Thursday, June 08, 2023
Workers in the San Francisco-Oakland-Hayward, CA Metropolitan Statistical Area had an average (mean) hourly wage of $45.37 in May 2022, 52 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 legal, management, and computer and mathematical.
When compared to the nationwide distribution, San Francisco area employment was more highly concentrated in 9 of the 22 occupational groups, including computer and mathematical, management, and business and financial operations. Thirteen groups had employment shares significantly below their national representation, including transportation and material moving, office and administrative support, and production. (See table A.)
|Major occupational group||Percent of total employment||Mean hourly wage|
|United States||San Francisco||United States||San Francisco||Percent difference (1)|
Total, all occupations
Business and financial operations
Computer and mathematical
Architecture and engineering
Life, physical, and social science
Community and social service
Educational instruction and library
Arts, design, entertainment, sports, and media
Healthcare practitioners and technical
Food preparation and serving related
Building and grounds cleaning and maintenance
Personal care and service
Sales and related
Office and administrative support
Farming, fishing, and forestry
Construction and extraction
Installation, maintenance, and repair
Transportation and material moving
One occupational group—computer and mathematical—was chosen to illustrate the diversity of data available for any of the 22 major occupational categories. San Francisco had 164,480 jobs in computer and mathematical, accounting for 6.9 percent of local area employment, significantly higher than the 3.4-percent share nationally. The average hourly wage for this occupational group locally was $74.76, significantly above the national wage of $51.99.
Some of the larger detailed occupations within the computer and mathematical group included software developers (67,010), computer systems analysts (12,690), and computer user support specialists (11,200). Among the higher-paying jobs in this group were computer and information research scientists and software developers, with mean hourly wages of $124.98 and $87.32, respectively. At the lower end of the wage scale were computer user support specialists ($40.10) and computer network support specialists ($45.92). (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_41860.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 San Francisco 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 4.1 times the national rate in San Francisco, and data scientists, at 3.4 times the U.S. average. Computer user support specialists had a location quotient of 1.0 in San Francisco, 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 California Employment Development Department.
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.
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 San Francisco-Oakland-Hayward, CA Metropolitan Statistical Area included 8,341 establishments with a response rate of 50 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 San Francisco-Oakland-Hayward, CA Metropolitan Statistical Area includes Alameda County, Contra Costa County, Marin County, San Francisco County, and San Mateo County.
For more information
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
Computer systems analysts
Information security analysts
Computer and information research scientists
Computer network support specialists
Computer user support specialists
Computer network architects
Network and computer systems administrators
Software quality assurance analysts and testers
Web and digital interface designers
Computer occupations, all other
Operations research analysts
Mathematical science occupations, all other
Last Modified Date: Thursday, June 08, 2023