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News Release Information

23-1281-SAN
Thursday, June 22, 2023

Contacts Technical information: Media contact:
  • (415) 625-2270

Occupational Employment and Wages in Seattle-Tacoma-Bellevue — May 2022

Workers in the Seattle-Tacoma-Bellevue, WA Metropolitan Statistical Area had an average (mean) hourly wage of $38.47 in May 2022, 29 percent above the nationwide average of $29.76, the U.S. Bureau of Labor Statistics reported today. Regional Commissioner Chris Rosenlund noted that, after testing for statistical significance, wages in the local area were higher than their respective national averages in 21 of the 22 major occupational groups, including management, computer and mathematical, and construction and extraction.

When compared to the nationwide distribution, Seattle area employment was more highly concentrated in 6 of the 22 occupational groups, including computer and mathematical, business and financial operations, and architecture and engineering. Eleven groups had employment shares significantly below their national representation, including production, transportation and material moving, and office and administrative support. (See table A.)

Table A. Occupational employment and wages by major occupational group, United States and the Seattle metropolitan area, and measures of statistical significance, May 2022
Major occupational group Percent of total employment Mean hourly wage ($)
United States Seattle United States Seattle Percent difference (1)

Total, all occupations

100.0 100.0 29.76 38.47* 29

Management

6.7 5.8* 63.08 78.26* 24

Business and financial operations

6.5 9.3* 41.39 47.21* 14

Computer and mathematical

3.4 8.3* 51.99 65.19* 25

Architecture and engineering

1.7 2.4* 45.52 51.44* 13

Life, physical, and social science

0.9 1.2* 40.21 45.03* 12

Community and social service

1.6 1.6 26.81 30.48* 14

Legal

0.8 0.8 59.87 63.50 6

Educational instruction and library

5.7 4.7* 30.41 35.59* 17

Arts, design, entertainment, sports, and media

1.4 1.7* 36.78 40.78* 11

Healthcare practitioners and technical

6.1 5.1* 46.52 54.96* 18

Healthcare support

4.6 4.6 17.10 21.27* 24

Protective service

2.3 1.8* 25.97 32.24* 24

Food preparation and serving related

8.5 8.0 15.45 20.64* 34

Building and grounds cleaning and maintenance

2.9 2.3* 17.26 21.72* 26

Personal care and service

1.9 1.8* 17.41 23.25* 34

Sales and related

8.9 9.3 24.22 31.44* 30

Office and administrative support

12.6 11.3* 21.90 26.40* 21

Farming, fishing, and forestry

0.3 0.1* 18.21 22.58* 24

Construction and extraction

4.1 4.6* 28.08 37.58* 34

Installation, maintenance, and repair

3.9 3.3* 26.77 32.78* 22

Production

5.9 4.2* 21.81 27.35* 25

Transportation and material moving

9.2 7.8* 21.12 27.82* 32

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

One occupational group—computer and mathematical—was chosen to illustrate the diversity of data available for any of the 22 major occupational categories. Seattle had 170,030 jobs in computer and mathematical, accounting for 8.3 percent of local area employment, significantly higher than the 3.4-percent share nationally. The average hourly wage for this occupational group locally was $65.19, significantly above the national wage of $51.99.

Some of the larger detailed occupations within the computer and mathematical group included software developers (80,770), computer user support specialists (14,100), and computer systems analysts (13,350). Among the higher-paying jobs in this group were computer and information research scientists and database architects, with mean hourly wages of $95.49 and $79.01, respectively. At the lower end of the wage scale were computer user support specialists ($36.00) and computer network support specialists ($42.80). (Detailed data for the computer and mathematical occupations are presented in table 1; for a complete listing of detailed occupations available go to www.bls.gov/oes/current/oes_42660.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 Seattle area, above-average concentrations of employment were found in many of the occupations within the computer and mathematical group. For instance, web and digital interface designers were employed at 4.6 times the national rate in Seattle, and web developers, at 4.3 times the U.S. average. Network and computer systems administrators had a location quotient of 1.1 in Seattle, indicating that this particular occupation’s local and national employment shares were similar.

These statistics are from the Occupational Employment and Wage Statistics (OEWS) survey, a federal-state cooperative program between BLS and State Workforce Agencies, in this case, the Washington Employment Security Department.

Changes to the Occupational Employment and Wage Statistics (OEWS) Data

The May 2022 OEWS estimates use the model-based (MB3) estimation method implemented with the May 2021 estimates release. Additional updates were made to the MB3 wage processing methodology for May 2022. For more information, see the May 2022 Survey Methods and Reliability Statement.

The May 2022 estimates are the first OEWS estimates to be produced using the 2022 NAICS, which replaces the 2017 NAICS used for the May 2017-May 2021 estimates. See North American Industry Classification System (NAICS) at BLS for details.


Technical Note

The Occupational Employment and Wage Statistics (OEWS) survey is a semiannual survey measuring occupational employment and wage rates for wage and salary workers in nonfarm establishments in the United States. The OEWS data available from BLS include cross-industry occupational employment and wage estimates for the nation; over 580 areas, including states and the District of Columbia, metropolitan statistical areas (MSAs), nonmetropolitan areas, and territories; national industry-specific estimates at the NAICS sector, 3-digit, most 4-digit, and selected 5- and 6-digit industry levels, and national estimates by ownership across all industries and for schools and hospitals. OEWS data are available at www.bls.gov/oes/tables.htm.

The OEWS survey is a cooperative effort between BLS and the State Workforce Agencies (SWAs). BLS funds the survey and provides the procedures and technical support, while the State Workforce Agencies collect most of the data. OEWS estimates are constructed from a sample of about 1.1 million establishments. Each year, two semiannual panels of approximately 179,000 to 187,000 sampled establishments are contacted, one panel in May and the other in November. Responses are obtained by Internet or other electronic means, mail, email, telephone, or personal visit. The May 2022 estimates are based on responses from six semiannual panels collected over a 3-year period: May 2022, November 2021, May 2021, November 2020, May 2020, and November 2019. The unweighted sampled employment of 80 million across all six semiannual panels represents approximately 57 percent of total national employment. The overall national response rate for the six panels, based on the 50 states and the District of Columbia, is 65.4 percent based on establishments and 62.5 percent based on weighted sampled employment. The sample in the Seattle-Tacoma-Bellevue, WA Metropolitan Statistical Area included 7,089 establishments with a response rate of 69 percent. For more information about OEWS concepts and methodology, go to www.bls.gov/oes/current/oes_tec.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.

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 Seattle-Tacoma-Bellevue, WA Metropolitan Statistical Area includes King County, Pierce County, and Snohomish County.

For more information

Answers to frequently asked questions about the OEWS data are available at www.bls.gov/oes/oes_ques.htm. Detailed information about the OEWS program is available at www.bls.gov/oes/oes_doc.htm.

Information in this release will be made available to individuals with sensory impairments upon request. Voice phone: (202) 691-5200; Telecommunications Relay Service: 7-1-1.

Table 1. Employment and wage data for computer and mathematical occupations, Seattle metropolitan area, May 2022
Occupation (1) Employment Mean wages ($)
Level (2) Location quotient (3) Hourly Annual (4)

Computer and mathematical occupations

170,030 2.5 65.19 135,590

Computer systems analysts

13,350 1.9 62.53 130,070

Information security analysts

4,280 1.9 65.59 136,430

Computer and information research scientists

910 2.0 95.49 198,610

Computer network support specialists

3,190 1.4 42.80 89,030

Computer user support specialists

14,100 1.5 36.00 74,870

Computer network architects

3,100 1.3 74.69 155,360

Database administrators

1,180 1.1 56.48 117,480

Database architects

2,740 3.2 79.01 164,350

Network and computer systems administrators

4,870 1.1 53.30 110,870

Computer programmers

2,020 1.1 64.30 133,750

Software developers

80,770 3.8 74.85 155,680

Software quality assurance analysts and testers

10,220 3.8 54.98 114,370

Web developers

5,230 4.3 68.36 142,200

Web and digital interface designers

6,120 4.6 58.53 121,750

Computer occupations, all other

10,360 1.8 55.13 114,670

Actuaries

200 0.6 61.99 128,940

Mathematicians

90 3.1 65.27 135,750

Operations research analysts

2,030 1.4 45.81 95,290

Statisticians

1,190 2.8 53.92 112,160

Data scientists

3,610 1.6 68.66 142,810

Mathematical science occupations, all other

480 9.1 34.26 71,260

Footnotes:
(1) For a complete listing of all detailed occupations in the Seattle-Tacoma-Bellevue, WA Metropolitan Statistical Area, see www.bls.gov/oes/current/oes_42660.htm.
(2) Estimates for detailed occupations may not sum to the totals due to rounding, and because the totals may include occupations that are 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.

 

Last Modified Date: Thursday, June 22, 2023