wisconsin is in the East North Central Division, which also includes Illinois, Indiana, Michigan, and Ohio. Every month, all state estimates in each division add
to the division CPS total and all divisions add to the national CPS total.
Annual historical benchmarking consists of updating model inputs and population controls, model re-estimation, smoothing, and controlling to revised monthly historical
benchmarked estimates at the division level, which in turn will sum to the monthly national CPS estimates. The monthly benchmarking procedure significantly reduces end-of-year
Some primary data users of LAUS data are federal, state, and local governments, private industries, and individuals. The statistics are used for determining
fund allocations, establishing the need for employment and training services, and assessing local labor market conditions.
Contact: Heather Thompson - (608) 267-5053
The Mass Layoffs Statistics (MLS) program is a Federal-State cooperative statistical effort which uses a standardized, automated
approach to identify, describe, and track the effects of major job cutbacks, using data from individual state unemployment insurance (UI)
The MLS program reports on mass layoff actions that result in workers being separated from their jobs. Monthly mass layoff numbers are from
establishments which have at least fifty (50) initial claims for unemployment insurance (UI) filed against them in a 5-week period.
Extended mass layoff numbers (released quarterly) are from a subset of such establishments, those where the employer indicates that 50 or more
people were separated from their jobs for at least 31 days. If the separations are of at least 31 days duration, information is obtained
from the establishments about the total number of persons separated, the reasons for the separations, recall expectations, and the movement of
MLS data are used for the following purposes:
- Sub-state allocations of Federal funds for dislocated workers through the Economic Development and Worker Adjustment Assistance Act.
- Analysis of ailing industries or geographic areas.
- Identifying the causes and scope of worker dislocations, especially in terms of the human and economic costs, and the characteristics of dislocated workers.
- Development of approaches for work force planners and labor market analysts for assisting employers and/or workers at the local level.
- Analysis of potentially available labor market supply.
The MLS program was discontinued on June 30, 2013, as a result of the cuts under the Balanced Budget and Emergency Deficit Control Act (commonly referred to as sequestration).
Contact: Sheila Ulrich - (608) 267-9611
Access Data Query
The Occupational Employment Statistics (OES) survey is a joint effort of the U.S. Department of Labor, Bureau of Statistics (BLS)
and the Wisconsin Department of Workforce Development. The survey’s purpose is to identify which occupations are in demand and to
estimate the number of employees in each and the wages paid to them. OES collects this information for each state, the District of
Columbia, the Virgin Islands, Puerto Rico and Guam.
A probability sample is used to create the estimates. BLS selects the sample and sends it to the relevant area for data collection.
After collection, the state or territory sends the sample data to BLS, which estimates cross-industry occupational wages and
employment. BLS then transmits the estimates back to the state for further processing and distribution to the public.
The OES Survey draws the major portion of the working sample from each state's or territory’s Unemployment Insurance (UI) file. BLS starts by stratifying the
firms in these files by area. In Wisconsin, establishments are stratified into fifteen Metropolitan Statistical Areas (Metro SA) and five
Balance of State (BOS) areas. The Balance of State areas consist of counties that are not part of an MSA, and to the extent possible,
contain contiguous counties that share a common economic base.
The following table lists Wisconsin’s Metro Statistical Areas (Metro SA) and the counties that comprise them:
|Appleton, WI Metro SA
|Duluth-Superior, MN-WI Metro SA*
|Eau Claire, WI Metro SA
||Chippewa, Eau Claire
|Fond du Lac, WI Metro SA
||Fond du Lac
|Green Bay, WI Metro SA
||Brown, Kewaunee, Oconto
|Janesville-Beloit, WI Metro SA
|Kenosha, WI Metro Division**
|La Crosse, WI-MN Metro SA*
|Madison, WI Metro SA
||Columbia, Dane, Iowa
|Milwaukee-Waukesha, West Allis, WI Metro SA
||Milwaukee, Waukesha, Ozaukee, Washington
|Minneapolis-St. Paul-Bloomington, MN-WI Metro SA
||Pierce, St Croix
|Oshkosh-Neenah, WI Metro SA
|Racine, WI Metro SA
|Sheboygan, WI Metro SA
|Wausau, WI Metro SA
* The Metro SA includes counties in other states.
** Kenosha county is combined with Lake County, IL to form a Metropolitan Division rather than an Metro SA.
The next table shows the counties that comprise each Balance of State (BOS) area:
||West Central BOS
||South West BOS
||South Central BOS
In 2004, the Office of Management and Budget (OMB) redefined many of the nation’s Metropolitan Statistical Areas (MSA).
At that time, they also gave states the opportunity to redefine their Balance of State (BOS) areas. These areas consist of counties that are not part of an MSA. Wisconsin
has defined five such areas, the maximum allowed. The Occupational Employment Statistics (OES) program implemented these changes with the release of the May 2005 estimates.
When creating the Balance of State areas, OMB only required that, to the extent possible, the individual areas consist
of contiguous counties. With this constraint in mind, we attempted to combine non-MSA contiguous counties into groups with a similar industrial structure. Industries were
categorized into the four super sectors: manufacturing, government, tourism-related activities, and other services. We used Quarterly Census of Employment and Wages (QCEW)
data to identify the industrial-employment distribution of each county, and we grouped together contiguous or nearby counties with a high proportion of employment in the same
super sector. For example, the counties assigned to the Eastern BOS area (Walworth, Jefferson, Dodge, Manitowoc and Marinette) have a substantial portion of their employment
in manufacturing, while counties in the Northern BOS area (Ashland, Bayfield, Door, Florence, Forest, Iron, Langlade, Menominee, Oneida, Sawyer and Vilas counties) have much
of their employment in tourism and government. In some cases, it was not possible to keep the counties contiguous, but, with the exception of the Eastern BOS, counties in a
Balance of State area are not separated by more than one county.
After stratifying by area, BLS stratifies the firms in each area into nine size classes, where size is measured by employment. Employment includes full-time
or part-time workers who are on paid vacations or other types of leave; who are on unpaid short-term absences; who are salaried officers, executives, and staff members
of incorporated firms; who are employees temporarily assigned to other units; and who are employees for whom the reporting unit is their permanent duty station regardless of whether that unit prepares their paycheck. The self-employed, owners/partners of unincorporated firms, and unpaid family workers are excluded
The size classes are:
1 - 4
5 - 9
10 - 19
20 - 49
50 - 99
100 - 249
250 - 499
500 - 999
1000 or More
Finally, establishments in each area and size class are further
stratified by industry. BLS uses the North American Industry Classification System (NAICS) for this purpose. (Prior to the 2002 survey, it used the Standard Industrial
Classification (SIC) system.) Industries covered include agricultural services; mining; construction; manufacturing; transportation and public utilities;
wholesale and retail trade; finance, insurance, and real estate; and services. Link to the Census Bureau's
North American Industrial Classification System (NAICS) page to learn more about NAICS.
After stratifying the firms in each state's or territory’s UI file by area, size and industry, BLS selects a random sample from each
stratum. It then adds state, federal, railroad and postal employees to these firms to construct the working sample used to generate the OES
estimates. Finally, BLS assigns each sample firm a weight that reflects the number of firms represented by that unit.
The sample is split into two panels. Firms in the first panel are asked to provide wage and employment information for the pay period
that includes May 12th, and firms in the second panel are asked to provide information for the pay period that includes November 12th.
(Prior to the 2002 survey, each establishment in the sample was asked to provide information for the pay period that included
either October 12th, November 12th, or December 12th.) Contact is made through a mail survey starting the week of May 12th or November
12th. Firms that do not respond, receive two more mail surveys. Firms that still do not respond are contacted by telephone.
BLS sets certain conditions to assure the quality of the estimates. First, states must collect information from establishments employing at least 65 percent of the total employment
and for at least 75 percent of all the units in the sample. Second, states must collect data for at least 70 percent of the sampled units or at least
75 percent of the sampled employment in each Metro SA and BOS.
The OES program uses the Standard Occupational Classification (SOC) system to classify occupations. A SOC code consists of six
digits. The first two refer to the major group, the third refers to the minor group, the fourth and fifth refer to the broad occupation
and the sixth refers to the detailed occupation. In the occupation coded 17-2112, for example, 17 refers to an occupation in the major
group Architecture and Engineering Occupations, 2 refers to the minor group Engineers, 11 refers to the broad occupation Industrial
Engineers, Including Health and Safety, and the last digit, 2, refers to the detailed occupation, Industrial Engineers. SOC
categorizes workers into 22 major groups with nearly 800 detailed occupations.
The major groups are:
Management occupations (Major Group 11)
Business and financial operations occupations (Major Group 13)
Computer and mathematical occupations (Major Group 15)
Architecture and engineering occupations (Major Group 17)
Life, physical, and social science occupations (Major Group 19)
Community and social services occupations (Major Group 21)
Legal occupations (Major Group 23)
Education, training and library occupations (Major Group 25)
Arts, design, entertainment, sports, and media occupations (Major Group 27)
Healthcare practitioners and technical occupations (Major Group 29)
Healthcare support occupations (Major Group 31)
Protective service occupations (Major Group 33)
Food preparation and serving related occupations (Major Group 35)
Building and grounds cleaning and maintenance occupations (Major Group 37)
Personal care and service occupations (Major Group 39)
Sales and related occupations (Major Group 41)
Office and administrative support occupations (Major Group 43)
Farming, fishing, and forestry occupations (Major Group 45)
Construction, and extraction occupations (Major Group 47)
Installation, maintenance, and repair occupations (Major Group 49)
Production occupations (Major Group 51)
Transportation and material moving occupations (Major Group 53).
Link to the Bureau of Labor Service's Standard Occupational Classification (SOC)
page to learn more about the SOC system.
After an employee's occupational classification is determined, a wage range is assigned. Wages are straight-time, gross pay, exclusive of premium pay. Wages
include base rate, cost-of-living adjustments, hazardous duty pay, incentive pay and on-call pay. Wages exclude back pay, jury duty pay, overtime pay,
severance pay, shift differentials, nonproduction bonuses, employer cost of supplemental benefits and tuition reimbursements.
Wages fall into one of following 12 intervals:
$7.50 to $9.49
$15,600 to $19,759\
$9.50 to $11.99
$19,760 to $24,959
$12.00 to $15.24
$24,960 to $31,719
$15.25 to $19.24
$31,720 to $40,039
$19.25 to $24.99
$40,400 to $50,959
$24.50 to $30.99
$50,960 to $64,479
$31.00 to $39.24
$64,480 to $81,639
$39.25 to $49.74
$81,640 to $103,479
$49.75 to $63.24
$103,480 to $131,559
$63.25 to $79.99
$131,560 to $166,399
$80.00 and Over
$166,400 and Over
The Bureau of Labor Statistics uses Wisconsin’s sample data to produce statewide cross-industry wage and employment estimates by
occupations as well as for occupations in each of the fifteen Metro SAs and the five BOS areas. The average wage, the median wage, the 10th percentile wage,
the 25th percentile wage, the 75th percentile wage, the 90th percentile wage, employment, the relative standard error of the
average wage and the relative standard error of the employment estimate are calculated.
BLS combines three years of sample data to generate the OES estimates. The larger sample results in smaller standard errors. Until 2002,
data was collected once a year. Starting in 2002, data is collected two times a year: a May panel and a November panel. Consequently,
estimates through 2004 are based on a combination of panel and annual data. The 2002 estimates, for example, use data from the
November panel of 2002 and data collected in the 2001 and 2000 survey years. (This set of estimates only uses 2.5 years of data.)
The next set of estimates, the 2003 May panel, uses data from the May panel of 2003, the November panel of 2002 and the 2001 and 2000
survey years. After 2004, only panel data is used.
BLS uses the Employment Cost Index (ECI) to adjust wage data from previous years for inflation when combining panels.
As mentioned, the OES Survey does not collect actual wages. For each occupation, employers are asked to record the number of
employees in wage intervals A through L. However, computation of the average wage paid to employees in an occupation requires an estimate
of the total wages paid to the employees in that occupation. Wage information provided by employers and information from the BLS
Office of Compensation and Working Conditions are used to compute this estimate. Except for wage interval L, where the lower bound of
the wage interval is used as the mean (Winsorized Mean), the Office of Compensation and Working Conditions uses population data to compute a mean value for
each wage interval. The mean value in each wage interval is multiplied by the establishment's weight and by the number of
workers reported by the establishment in that wage interval. BLS then sums these values over the 12 wage intervals to find an
estimate of the total wages paid to employees in the specified occupation employed by the establishment. This is repeated for all firms that report employees in the
occupation. The sum of these values is the estimate of total wages paid to the occupation.
BLS estimates the total number of employees in each occupation by multiplying each firm's weight by the number of employees it
reported in each wage interval and summing across all firms reporting employment in the occupation.
The estimated mean wage is found by dividing the estimate of total wages paid by the estimated number of employees. Estimated
total wages paid are also used to compute the estimates of the various percentile wages.
BLS uses the standard 40-hour, 52-week year when estimating wages. Some employees, such as teachers and airline pilots, work
more or less than this amount. For these and other occupations of this type, only annual wages are estimated.
BLS uses the Relative Standard Error (RSE) to measure the reliability of its estimates. A small RSE indicates a
reliable estimate. The RSE of an estimate is computed by dividing its standard error by its estimated value (for example, the standard
error of the average wage divided by the estimate of the average wage).
Data collection for the May and November panels ends December 30th and June 30th respectively. However, for budgetary reasons, the Bureau of Labor Statistics
only publishes the May panel. States send this database to the Bureau of Labor Statistics toward the end of January. It takes about six weeks for BLS to generate the
wage and employment estimates, after which they transfer the estimates to the states for verification and further processing. These estimates are usually ready for publication
by late April or early May.
Estimate Suppression and Survey Confidentiality
BLS will not publish an estimate if its variability is too high. The employment estimate is suppressed if its RSE exceeds 50 percent
and the wage estimate if its RSE exceeds 30 percent.
The survey does not request employee names, Social Security numbers or any other personal identifiers. OES is only interested in occupation and wage data
and not what a particular individual does or earns.
BLS will not publish an estimate if the confidentiality of an employer may be violated. It suppresses an estimate if there are fewer than three employers
in an estimation cell, if the top employer accounts for more than 50 percent of the total employment in the estimation cell or if the
top two employers account for more than 75 percent of the cell's employment. The employment estimate is also suppressed if there are fewer than 10 employees in a cell.
Content Reviewed: May 2013
Contact: Nelse Grundvig - (608) 266-2930
Access Industry Projections Query
Access Occupation Projections Query
Access Projections Matrix Query
The Projections Unit of the Office of Economic Development develops both long- and short-term outlooks of employment in Wisconsin's industries and occupations. Employment
includes all nonfarm wage and salary employment and nonfarm self-employment. Employment trends in approximately 90 industries and 770 occupations are examined.
The long-term projections are for ten years out into the future and are updated every two years. The short-term projections are for two years into the future
and are updated annually. Projections are done for Wisconsin as a whole and for workforce development areas (WDAs).
Long-term projections assist customers in long-range planning, while short-term projections help inform customers of more immediate employment conditions.
Students, job seekers, and counselors may use the projections to explore employment in occupations and industries. Educational institutions may use
occupational projections to evaluate degree and/or course offerings. Researchers may use the data in analyses of Wisconsin's labor market. Employers
may use the data to examine expected employment in industries and occupations.
This program is funded by the U.S. Department of Labor, Employment and Training Administration (ETA).
U.S. Census Bureau, Decennial Censuses; U.S. Bureau of Labor Statistics, Current Population Survey (CPS) and Employment Projections; Current Employment
Statistics (CES); Quarterly Census of Employment and Wages (QCEW, CEW or ES-202); and Occupational Employment Statistics (OES).
Industrial Employment Projections
Preparing industrial projections involves four steps. First, historical time series of industry employment are developed using data from the
Current Employment Statistics (CES) and Quarterly Census of Employment and Wages (QCEW, CEW or ES-202) programs.
Several statistical methods and econometric models are then used to develop a set of preliminary projections for each industry. The models for the long-term
projections include shift-share and ordinary least-squares models. The short-term models include trend, ordinary least-squares, autoregressive-moving
average, vector autoregressive, and Bayesian vector autoregressive models.
Next, a panel of analysts from business, academia, and government review the historical data and the preliminary projections for approximately 50 industry
groups. These groups are based on two- and three-digit North American Industry Classification System (NAICS) codes. The analysts use their knowledge of economic, social,
and technological trends to anticipate future scenarios and changes in employment. Each analyst then provides their own projection for each of the 50 industry groups.
The analysts' projections are then pooled and the averages are used as the final industrial employment projections for the 50 industry groups.
The fourth step involves using the employment projections from the 50 industry groups to develop industry projections at a more detailed level.
The projections from each industry group are dispersed across the three and four-digit NAICS level industries within that group.
The ratios used in the conversion from the larger 50 industry groups to the three and four-digit levels are based on ratios that come from the national
projections prepared by the U.S. Bureau of Labor Statistics. An assumption is made that each Wisconsin detailed industry's growth will be in the same proportion
to the more aggregate level as the U.S. detailed industry's growth is to the more aggregated U.S. level. As warranted, further adjustments are made to the
projections at the detailed level.
Occupational Employment Projections
Occupational employment projections involves merging data from three sources - the Occupational Employment Statistics (OES) survey, the U.S. Bureau
of Labor Statistics (BLS) national projections, and the Wisconsin four-digit NAICS industrial employment for the base and projected years.
The primary source of the base year occupational data is the OES survey. The survey obtains employment by occupation
within each nonfarm wage and salary industry based on four-digit NAICS. About 15,000 firms are surveyed over a three year
period. Each firm is asked to report how many people are employed in each occupation and how much they are paid.
The OES Survey does not obtain a sample of self-employment or unpaid family employment by occupation. As a result,
national ratios of self-employment and unpaid family employment to nonfarm wage and salary employment by occupation are
obtained from BLS. The BLS ratios are based on data from the Current Population Survey (CPS). The national ratios are
applied to Wisconsin OES data to estimate self-employment and unpaid family workers in Wisconsin.
BLS also provides replacement rates by occupation which are derived from the national CPS. Replacement rates are the
expected rate at which job openings will emerge due to people permanently leaving a given occupation. A permanent leave
occurs when a person retires, dies, or for some other reason decides to leave the occupation. In addition, BLS provides
change factors which are used to estimate shifts in the distribution of employment among occupations, within
each industry, over the projection period.
A base year table, called a matrix, of employment by occupation and industry is developed. The matrix is based on
occupational and industrial employment for the current base year. The base year matrix is then merged with the projected
year industrial employment projections, and the BLS separation rates and change factors. The merger of this information
creates the projections of occupational employment by industry.
Content reviewed: May 2013
Blania Calderon - (608) 267-7314
Aziz Tursunov - (608) 267-9609
Access Data Query
The wage and income data provided at the County level are estimates based on the Estimates Delivery System (EDS)
developed by the State of North Carolina and used in a number of other states. EDS uses the state Occupational Employment
Statistics (OES) data to generate wage and employment estimates at the county
level. These estimates are not intended to be quoted in any official or certifying capacity. The data are intended to show
occupational wages at a smaller geographic detail than what is normally offered via the Occupational Employment Statistics
Contact: Nelse Grundvig
- (608) 266-2930