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News Release Information

18-431-CHI
Wednesday, May 23, 2018

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Technical information:
Media contact:
  • (312) 353-1138

Occupational Employment and Wages in Green Bay — May 2017

Workers in the Green Bay Metropolitan Statistical Area had an average (mean) hourly wage of $21.19 in May 2017, about 13 percent below the nationwide average of $24.34, 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 16 of the 22 major occupational groups, including legal; management; and architecture and engineering.

When compared to the nationwide distribution, local employment was more highly concentrated in 2 of the 22 occupational groups: production and transportation and material moving. Conversely, 12 groups had employment shares significantly below their national representation, including sales and related; food preparation and serving related; and management. (See table A and box note at end of release.)

Table A. Occupational employment and wages by major occupational group, United States and the Green Bay Metropolitan Statistical Area, and measures of statistical significance, May 2017
Major occupational groupPercent of total employmentMean hourly wage
United StatesGreen BayUnited StatesGreen BayPercent difference (1)

Total, all occupations

100.0100.0$24.34$21.19*-13

Management

5.14.3*57.6547.01*-18

Business and financial operations

5.24.7*36.7028.32*-23

Computer and mathematical

3.02.643.1833.94*-21

Architecture and engineering

1.81.741.4432.19*-22

Life, physical, and social science

0.80.5*35.7629.38*-18

Community and social service

1.51.2*23.1021.66*-6

Legal

0.80.3*51.6240.42*-22

Education, training, and library

6.15.4*26.6722.85*-14

Arts, design, entertainment, sports, and media

1.41.328.3420.34*-28

Healthcare practitioners and technical

6.05.838.8335.03*-10

Healthcare support

2.92.3*15.0515.453

Protective service

2.41.9*22.6920.10*-11

Food preparation and serving related

9.38.5*11.8810.34*-13

Building and grounds cleaning and maintenance

3.12.4*13.9112.79*-8

Personal care and service

3.64.013.1111.73*-11

Sales and related

10.29.3*19.5619.32-1

Office and administrative support

15.416.118.2417.28*-5

Farming, fishing, and forestry

0.30.1*13.8717.21*24

Construction and extraction

4.04.024.0123.66-1

Installation, maintenance, and repair

3.94.023.0222.18*-4

Production

6.311.5*18.3018.401

Transportation and material moving

7.08.0*17.8217.62-1

Footnotes:
(1) A positive percent difference measures how much the mean wage in the Green Bay 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. Green Bay had 19,980 jobs in production, accounting for 11.5 percent of local area employment, significantly higher than the 6.3-percent share nationally. The average hourly wage for this occupational group locally was $18.40, compared to the national wage of $18.30.

Some of the larger detailed occupations within the production group included assemblers and fabricators, all other, including team assemblers (1,930); paper goods machine setters, operators, and tenders (1,470); and first-line supervisors of production and operating workers (1,460). Among the higher paying jobs in this group were first-line supervisors of production and operating workers with mean hourly wages of $28.54 and water and wastewater treatment plant and system operators, $26.84. At the lower end of the wage scale were textile cutting machine setters, operators, and tenders ($10.28) and laundry and dry-cleaning workers ($11.59). (Detailed data for production occupations are presented in table 1; for a complete listing of detailed occupations available go to www.bls.gov/oes/current/oes_24580.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 Green Bay Metropolitan Statistical Area, above-average concentrations of employment were found in many of the occupations within the production group. For instance, paper goods machine setters, operators, and tenders were employed at 12.8 times the national rate in Green Bay, and print binding and finishing workers, at 5.4 times the U.S. average. On the other hand, laundry and dry-cleaning workers had a location quotient of 1.1 in Green Bay, 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 release of the May 2017 estimates, the OES program has replaced 21 detailed occupations found in the 2010 Standard Occupational Classification (SOC) with 10 new aggregations of those occupations. In addition, selected 4- and 5-digit North American Industry Classification System (NAICS) industries previously published by OES will no longer be published separately. Some of the 4-digit NAICS industries that are no longer being published separately will instead be published as OES-specific industry aggregations. More information about the new occupational and industry aggregations is available at www.bls.gov/oes/changes_2017.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 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 2017 estimates are based on responses from six semiannual panels collected over a 3-year period: May 2017, November 2016, May 2016, November 2015, May 2015, and November 2014. The overall national response rate for the six panels, based on the 50 states and the District of Columbia, is 72 percent based on establishments and 68 percent based on weighted sampled employment. The unweighted sample employment of 82 million across all six semiannual panels represents approximately 58 percent of total national employment. The sample in the Green Bay Metropolitan Statistical Area included 1,857 establishments with a response rate of 77 percent. For more information about OES concepts and methodology, go to www.bls.gov/oes/current/oes_tec.htm.

The May 2017 OES estimates are based on the 2010 Standard Occupational Classification (SOC) system and the 2017 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 2017 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 Green Bay, Wis. Metropolitan Statistical Area includes Brown, Kewaunee, and Oconto 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, Green Bay Metropolitan Statistical Area, May 2017
Occupation (1)EmploymentMean wages
Level (2)Location quotient (3)HourlyAnnual (4)

Production occupations

19,9801.8$18.40$38,260

First-line supervisors of production and operating workers

1,4602.028.5459,370

Electrical, electronic, and electromechanical assemblers, except coil winders, tapers, and finishers

4801.515.3331,890

Structural metal fabricators and fitters

4604.821.4644,640

Assemblers and fabricators, all other, including team assemblers

1,9301.214.9431,080

Bakers

2801.315.2831,780

Butchers and meat cutters

2001.218.0637,560

Meat, poultry, and fish cutters and trimmers

8104.315.0031,190

Slaughterers and meat packers

2402.615.7432,740

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

1606.312.9326,890

Food batchmakers

9004.918.2037,850

Food cooking machine operators and tenders

401.017.0335,420

Food processing workers, all other

4709.013.3027,660

Computer-controlled machine tool operators, metal and plastic

3502.021.3144,330

Computer numerically controlled machine tool programmers, metal and plastic

602.123.7649,420

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

(5)(5)14.6630,490

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

1900.918.4438,360

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

(5)(5)13.7028,490

Machinists

7101.622.5846,970

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

(5)(5)14.7130,590

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

(5)(5)17.6236,640

Tool and die makers

500.621.1143,910

Welders, cutters, solderers, and brazers

8201.819.9041,400

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

(5)(5)17.4736,330

Prepress technicians and workers

1905.117.6136,630

Printing press operators

8604.119.3640,280

Print binding and finishing workers

3205.415.5132,250

Laundry and dry-cleaning workers

2701.111.5924,100

Sewing machine operators

1200.712.0024,950

Textile cutting machine setters, operators, and tenders

(5)(5)10.2821,390

Upholsterers

401.016.9435,230

Cabinetmakers and bench carpenters

2902.516.6934,710

Furniture finishers

1205.714.7930,760

Sawing machine setters, operators, and tenders, wood

1101.714.4430,040

Woodworking machine setters, operators, and tenders, except sawing

2202.314.5630,280

Stationary engineers and boiler operators

701.724.7051,370

Water and wastewater treatment plant and system operators

900.626.8455,830

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

300.518.3838,220

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

(5)(5)21.1644,010

Grinding and polishing workers, hand

401.114.6930,560

Mixing and blending machine setters, operators, and tenders

4102.620.2642,130

Cutting and slicing machine setters, operators, and tenders

2503.518.4038,270

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

1101.220.3542,320

Inspectors, testers, sorters, samplers, and weighers

9001.417.8837,190

Dental laboratory technicians

(5)(5)16.0733,420

Ophthalmic laboratory technicians

902.515.3231,870

Packaging and filling machine operators and tenders

1,3602.917.9137,250

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

2102.018.9439,400

Painters, transportation equipment

(5)(5)20.0241,630

Cleaning, washing, and metal pickling equipment operators and tenders

(5)(5)15.3631,950

Molders, shapers, and casters, except metal and plastic

(5)(5)15.3831,990

Paper goods machine setters, operators, and tenders

1,47012.820.0741,750

Helpers--production workers

9001.816.7834,900

Production workers, all other

1800.615.3631,950

Footnotes:
(1) For a complete listing of all detailed occupations in Green Bay, WI, see www.bls.gov/oes/current/oes_24580.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, May 23, 2018