Geography

Wisconsin's CES data provides information statewide and in Metropolitan Statistical Areas below:

• Appleton (Calumet and Outagamie)
• 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

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.

Definitions

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: 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: Classified in an industry on the basis of their principal product or activity in accordance with the North American Industry Classification System (NAICS) Manual.