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22-1412-SAN
Thursday, July 07, 2022
Workers in the Seattle-Tacoma-Bellevue, WA Metropolitan Statistical Area had an average (mean) hourly wage of $36.62 in May 2021, about 31 percent above the nationwide average of $28.01, 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 computer and mathematical, management, and healthcare practitioners and technical.
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. Thirteen groups had employment shares significantly below their national representation, including production, healthcare practitioners and technical, and educational instruction and library. (See table A.)
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 | $28.01 | $36.62* | 31 |
Management | 6.3 | 5.7* | 59.31 | 73.64* | 24 |
Business and financial operations | 6.4 | 8.9* | 39.72 | 46.83* | 18 |
Computer and mathematical | 3.3 | 8.4* | 48.01 | 62.45* | 30 |
Architecture and engineering | 1.7 | 2.5* | 44.10 | 52.05* | 18 |
Life, physical, and social science | 0.9 | 1.2* | 38.81 | 43.32* | 12 |
Community and social service | 1.6 | 1.6 | 25.94 | 29.28* | 13 |
Legal | 0.8 | 0.8 | 54.38 | 56.05 | 3 |
Educational instruction and library | 5.8 | 4.8* | 29.88 | 34.19* | 14 |
Arts, design, entertainment, sports, and media | 1.3 | 1.6* | 31.78 | 36.75* | 16 |
Healthcare practitioners and technical | 6.2 | 5.0* | 43.80 | 53.94* | 23 |
Healthcare support | 4.7 | 4.1* | 16.02 | 20.36* | 27 |
Protective service | 2.4 | 1.9* | 25.68 | 32.31* | 26 |
Food preparation and serving related | 8.0 | 6.9* | 14.16 | 19.41* | 37 |
Building and grounds cleaning and maintenance | 2.9 | 2.3* | 16.23 | 20.30* | 25 |
Personal care and service | 1.8 | 1.9 | 16.17 | 20.94* | 29 |
Sales and related | 9.4 | 9.0* | 22.15 | 27.72* | 25 |
Office and administrative support | 13.0 | 12.5* | 20.88 | 25.32* | 21 |
Farming, fishing, and forestry | 0.3 | 0.1* | 16.70 | 21.37* | 28 |
Construction and extraction | 4.2 | 4.8* | 26.87 | 35.84* | 33 |
Installation, maintenance, and repair | 4.0 | 3.4* | 25.66 | 31.23* | 22 |
Production | 6.0 | 4.6* | 20.71 | 25.93* | 25 |
Transportation and material moving | 9.0 | 8.1* | 19.88 | 25.50* | 28 |
Footnotes: |
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 160,660 jobs in computer and mathematical, accounting for 8.4 percent of local area employment, significantly higher than the 3.3-percent share nationally. The average hourly wage for this occupational group locally was $62.45, significantly above the national wage of $48.01.
Some of the larger detailed occupations within the computer and mathematical group included software developers (73,860), web and digital interface designers (13,910), and computer user support specialists (12,670). Among the higher-paying jobs in this group were database architects and software developers, with mean hourly wages of $75.25 and $71.26, respectively. At the lower end of the wage scale were computer user support specialists ($31.52) and computer network support specialists ($45.25). (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 12.4 times the national rate in Seattle, and software developers, at 4.0 times the U.S. average. Network and computer systems administrators had a location quotient of 1.3 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.
With the May 2021 estimates release, the Occupational Employment and Wage Statistics (OEWS) program has implemented a new model-based (MB3) estimation method. For more information, see the May 2021 Survey Methods and Reliability Statement at www.bls.gov/oes/methods_21.pdf and the Monthly Labor Review article at www.bls.gov/opub/mlr/2019/article/model-based-estimates-for-the-occupational-employment-statistics-program.htm. OEWS estimates for the years 2015-19 were recalculated using the new estimation method and are available as research estimates at www.bls.gov/oes/oes-mb3-methods.htm.
The May 2021 OEWS estimates are also the first estimates based entirely on survey data collected using the 2018 Standard Occupational Classification (SOC) system. To improve data quality, the OEWS program aggregates some occupations to the SOC broad occupation level or as OEWS-specific combinations of 2018 SOC detailed occupations.
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 2021 estimates are based on responses from six semiannual panels collected over a 3-year period: May 2021, November 2020, May 2020, November 2019, May 2019, and November 2018. The unweighted sampled employment of 82 million across all six semiannual panels represents approximately 62 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 67.2 percent based on establishments and 64.5 percent based on weighted sampled employment. The sample in the Seattle-Tacoma-Bellevue, WA Metropolitan Statistical Area included 7,039 establishments with a response rate of 70 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.
Occupation (1) | Employment | Mean wages | ||
---|---|---|---|---|
Level (2) | Location quotient (3) | Hourly | Annual (4) | |
Computer and mathematical occupations | 160,660 | 2.5 | $62.45 | $129,890 |
Computer systems analysts | 11,130 | 1.6 | 56.28 | 117,070 |
Information security analysts | 3,280 | 1.5 | 61.32 | 127,550 |
Computer and information research scientists | 2,030 | 4.8 | 68.30 | 142,070 |
Computer network support specialists | 2,350 | 1.0 | 45.25 | 94,120 |
Computer user support specialists | 12,670 | 1.4 | 31.52 | 65,560 |
Computer network architects | 2,660 | 1.2 | 65.43 | 136,100 |
Database administrators | 1,610 | 1.4 | 57.35 | 119,280 |
Database architects | 1,520 | 2.2 | 75.25 | 156,530 |
Network and computer systems administrators | 5,480 | 1.3 | 48.53 | 100,940 |
Computer programmers | 3,460 | 1.7 | (5) | (5) |
Software developers | 73,860 | 4.0 | 71.26 | 148,220 |
Software quality assurance analysts and testers | 9,110 | 3.5 | 51.33 | 106,760 |
Web developers | 2,190 | 1.9 | 52.22 | 108,610 |
Web and digital interface designers | 13,910 | 12.4 | 69.58 | 144,720 |
Computer occupations, all other | 10,150 | 2.0 | 47.98 | 99,800 |
Actuaries | 160 | 0.5 | 57.25 | 119,080 |
Operations research analysts | 1,260 | 0.9 | 51.80 | 107,730 |
Statisticians | 1,230 | 2.9 | 48.98 | 101,880 |
Data scientists | 2,120 | 1.5 | 65.34 | 135,900 |
Mathematical science occupations, all other | (5) | (5) | 35.31 | 73,450 |
Footnotes: |
Last Modified Date: Thursday, July 07, 2022