Program Descriptions

Program Descriptions

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.

Quarterly Census of Employment and Wages (QCEW/ES-202)

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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 Washington, DC.

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

  1. 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.
  1. 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.

Industrial Classification

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 major input.

More information about NAICS is on-line at

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 domestic workers.

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 establishment level.

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.

Disclosure Restrictions

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.

Imputed Data

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.

Data Users

Data Uses

Bureau of Economic Analysis

Personal Income

(National Income and Product Accounts)

County Personal and Per Capita Income

Bureau of the Census

Industry Coding

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

NCS 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 Estimates

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

Research Units

Wage Survey Sampling

Birth/Death Studies

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

Private Consultants

Econometric Modeling and Forecasting


Assorted Research


Articles and Publications

General Public

Employment information

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

Short Description

Contact: Deb Holt - (608) 266-5321

Current Employment Statistics (CES)

Data Sources

CES Data Query (Not Seasonally Adjusted)
CES Data Downloads (Seasonally Adjusted and Not Seasonally Adjusted .xls files)


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 & Technical Support in the Department of Workforce Development.

Data Uses

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:

Private Sector

  • 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.

Public Sector

  • 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 the economy.


In Wisconsin, there are CES statistics for:

  • Wisconsin (statewide), and

Wisconsin’s Metropolitan Statistical Areas:

  • Appleton (Outagamie and Calumet)
  • Eau Claire (Eau Claire and Chippewa)
  • Fond du Lac
  • Green Bay (Brown, Oconto and Kewaunee)
  • Janesville (Rock)
  • La Crosse (La Crosse and Houston County, MN)
  • Madison (Dane, Columbia, Iowa and Green)*
  • Milwaukee-Waukesha-West Allis (Milwaukee, Waukesha, Ozaukee and Washington)
  • Oshkosh-Neenah (Winnebago)
  • Racine
  • Sheboygan
  • Wausau (Marathon)
*New definition 2015

Technical Notes on CES Employment

Currently, the CES program sample in Wisconsin includes about 9,500 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: April 2015

Short Description

Contact: - Andrea Gabel - (608) 266-6775

Local Area Unemployment Statistics (LAUS)

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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 revisions.

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.

Short Description

Contact: Heather Thompson - (608) 267-5053

Mass Layoff Statistics (MLS)

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) databases.

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 work.

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).

Short Description

Contact: Sheila Ulrich - (608) 267-9611

Occupational Employment Statistics (OES)

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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 four 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:

Metro SA Counties
Appleton, WI Metro SA Calumet, Outagamie
Duluth-Superior, MN-WI Metro SA* Douglas
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 Rock
Kenosha, WI Metro Division** Kenosha
La Crosse, WI-MN Metro SA* La Crosse
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 Winnebago
Racine, WI Metro SA Racine
Sheboygan, WI Metro SA Sheboygan
Wausau, WI Metro SA Marathon

* 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:

Northwestern BOS 1 Northeastern BOS 2 Southeastern BOS 3 Western
Ashland Adams Dodge Barron
Bayfield Door Grant Buffalo
Burnett Florence Green Lake Clark
Iron Forest Jefferson Crawford
Price Langlade Lafayette Dunn
Rusk Lincoln Marquette Jackson
Sawyer Manitowoc Richland Juneau
Taylor Marinette Sauk Monroe
Washburn Menominee Walworth Pepin


  Portage Waushara Trempealeau













In 2014, 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 four such areas. The Occupational Employment Statistics (OES) program implemented these changes with the release of the May 2015 estimates.

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:

Size Class



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.

Data Collection

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 email or 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:


Hourly Wages

Annual Wages

Range A

Under $9.25

Under $19,240

Range B

$9.25 to $11.74

$19,240 to $24,439

Range C

$11.75 to $14.74

$24,440 to $30,679

Range D

$14.75 to $18.74

$30,680 to $38,999

Range E

$18.75 to $23.99

$39,000 to $49,919

Range F

$24.00 to $30.24

$49,920 to $62,919

Range G

$30.25 to $38.49

$62,920  to $80,079

Range H

$38.50 to $48.99

$80,080 to $101,919

Range I

$49.00 to $61.99

$101,920 to $128,959

Range J

$62.00 to $78.74

$128,960 to $163,799

Range K

$78.75 to $99.99

$163,800 to $207,999

Range L

$100.00 and Over

$208,000 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 four 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 2017

Short Description

Contact: Sal Serio - (608) 266-2069


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 300 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).

Data Used

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

Short Description

Blania Calderon - (608) 267-7314
Aziz Tursunov - (608) 267-9609

County Wages and Employment by Occupation

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 (OES) survey.

Short Description

Contact: Judith Lee - (608) 266-2869

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