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16-572-CHI
Friday, June 24, 2016

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Occupational Employment and Wages in Milwaukee-Waukesha-West Allis — May 2015

Workers in the Milwaukee-Waukesha-West Allis Metropolitan Statistical Area had an average (mean) hourly wage of $23.16 in May 2015, comparable to the nationwide average of $23.23, according to the U.S. Bureau of Labor Statistics. Assistant Commissioner for Regional Operations Charlene Peiffer noted that, after testing for statistical significance, wages in the local area were lower than their respective national averages in 11 of the 22 major occupational groups including legal; architecture and engineering; and computer and mathematical. Five groups had significantly higher wages than their respective national averages, including construction and extraction; sales and related; and production.

When compared to the nationwide distribution, local employment was more highly concentrated in 5 of the 22 occupational groups, including production; personal care and service; and architecture and engineering. Conversely, 11 groups had employment shares significantly below their national representation, including food preparation and serving related; construction and extraction; and sales and related. (See table A and box note at end of release.)

Table A. Occupational employment and wages by major occupational group, United States and the Milwaukee-Waukesha-West Allis Metropolitan Statistical Area, and measures of statistical significance, May 2015
Major occupational group Percent of total employment Mean hourly wage
United States Milwaukee United States Milwaukee Percent difference (1)

Total, all occupations

100.0% 100.0% $23.23 $23.16 0

Management

5.0 5.2* 55.30 54.61 -1

Business and Financial Operations

5.1 5.3 35.48 33.16* -7

Computer and Mathematical

2.9 3.1 41.43 36.75* -11

Architecture and Engineering

1.8 2.1* 39.89 34.43* -14

Life, Physical, and Social Science

0.8 0.5* 34.24 29.93* -13

Community and Social Services

1.4 1.5 22.19 20.81* -6

Legal

0.8 0.8 49.74 41.22* -17

Education, Training, and Library

6.2 5.6* 25.48 26.72 5

Arts, Design, Entertainment, Sports, and Media

1.3 1.5* 27.39 23.10* -16

Healthcare Practitioner and Technical

5.8 6.1 37.40 38.15 2

Healthcare Support

2.9 2.6* 14.19 14.31 1

Protective Service

2.4 1.8* 21.45 20.18 -6

Food Preparation and Serving Related

9.1 8.0* 10.98 9.83* -10

Building and Grounds Cleaning and Maintenance

3.2 2.9* 13.02 12.43* -5

Personal Care and Service

3.1 5.3* 12.33 11.44* -7

Sales and Related

10.5 9.7* 18.90 21.74* 15

Office and Administrative Support

15.8 15.2* 17.47 17.98* 3

Farming, Fishing, and Forestry

0.3 0.1* 12.67 13.54 7

Construction and Extraction

4.0 3.0* 22.88 26.61* 16

Installation, Maintenance, and Repair

3.9 3.2* 22.11 22.53* 2

Production

6.6 10.0* 17.41 18.50* 6

Transportation and Material Moving

6.9 6.7 16.90 15.67* -7

Footnotes:
(1) A positive percent difference measures how much the mean wage in Milwaukee is above the national mean wage, while a negative difference reflects a lower wage.
* The percent share of employment or mean hourly wage for this area is significantly different from the national average of all areas at the 90-percent confidence level.
 

One occupational group—production—was chosen to illustrate the diversity of data available for any of the 22 major occupational categories. Milwaukee-Waukesha-West Allis had 82,730 jobs in production, accounting for 10.0 percent of local area employment, significantly higher than the 6.6-percent share nationally. The average hourly wage for this occupational group locally was $18.50, significantly above the national wage of $17.41.

Some of the larger detailed occupations within the production group included team assemblers (11,260), machinists (5,720), and first-line supervisors of production and operating workers (5,410). Among the higher paying jobs were gas plant operators ($41.14) and drilling and boring machine tool setters, operators, and tenders, metal and plastic ($38.00). At the lower end of the wage scale were pressers, textile, garment, and related materials ($10.34) and laundry and dry-cleaning workers ($10.49). (Detailed occupational data for production are presented in table 1; for a complete listing of detailed occupations available go to www.bls.gov/oes/2015/may/oes_33340.htm .)

Location quotients allow us to explore the occupational make-up of a metropolitan area by comparing the composition of jobs in an area relative to the national average. (See table 1.) For example, a location quotient of 2.0 indicates that an occupation accounts for twice the share of employment in the area than it does nationally. In the Milwaukee-Waukesha-West Allis Metropolitan Statistical Area, above-average concentrations of employment were found in many of the occupations within the production group. For instance, foundry mold and coremakers were employed at 9.4 times the national rate in Milwaukee, and computer-controlled machine tool operators, metal and plastic, at 4.4 times the U.S. average. On the other hand, food batchmakers had a location quotient of 1.2 in Milwaukee, indicating that this particular occupation’s local and national employment shares were similar.

These statistics are from the Occupational Employment Statistics (OES) survey, a federal-state cooperative program between BLS and State Workforce Agencies, in this case, the Wisconsin Department of Workforce Development.

Notes on Occupational Employment Statistics Data

With the issuance of data for May 2015, the OES program has incorporated redefined metropolitan area definitions as designated by the Office of Management and Budget. OES data are available for 394 metropolitan areas, 38 metropolitan divisions, and 167 OES-defined nonmetropolitan areas. A listing of the areas and their definitions can be found at www.bls.gov/oes/current/msa_def.htm.

A value that is statistically different from another does not necessarily mean that the difference has economic or practical significance. Statistical significance is concerned with the ability to make confident statements about a universe based on a sample. It is entirely possible that a large difference between two values is not significantly different statistically, while a small difference is, since both the size and heterogeneity of the sample affect the relative error of the data being tested.


Technical Note

The Occupational Employment Statistics (OES) survey is a semiannual mail survey measuring occupational employment and wage rates for wage and salary workers in nonfarm establishments in the United States. The OES program produces employment and wage estimates for over 800 occupations for all industries combined in the nation; the 50 states and the District of Columbia; 432 metropolitan areas and divisions; 167 nonmetropolitan areas; and Guam, Puerto Rico, and the U.S. Virgin Islands. National estimates are also available by industry for NAICS sectors, 3-, 4-, and selected 5- and 6-digit industries, and by ownership across all industries and for schools and hospitals. OES data are available at www.bls.gov/oes/tables.htm.

OES estimates are constructed from a sample of about 1.2 million establishments. Forms are mailed to approximately 200,000 sampled establishments in May and November each year. May 2015 estimates are based on responses from six semiannual panels collected over a 3-year period: May 2015, November 2014, May 2014, November 2013, May 2013, and November 2012. The overall national response rate for the six panels is 73.5 percent based on establishments and 69.6 percent based on weighted sampled employment. The unweighted employment of sampled establishments across all six semiannual panels represents approximately 57.9 percent of total national employment. (Response rates are slightly lower for these estimates due to the federal shutdown in October 2013.) The sample in the Milwaukee-Waukesha-West Allis Metropolitan Statistical Area included 5,078 establishments with a response rate of 74 percent. For more information about OES concepts and methodology, go to www.bls.gov/news.release/ocwage.tn.htm.

The May 2015 OES estimates are based on the 2010 Standard Occupational Classification (SOC) system and the 2012 North American Industry Classification System (NAICS). Information about the 2010 SOC is available on the BLS website at www.bls.gov/soc and information about the 2012 NAICS is available at www.bls.gov/bls/naics.htm.

Metropolitan area definitions

The substate area data published in this release reflect the standards and definitions established by the U.S. Office of Management and Budget.

The Milwaukee-Waukesha-West Allis, Wis. Metropolitan Statistical Area includes Milwaukee, Ozaukee, Washington, and Waukesha Counties.

Additional information

OES data are available on our regional web page at www.bls.gov/regions/midwest. Answers to frequently asked questions about the OES data are available at www.bls.gov/oes/oes_ques.htm. Detailed technical information about the OES survey is available in our Survey Methods and Reliability Statement on the BLS website at www.bls.gov/oes/2015/may/methods_statement.pdf.

Information in this release will be made available to sensory impaired individuals upon request . Voice phone: 202-691-5200; Federal Relay Service: 800-877-8339.

Table 1. Employment and wage data from the Occupational Employment Statistics survey, by occupation, Milwaukee-Waukesha-West Allis Metropolitan Statistical Area, May 2015
Occupation (1) Employment Mean wages
Level (2) Location quotient (3) Hourly Annual (4)

Production Occupations

82,730 1.5 $18.50 $38,490

First-Line Supervisors of Production and Operating Workers

5,410 1.5 29.82 62,030

Coil Winders, Tapers, and Finishers

350 4.0 19.80 41,180

Electrical and Electronic Equipment Assemblers

2,570 2.0 18.74 38,970

Electromechanical Equipment Assemblers

630 2.3 23.38 48,620

Engine and Other Machine Assemblers

210 0.9 18.98 39,480

Structural Metal Fabricators and Fitters

990 2.1 20.94 43,560

Team Assemblers

11,260 1.7 16.80 34,950

Assemblers and Fabricators, All Other

1,540 1.1 12.29 25,560

Bakers

1,240 1.2 12.94 26,920

Butchers and Meat Cutters

580 0.7 16.43 34,170

Meat, Poultry, and Fish Cutters and Trimmers

(5) (5) 11.85 24,640

Food and Tobacco Roasting, Baking, and Drying Machine Operators and Tenders

150 1.2 14.85 30,880

Food Batchmakers

930 1.2 14.02 29,160

Food Cooking Machine Operators and Tenders

90 0.4 15.50 32,240

Food Processing Workers, All Other

(5) (5) 13.40 27,870

Computer-Controlled Machine Tool Operators, Metal and Plastic

3,920 4.4 20.45 42,540

Computer Numerically Controlled Machine Tool Programmers, Metal and Plastic

510 3.3 26.66 55,450

Extruding and Drawing Machine Setters, Operators, and Tenders, Metal and Plastic

(5) (5) 15.91 33,100

Forging Machine Setters, Operators, and Tenders, Metal and Plastic

110 1.0 17.38 36,150

Rolling Machine Setters, Operators, and Tenders, Metal and Plastic

90 0.5 18.78 39,060

Cutting, Punching, and Press Machine Setters, Operators, and Tenders, Metal and Plastic

2,540 2.2 17.22 35,830

Drilling and Boring Machine Tool Setters, Operators, and Tenders, Metal and Plastic

180 2.0 38.00 79,030

Grinding, Lapping, Polishing, and Buffing Machine Tool Setters, Operators, and Tenders, Metal and Plastic

1,140 2.6 16.83 35,010

Lathe and Turning Machine Tool Setters, Operators, and Tenders, Metal and Plastic

780 3.2 18.83 39,160

Milling and Planing Machine Setters, Operators, and Tenders, Metal and Plastic

60 0.5 22.45 46,700

Machinists

5,720 2.4 20.20 42,010

Metal-Refining Furnace Operators and Tenders

160 1.3 17.14 35,640

Pourers and Casters, Metal

150 2.7 19.30 40,140

Model Makers, Metal and Plastic

120 3.2 27.37 56,930

Foundry Mold and Coremakers

730 9.4 16.67 34,670

Molding, Coremaking, and Casting Machine Setters, Operators, and Tenders, Metal and Plastic

2,180 2.7 16.41 34,130

Multiple Machine Tool Setters, Operators, and Tenders, Metal and Plastic

1,630 2.6 17.89 37,210

Tool and Die Makers

1,390 3.1 25.04 52,080

Welders, Cutters, Solderers, and Brazers

2,930 1.3 20.38 42,400

Welding, Soldering, and Brazing Machine Setters, Operators, and Tenders

810 2.5 26.00 54,080

Heat Treating Equipment Setters, Operators, and Tenders, Metal and Plastic

240 1.9 20.09 41,780

Plating and Coating Machine Setters, Operators, and Tenders, Metal and Plastic

610 2.8 15.77 32,800

Tool Grinders, Filers, and Sharpeners

170 2.8 19.96 41,520

Metal Workers and Plastic Workers, All Other

130 1.0 17.69 36,800

Prepress Technicians and Workers

580 2.7 19.59 40,750

Printing Press Operators

2,290 2.3 19.32 40,180

Print Binding and Finishing Workers

1,400 4.4 15.52 32,280

Laundry and Dry-Cleaning Workers

1,450 1.2 10.49 21,820

Pressers, Textile, Garment, and Related Materials

(5) (5) 10.34 21,510

Sewing Machine Operators

490 0.6 12.87 26,780

Tailors, Dressmakers, and Custom Sewers

190 1.6 13.77 28,630

Upholsterers

50 0.3 16.46 34,240

Textile, Apparel, and Furnishings Workers, All Other

(5) (5) 9.53 19,830

Cabinetmakers and Bench Carpenters

350 0.6 18.42 38,310

Furniture Finishers

70 0.7 17.72 36,850

Sawing Machine Setters, Operators, and Tenders, Wood

(5) (5) 19.09 39,700

Woodworking Machine Setters, Operators, and Tenders, Except Sawing

330 0.7 14.59 30,360

Stationary Engineers and Boiler Operators

70 0.3 25.35 52,730

Water and Wastewater Treatment Plant and System Operators

550 0.8 22.88 47,590

Gas Plant Operators

40 0.4 41.14 85,560

Chemical Equipment Operators and Tenders

200 0.5 21.81 45,350

Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders

350 1.2 19.57 40,710

Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders

100 0.5 17.61 36,630

Grinding and Polishing Workers, Hand

300 1.8 16.04 33,360

Mixing and Blending Machine Setters, Operators, and Tenders

1,170 1.5 17.97 37,390

Cutters and Trimmers, Hand

50 0.5 12.77 26,570

Cutting and Slicing Machine Setters, Operators, and Tenders

550 1.4 16.53 34,370

Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders

370 0.9 13.11 27,260

Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders

(5) (5) 21.69 45,110

Inspectors, Testers, Sorters, Samplers, and Weighers

3,790 1.2 19.09 39,700

Jewelers and Precious Stone and Metal Workers

100 0.6 23.98 49,870

Dental Laboratory Technicians

190 0.8 19.10 39,720

Medical Appliance Technicians

(5) (5) 15.95 33,170

Ophthalmic Laboratory Technicians

170 1.0 15.16 31,540

Packaging and Filling Machine Operators and Tenders

3,330 1.5 15.87 33,000

Coating, Painting, and Spraying Machine Setters, Operators, and Tenders

1,290 2.4 18.76 39,020

Painters, Transportation Equipment

160 0.5 22.80 47,420

Photographic Process Workers and Processing Machine Operators

230 1.6 14.57 30,300

Adhesive Bonding Machine Operators and Tenders

50 0.4 15.04 31,270

Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders

40 0.3 15.18 31,580

Etchers and Engravers

150 2.6 16.07 33,420

Molders, Shapers, and Casters, Except Metal and Plastic

100 0.4 16.26 33,820

Paper Goods Machine Setters, Operators, and Tenders

1,100 2.0 16.81 34,960

Helpers--Production Workers

3,510 1.3 12.33 25,650

Production Workers, All Other

1,180 0.8 16.80 34,940

Footnotes:
(1) For a complete listing of all detailed occupations in the Milwaukee-Waukesha-West Allis Metropolitan Statistical Area, see www.bls.gov/oes/current/oes_33340.htm.
(2) Estimates for detailed occupations do not sum to the totals because the totals include occupations not shown separately. Estimates do not include self-employed workers.
(3) The location quotient is the ratio of the area concentration of occupational employment to the national average concentration. A location quotient greater than one indicates the occupation has a higher share of employment than average, and a location quotient less than one indicates the occupation is less prevalent in the area than average.
(4) Annual wages have been calculated by multiplying the hourly mean wage by a ‘year-round, full-time’ hours figure of 2,080 hours; for those occupations where there is not an hourly mean wage published, the annual wage has been directly calculated from the reported survey data.
(5) Estimates not released.
 

 

Last Modified Date: Friday, June 24, 2016