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17-535-CHI
Wednesday, June 28, 2017

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Occupational Employment and Wages in Milwaukee-Waukesha-West Allis — May 2016

Workers in the Milwaukee-Waukesha-West Allis Metropolitan Statistical Area had an average (mean) hourly wage of $23.73 in May 2016, not significantly different than the nationwide average of $23.86, 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. Six groups had significantly higher wages than their respective national averages, including healthcare support; construction and extraction; and sales and related.

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 business and financial operations. Conversely, 12 groups had employment shares significantly below their national representation, including construction and extraction; food preparation and serving related; and office and administrative support. (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 2016
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 $23.86 $23.73 -1

Management

5.1 5.3* 56.74 56.05 -1

Business and financial operations

5.2 5.6* 36.09 33.66* -7

Computer and mathematical

3.0 3.1 42.25 36.11* -15

Architecture and engineering

1.8 2.0* 40.53 34.34* -15

Life, physical, and social science

0.8 0.5* 35.06 31.02* -12

Community and social service

1.4 1.6 22.69 20.82* -8

Legal

0.8 0.8 50.95 41.66* -18

Education, training, and library

6.2 5.6* 26.21 26.78 2

Arts, design, entertainment, sports, and media

1.4 1.5 28.07 23.13* -18

Healthcare practitioners and technical

5.9 6.3 38.06 39.54 4

Healthcare support

2.9 2.4* 14.65 15.13* 3

Protective service

2.4 1.8* 22.03 21.67 -2

Food preparation and serving related

9.2 8.4* 11.47 10.27* -10

Building and grounds cleaning and maintenance

3.2 2.9* 13.47 12.60* -6

Personal care and service

3.2 5.3* 12.74 11.89* -7

Sales and related

10.4 9.6* 19.50 21.91* 12

Office and administrative support

15.7 14.9* 17.91 18.37* 3

Farming, fishing, and forestry

0.3 0.1* 13.37 16.01* 20

Construction and extraction

4.0 3.0* 23.51 27.25* 16

Installation, maintenance, and repair

3.9 3.3* 22.45 22.75 1

Production

6.5 10.0* 17.88 18.91* 6

Transportation and material moving

6.9 6.2* 17.34 16.84* -3

Footnotes:
(1) A positive percent difference measures how much the mean wage in the Milwaukee-Waukesha-West Allis Metropolitan Statistical Area 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 84,500 jobs in production, accounting for 10.0 percent of local area employment, significantly higher than the 6.5-percent share nationally. The average hourly wage for this occupational group locally was $18.91, significantly above the national wage of $17.88.

Some of the largest detailed occupations within the production group included team assemblers (11,510), machinists (6,010), and first-line supervisors of production and operating workers (5,660). Among the higher paying jobs were drilling and boring machine tool setters, operators, and tenders, metal and plastic with mean hourly wages of $38.27 and power plant operators, $36.96. At the lower end of the wage scale were laundry and dry-cleaning workers ($10.13) and pressers, textile, garment, and related materials ($11.21). (Detailed occupational data for production are presented in table 1; for a complete listing of detailed occupations available go to www.bls.gov/oes/2016/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, computer-controlled machine tool operators, metal and plastic were employed at 4.7 times the national rate in Milwaukee, and print binding and finishing workers, at 4.4 times the U.S. average. On the other hand, laundry and dry-cleaning workers had a location quotient of 1.0 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.

Note

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 data available from BLS include cross-industry occupational employment and wage estimates for the nation; over 650 areas, including states and the District of Columbia, metropolitan statistical areas (MSAs), metropolitan divisions, nonmetropolitan areas, and territories; national industry-specific estimates at the NAICS sector, 3-, 4-, and selected 5- and 6-digit industry levels, and national estimates 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. Each year, two semiannual panels of approximately 200,000 sampled establishments are contacted, one panel in May and the other in November. Responses are obtained by mail, Internet or other electronic means, email, telephone, or personal visit. The May 2016 estimates are based on responses from six semiannual panels collected over a 3-year period: May 2016, November 2015, May 2015, November 2014, May 2014, and November 2013. The overall national response rate for the six panels, based on the 50 states and the District of Columbia, is 73 percent based on establishments and 69 percent based on weighted sampled employment. The unweighted employment of sampled establishments across all six semiannual panels represents approximately 58 percent of total national employment. The sample in the Milwaukee-Waukesha-West Allis Metropolitan Statistical Area included 4,997 establishments with a response rate of 75 percent. For more information about OES concepts and methodology, go to www.bls.gov/news.release/ocwage.tn.htm.

The May 2016 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/current/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 2016
Occupation (1) Employment Mean wages
Level (2) Location quotient (3) Hourly Annual (4)

Production occupations

84,500 1.6 $18.91 $39,330

First-line supervisors of production and operating workers

5,660 1.6 30.14 62,690

Coil winders, tapers, and finishers

(5) (5) 17.17 35,720

Electrical and electronic equipment assemblers

3,500 2.7 17.84 37,100

Electromechanical equipment assemblers

710 2.6 22.34 46,460

Engine and other machine assemblers

220 0.9 17.98 37,400

Structural metal fabricators and fitters

1,030 2.2 21.40 44,520

Team assemblers

11,510 1.7 16.50 34,320

Assemblers and fabricators, all other

880 0.6 12.85 26,730

Bakers

1,110 1.0 13.69 28,470

Butchers and meat cutters

480 0.6 20.22 42,060

Meat, poultry, and fish cutters and trimmers

470 0.5 12.85 26,730

Food and tobacco roasting, baking, and drying machine operators and tenders

270 2.3 12.29 25,560

Food batchmakers

1,300 1.5 13.14 27,330

Food cooking machine operators and tenders

110 0.5 16.57 34,460

Food processing workers, all other

110 0.4 12.98 27,000

Computer-controlled machine tool operators, metal and plastic

4,140 4.7 21.43 44,580

Computer numerically controlled machine tool programmers, metal and plastic

470 3.1 27.02 56,200

Extruding and drawing machine setters, operators, and tenders, metal and plastic

(5) (5) 17.88 37,190

Forging machine setters, operators, and tenders, metal and plastic

(5) (5) 15.09 31,390

Rolling machine setters, operators, and tenders, metal and plastic

110 0.6 22.63 47,060

Cutting, punching, and press machine setters, operators, and tenders, metal and plastic

3,090 2.7 18.01 37,470

Drilling and boring machine tool setters, operators, and tenders, metal and plastic

190 2.5 38.27 79,600

Grinding, lapping, polishing, and buffing machine tool setters, operators, and tenders, metal and plastic

1,650 3.7 17.20 35,770

Lathe and turning machine tool setters, operators, and tenders, metal and plastic

670 3.3 20.67 42,990

Milling and planing machine setters, operators, and tenders, metal and plastic

50 0.5 21.11 43,910

Machinists

6,010 2.6 20.14 41,890

Metal-refining furnace operators and tenders

110 1.0 17.45 36,300

Pourers and casters, metal

200 4.0 18.22 37,890

Model makers, metal and plastic

80 2.2 27.38 56,950

Patternmakers, metal and plastic

50 2.6 19.43 40,410

Molding, coremaking, and casting machine setters, operators, and tenders, metal and plastic

2,290 2.6 16.63 34,580

Multiple machine tool setters, operators, and tenders, metal and plastic

1,180 1.7 18.93 39,370

Tool and die makers

1,200 2.8 25.45 52,940

Welders, cutters, solderers, and brazers

3,330 1.5 21.08 43,840

Welding, soldering, and brazing machine setters, operators, and tenders

430 1.5 25.67 53,390

Heat treating equipment setters, operators, and tenders, metal and plastic

280 2.4 20.63 42,920

Plating and coating machine setters, operators, and tenders, metal and plastic

520 2.5 15.53 32,290

Tool grinders, filers, and sharpeners

170 3.0 19.40 40,360

Metal workers and plastic workers, all other

80 0.6 17.36 36,120

Prepress technicians and workers

570 2.9 21.02 43,710

Printing press operators

2,270 2.2 19.41 40,370

Print binding and finishing workers

1,380 4.4 15.68 32,610

Laundry and dry-cleaning workers

1,240 1.0 10.13 21,060

Pressers, textile, garment, and related materials

170 0.6 11.21 23,310

Sewing machine operators

500 0.6 13.22 27,490

Tailors, dressmakers, and custom sewers

200 1.6 14.80 30,790

Textile knitting and weaving machine setters, operators, and tenders

40 0.3 13.15 27,350

Upholsterers

(5) (5) 17.22 35,820

Cabinetmakers and bench carpenters

400 0.7 19.17 39,860

Furniture finishers

50 0.5 17.19 35,760

Sawing machine setters, operators, and tenders, wood

(5) (5) 19.95 41,500

Woodworking machine setters, operators, and tenders, except sawing

330 0.7 15.28 31,780

Power plant operators

110 0.5 36.96 76,880

Stationary engineers and boiler operators

90 0.5 25.90 53,870

Water and wastewater treatment plant and system operators

360 0.5 27.84 57,900

Chemical equipment operators and tenders

390 0.9 22.27 46,310

Separating, filtering, clarifying, precipitating, and still machine setters, operators, and tenders

330 1.2 21.04 43,750

Crushing, grinding, and polishing machine setters, operators, and tenders

90 0.5 18.47 38,410

Grinding and polishing workers, hand

200 1.3 18.02 37,470

Mixing and blending machine setters, operators, and tenders

1,400 1.8 18.19 37,840

Cutters and trimmers, hand

30 0.4 13.63 28,350

Cutting and slicing machine setters, operators, and tenders

700 1.9 16.93 35,210

Extruding, forming, pressing, and compacting machine setters, operators, and tenders

250 0.6 14.47 30,100

Inspectors, testers, sorters, samplers, and weighers

4,210 1.4 19.94 41,460

Jewelers and precious stone and metal workers

(5) (5) 26.55 55,230

Dental laboratory technicians

110 0.5 21.16 44,020

Medical appliance technicians

110 1.3 (5) (5)

Ophthalmic laboratory technicians

160 0.9 14.65 30,480

Packaging and filling machine operators and tenders

2,940 1.3 16.14 33,580

Coating, painting, and spraying machine setters, operators, and tenders

1,400 2.7 18.43 38,330

Painters, transportation equipment

190 0.6 22.32 46,430

Photographic process workers and processing machine operators

240 1.5 14.46 30,070

Adhesive bonding machine operators and tenders

(5) (5) 16.57 34,470

Etchers and engravers

150 2.6 16.12 33,530

Molders, shapers, and casters, except metal and plastic

360 1.5 15.95 33,180

Paper goods machine setters, operators, and tenders

1,030 1.8 17.94 37,320

Helpers--production workers

3,150 1.2 12.61 26,220

Production workers, all other

1,200 0.8 16.76 34,870

Footnotes:
(1) For a complete listing of all detailed occupations in the Milwaukee-Waukesha-West Allis, WI, 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) Estimate not released.
 

 

Last Modified Date: Wednesday, June 28, 2017