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Wednesday, May 20, 2020
Workers in the San Jose-Sunnyvale-Santa Clara, CA Metropolitan Statistical Area had an average (mean) hourly wage of $40.37 in May 2019, about 57 percent above the nationwide average of $25.72, the U.S. Bureau of Labor Statistics reported today. Assistant Commissioner for Regional Operations Richard Holden 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 healthcare practitioners and technical.
When compared to the nationwide distribution, San Jose area employment was more highly concentrated in 5 of the 22 occupational groups, including computer and mathematical, management, and architecture and engineering. Conversely, fifteen groups had employment shares significantly below their national representation, including transportation and material moving, office and administrative support, and healthcare practitioners and technical. (See table A and box note at end of release.)
|Major occupational group||Percent of total employment||Mean hourly wage|
|United States||San Jose||United States||San Jose||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 Jose had 144,530 jobs in computer and mathematical, accounting for 12.7 percent of local area employment, significantly higher than the 3.1-percent share nationally. The average hourly wage for this occupational group locally was $64.32, significantly above the national wage of $45.08.
Some of the larger detailed occupations within the computer and mathematical group included software developers and software quality assurance analysts and testers (81,950), computer user support specialists (12,850), and computer systems analysts (12,190). Among the higher-paying jobs in this group were computer and information research scientists and computer network architects, with mean hourly wages of $82.29 and $73.27, respectively. At the lower end of the wage scale were computer user support specialists ($39.28) and computer network support specialists ($40.08). (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_41940.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 Jose area, above-average concentrations of employment were found in many of the occupations within the computer and mathematical group. For instance, software developers and software quality assurance analysts and testers were employed at 7.5 times the national rate in San Jose, and computer network architects, at 2.8 times the U.S. average.
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 California Employment Development Department.
With the May 2019 estimates, the OES program has begun implementing the 2018 Standard Occupational Classification (SOC) system. Each set of OES estimates is calculated from six panels of survey data collected over three years. Because the May 2019 estimates are based on a combination of survey data collected using the 2010 SOC and survey data collected using the 2018 SOC, these estimates use a hybrid of the two classification systems that contains some combinations of occupations that are not found in either the 2010 or 2018 SOC. These combinations may include occupations from more than one 2018 SOC minor group or broad occupation. Therefore, OES will not publish data for some 2018 SOC minor groups and broad occupations in the May 2019 estimates. The May 2021 estimates, to be published in Spring 2022, will be the first OES estimates based entirely on survey data collected using the 2018 SOC.
In addition, the OES program has replaced some 2018 SOC detailed occupations with SOC broad occupations or OES-specific aggregations. These include home health aides and personal care aides, for which OES will publish only the 2018 SOC broad occupation 31-1120 Home Health and Personal Care Aides.
For more information on the occupational classification system used in the May 2019 OES estimates, please see www.bls.gov/oes/soc_2018.htm and www.bls.gov/oes/oes_ques.htm#qf10.
The May 2019 OES estimates use the metropolitan area definitions delineated in Office of Management and Budget (OMB) Bulletin 17-01, which add a new Metropolitan Statistical Area (MSA) for Twin Falls, Idaho. For more information on the area definitions used in the May 2019 estimates, please see www.bls.gov/oes/current/msa_def.htm.
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 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. OES data are available at www.bls.gov/oes/tables.htm.
The OES 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. OES estimates are constructed from a sample of about 1.1 million establishments. Each year, two semiannual panels of approximately 180,000 to 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 2019 estimates are based on responses from six semiannual panels collected over a 3-year period: May 2019, November 2018, May 2018, November 2017, May 2017, and November 2016. The unweighted sample employment of 83 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 71 percent based on establishments and 68 percent based on weighted sampled employment. The sample in the San Jose-Sunnyvale-Santa Clara, CA Metropolitan Statistical Area included 4,800 establishments with a response rate of 57 percent. For more information about OES 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.
The May 2019 OES estimates are the first set of OES estimates to be based in part on survey data collected using the 2018 SOC. These estimates use a hybrid of the 2010 and 2018 SOC systems. More information on the hybrid classification system is available at www.bls.gov/oes/soc_2018.htm.
The May 2019 OES estimates are based on the 2017 North American Industry Classification System (NAICS). More 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 San Jose-Sunnyvale-Santa Clara, CA Metropolitan Statistical Area includes San Benito and Santa Clara Counties.
For more information
Answers to frequently asked questions about the OES data are available at www.bls.gov/oes/oes_ques.htm. Detailed information about the OES program is available at www.bls.gov/oes/oes_doc.htm.
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.
|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
Database administrators and architects
Software developers and software quality assurance analysts and testers
Web developers and digital interface designers
Computer occupations, all other
Operations research analysts
Data scientists and mathematical science occupations, all other
Last Modified Date: Wednesday, May 20, 2020