79 datasets found
  1. Occupational Employment and Wage Statistics (OES)

    • catalog.data.gov
    • gimi9.com
    • +1more
    Updated May 16, 2022
    + more versions
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    Bureau of Labor Statistics (2022). Occupational Employment and Wage Statistics (OES) [Dataset]. https://catalog.data.gov/dataset/occupational-employment-and-wage-statistics-oes
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    Dataset updated
    May 16, 2022
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    Description

    The Occupational Employment and Wage Statistics (OES) program conducts a semi-annual survey to produce estimates of employment and wages for specific occupations. The OES program collects data on wage and salary workers in nonfarm establishments in order to produce employment and wage estimates for about 800 occupations. Data from self-employed persons are not collected and are not included in the estimates. The OES program produces these occupational estimates by geographic area and by industry. Estimates based on geographic areas are available at the National, State, Metropolitan, and Nonmetropolitan Area levels. The Bureau of Labor Statistics produces occupational employment and wage estimates for over 450 industry classifications at the national level. The industry classifications correspond to the sector, 3-, 4-, and 5-digit North American Industry Classification System (NAICS) industrial groups. More information and details about the data provided can be found at http://www.bls.gov/oes

  2. Occupational Employment and Wage Statistics (OEWS)

    • catalog.data.gov
    • data.ca.gov
    Updated Jul 23, 2025
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    California Employment Development Department (2025). Occupational Employment and Wage Statistics (OEWS) [Dataset]. https://catalog.data.gov/dataset/occupational-employment-and-wage-statistics-oews-4b4c4
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    Dataset updated
    Jul 23, 2025
    Dataset provided by
    Employment Development Departmenthttp://www.edd.ca.gov/
    Description

    The Occupational Employment and Wage Statistics (OEWS) Survey is a federal-state cooperative program between the Bureau of Labor Statistics (BLS) and State Workforce Agencies (SWAs). The BLS provides the procedures and technical support, draws the sample, and produces the survey materials, while the SWAs collect the data. SWAs from all fifty states, plus the District of Columbia, Puerto Rico, Guam, and the Virgin Islands participate in the survey. Occupational employment and wage rate estimates at the national level are produced by BLS using data from the fifty states and the District of Columbia. Employers who respond to states' requests to participate in the OEWS survey make these estimates possible. The OEWS survey collects data from a sample of establishments and calculates employment and wage estimates by occupation, industry, and geographic area. The semiannual survey covers all non-farm industries. Data are collected by the Employment Development Department in cooperation with the Bureau of Labor Statistics, US Department of Labor. The OEWS Program estimates employment and wages for approximately 830 occupations. It also produces employment and wage estimates for statewide, Metropolitan Statistical Areas (MSAs), and Balance of State areas. Estimates are a snapshot in time and should not be used as a time series. The OEWS estimates are published annually. SOURCE: https://www.bls.gov/oes/oes_emp.htm

  3. Bureau of Labor Statistics - Occupational Employment and Wage Statistics...

    • datalumos.org
    Updated Jul 8, 2025
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    United States Department of Labor. Bureau of Labor Statistics (2025). Bureau of Labor Statistics - Occupational Employment and Wage Statistics (OEWS) [Dataset]. http://doi.org/10.3886/E235441V1
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    Dataset updated
    Jul 8, 2025
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    United States Department of Laborhttp://www.dol.gov/
    Authors
    United States Department of Labor. Bureau of Labor Statistics
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The Occupational Employment and Wage Statistics (OEWS) program produces employment and wage estimates annually for approximately 830 occupations. These estimates are available for the nation as a whole, for individual states, and for metropolitan and nonmetropolitan areas; national occupational estimates for specific industries are also available.This resource contains OEWS estimates, including:National (XLSX): 1997-2024State (XLSX): 1997-2024Metropolitan and nonmetropolitan area (XLSX): 1997-2024National industry-specific and by ownership (XLSX): 1997-2024All data: 2011-2024Agricultural data supplement: 2011 onlyEstimates: 1988-1995 (HTML)Also see additional folders for:Research estimates: 2012-2023Featured tables (tables and charts): 2019-2024Additional tables: Various, 2011-2024Note that at present, this scrape does NOT include occupational profiles. This is due to issues scraping the most recent (2024) profiles from the web application. Will update with more clarification on whether we can indeed scrape these profiles, if we'll limit to 2023-and-earlier profiles, add to a separate project, etc.

  4. A

    Occupational Employment and Wage Estimates

    • data.amerigeoss.org
    • data.wu.ac.at
    csv, json, rdf, xml
    Updated Jul 2, 2019
    + more versions
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    United States (2019). Occupational Employment and Wage Estimates [Dataset]. https://data.amerigeoss.org/ja/dataset/occupational-employment-and-wage-estimates
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    rdf, csv, json, xmlAvailable download formats
    Dataset updated
    Jul 2, 2019
    Dataset provided by
    United States
    Description

    Washington State, metropolitan statistical areas (MSA) and nonmetropolitan areas (NMA), 2019 OES is a program of the U.S. Department of Labor, Bureau of Labor Statistics (BLS). This federal-state cooperative program produces employment and wage estimates for nearly 840 occupations. The occupational employment and wage estimates are based on data collected from the OES survey. The survey includes employment counts, occupations and wages from more than 4,800 Washington state employers. Data from six survey panels are combined to create a sample size of more than 29,300 employers. Blanks in the data columns indicate suppressed data.

  5. Modeled Wage Estimates

    • db.nomics.world
    Updated Aug 23, 2024
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    DBnomics (2024). Modeled Wage Estimates [Dataset]. https://db.nomics.world/BLS/wm
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    Dataset updated
    Aug 23, 2024
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    Authors
    DBnomics
    Description

    The Occupational Employment Statistics (OES) and National Compensation Survey (NCS) programs have produced estimates by borrowing from the strength and breadth of each survey to provide more details on occupational wages than either program provides individually. Modeled wage estimates provide annual estimates of average hourly wages for occupations by selected job characteristics and within geographical location.

  6. n

    Occupational Employment and Wage Statistics (OEWS) - May 2024

    • nectarin.com.ua
    Updated Nov 21, 2025
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    (2025). Occupational Employment and Wage Statistics (OEWS) - May 2024 [Dataset]. http://nectarin.com.ua/en/trades/electrician/texas
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    Dataset updated
    Nov 21, 2025
    Description

    Bureau of Labor Statistics dataset providing detailed wage and employment estimates for occupations in the United States.

  7. g

    Occupational Employment and Wage Statistics (OEWS) | gimi9.com

    • gimi9.com
    Updated Jul 26, 2017
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    (2017). Occupational Employment and Wage Statistics (OEWS) | gimi9.com [Dataset]. https://gimi9.com/dataset/california_oews
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    Dataset updated
    Jul 26, 2017
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The Occupational Employment and Wage Statistics (OEWS) Survey collects data from a sample of establishments and calculates employment and wage estimates by occupation, industry, and geographic area. The semiannual survey covers all non-farm industries. Data are collected by the Employment Development Department in cooperation with the Bureau of Labor Statistics, US Department of Labor. The OEWS Program estimates employment and wages for over 800 occupations from an annual sample of approx. 34,000 California employers. It also produces employment and wage estimates for statewide, Metropolitan Statistical Areas (MSAs), and Balance of State areas. Estimates are a snapshot in time and should not be used as a time series.

  8. S

    Data from: Occupational Employment and Wage Statistics

    • data.ny.gov
    • datasets.ai
    • +2more
    csv, xlsx, xml
    Updated Jul 2, 2025
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    New York State Department of Labor (2025). Occupational Employment and Wage Statistics [Dataset]. https://data.ny.gov/w/gkgz-nw24/caer-yrtv?cur=A9AAyAB1XPO
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    csv, xml, xlsxAvailable download formats
    Dataset updated
    Jul 2, 2025
    Dataset authored and provided by
    New York State Department of Labor
    Description

    The Occupational Employment and Wage Statistics (OEWS) survey is a semiannual mail survey of employers that measures occupational employment and occupational wage rates for wage and salary workers in nonfarm establishments, by industry. OEWS estimates are constructed from a sample of about 41,400 establishments. Each year, forms are mailed to two semiannual panels of approximately 6,900 sampled establishments, one panel in May and the other in November.

  9. V

    Texas Workforce Development Areas (WDA) Wages

    • data.virginia.gov
    csv
    Updated Oct 24, 2025
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    Datathon 2024 (2025). Texas Workforce Development Areas (WDA) Wages [Dataset]. https://data.virginia.gov/dataset/texas-workforce-development-areas-wda-wages
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    csv(3340241)Available download formats
    Dataset updated
    Oct 24, 2025
    Dataset authored and provided by
    Datathon 2024
    Description

    The Bureau of Labor Statistics (BLS) calculates employment and wage estimates for every state, Metropolitan Statistical Area and Balance-of-State area in the United States. In order to better meet the needs of local users, the Occupational Employment and Wage Statistics (OEWS) staff in the Texas Labor Market Information Department of the Texas Workforce Commission (LMI) has produced wage estimates for geographic areas not produced by BLS. Workforce Development Areas (WDAs) are not published by BLS and are not, therefore, official BLS data series. Due to confidentiality and quality criteria, LMI cannot produce estimates for every occupation in every geographic area.

  10. F

    Employed full time: Wage and salary workers: Personal care and service...

    • fred.stlouisfed.org
    json
    Updated Jan 22, 2025
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    (2025). Employed full time: Wage and salary workers: Personal care and service occupations: 16 years and over: Women [Dataset]. https://fred.stlouisfed.org/series/LEU0254708300A
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    jsonAvailable download formats
    Dataset updated
    Jan 22, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Employed full time: Wage and salary workers: Personal care and service occupations: 16 years and over: Women (LEU0254708300A) from 2000 to 2024 about hygiene, occupation, full-time, females, salaries, workers, 16 years +, wages, services, employment, and USA.

  11. Occupational Wages 2018 Labor and Industry

    • data.pa.gov
    csv, xlsx, xml
    Updated Nov 13, 2019
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    Department of Labor and Industry (2019). Occupational Wages 2018 Labor and Industry [Dataset]. https://data.pa.gov/Workforce-Development/Occupational-Wages-2018-Labor-and-Industry/mdvn-squs
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    xml, xlsx, csvAvailable download formats
    Dataset updated
    Nov 13, 2019
    Dataset provided by
    United States Department of Laborhttp://www.dol.gov/
    Authors
    Department of Labor and Industry
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    Represents a comprehensive collection of occupational wage data available for Pennsylvania. Data are collected through the Occupational Employment Statistics program in cooperation with the U.S. Department of Labor’s Bureau of Labor Statistics. Occupational wage information can be used as a reference by educators, PACareerLink® staff, career counselors, Workforce Development Boards, economic developers, program planners, and others.

    Technical Note Occupational wages do not represent a time series. Due to the prescribed production methodology, current occupational wages are not comparable to previously published occupational wages.

  12. Data from: Quarterly Census of Employment and Wages

    • icpsr.umich.edu
    Updated Oct 22, 2015
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    United States Department of Labor. Bureau of Labor Statistics (2015). Quarterly Census of Employment and Wages [Dataset]. https://www.icpsr.umich.edu/web/NADAC/studies/36312
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    Dataset updated
    Oct 22, 2015
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    United States Department of Labor. Bureau of Labor Statistics
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/36312/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/36312/terms

    Area covered
    United States
    Description

    The Quarterly Census of Employment and Wages (QCEW) program is a cooperative program involving the Bureau of Labor Statistics (BLS) of the United States Department of Labor and the State Employment Security Agencies (SESAs). The QCEW program produces a comprehensive tabulation of employment and wage information for workers covered by State unemployment insurance (UI) laws and Federal workers covered by the Unemployment Compensation for Federal Employees (UCFE) program. Publicly available data files include information on the number of establishments, monthly employment, and quarterly wages, by NAICS industry, by county, by ownership sector, for the entire United States. These data are aggregated to annual levels, to higher industry levels (NAICS industry groups, sectors, and supersectors), and to higher geographic levels (national, State, and Metropolitan Statistical Area (MSA)). To download and analyze QCEW data, users can begin on the QCEW Databases page. Downloadable data are available in formats such as text and CSV. Data for the QCEW program that are classified using the North American Industry Classification System (NAICS) are available from 1990 forward, and on a more limited basis from 1975 to 1989. These data provide employment and wage information for arts-related NAICS industries, such as: Arts, entertainment, and recreation (NAICS Code 71) Performing arts and spectator sports Museums, historical sites, zoos, and parks Amusements, gambling, and recreation Professional, scientific, and technical services (NAICS Code 54) Architectural services Graphic design services Photographic services Retail trade (NAICS Code 44-45) Sporting goods, hobby, book and music stores Book, periodical, and music stores Art dealers For years 1975-2000, data for the QCEW program provide employment and wage information for arts-related industries are based on the Standard Industrial Classification (SIC) system. These arts-related SIC industries include the following: Book stores (SIC 5942) Commercial photography (SIC Code 7335) Commercial art and graphic design (SIC Code 7336) Museums, Botanical, Zoological Gardens (SIC Code 84) Dance studios, schools, and halls (SIC Code 7911) Theatrical producers and services (SIC Code 7922) Sports clubs, managers, & promoters (SIC Code 7941) Motion Picture Services (SIC Code 78) The QCEW program serves as a near census of monthly employment and quarterly wage information by 6-digit NAICS industry at the national, state, and county levels. At the national level, the QCEW program provides employment and wage data for almost every NAICS industry. At the State and area level, the QCEW program provides employment and wage data down to the 6-digit NAICS industry level, if disclosure restrictions are met. Employment data under the QCEW program represent the number of covered workers who worked during, or received pay for, the pay period including the 12th of the month. Excluded are members of the armed forces, the self-employed, proprietors, domestic workers, unpaid family workers, and railroad workers covered by the railroad unemployment insurance system. Wages represent total compensation paid during the calendar quarter, regardless of when services were performed. Included in wages are pay for vacation and other paid leave, bonuses, stock options, tips, the cash value of meals and lodging, and in some States, contributions to deferred compensation plans (such as 401(k) plans). The QCEW program does provide partial information on agricultural industries and employees in private households. Data from the QCEW program serve as an important source for many BLS programs. The QCEW data are used as the benchmark source for employment by the Current Employment Statistics program and the Occupational Employment Statistics program. The UI administrative records collected under the QCEW program serve as a sampling frame for BLS establishment surveys. In addition, data from the QCEW program serve as a source to other Federal and State programs. The Bureau of Economic Analysis (BEA) of the Department of Commerce uses QCEW data as the base for developing the wage and salary component of personal income. The Employment and Training Administration (ETA) of the Department of Labor and the SESAs use QCEW data to administer the employment security program. The QCEW data accurately reflect the ex

  13. National Compensation Survey - Modeled Wage Estimates

    • s.cnmilf.com
    • catalog.data.gov
    Updated May 16, 2022
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    Bureau of Labor Statistics (2022). National Compensation Survey - Modeled Wage Estimates [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/national-compensation-survey-modeled-wage-estimates-5de7e
    Explore at:
    Dataset updated
    May 16, 2022
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    Description

    The National Compensation Survey (NCS) program produces information on wages by occupation for many metropolitan areas.The Modeled Wage Estimates (MWE) provide annual estimates of average hourly wages for occupations by selected job characteristics and within geographical _location. The job characteristics include bargaining status (union and nonunion), part- and full-time work status, incentive- and time-based pay, and work levels by occupation. The modeled wage estimates are produced using a statistical procedure that combines survey data collected by the National Compensation Survey (NCS) and the Occupational Employment Statistics (OES) programs. Borrowing from the strengths of the NCS, information on job characteristics and work levels, and from the OES, the occupational and geographic detail, the modeled wage estimates provide more detail on occupational average hourly wages than either program is able to provide separately. Wage rates for different work levels within occupation groups also are published. Data are available for private industry, State and local governments, full-time workers, part-time workers, and other workforce characteristics.

  14. Employment Projections (EP)

    • icpsr.umich.edu
    Updated May 29, 2024
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    U.S. Bureau of Labor Statistics (2024). Employment Projections (EP) [Dataset]. https://www.icpsr.umich.edu/web/NADAC/studies/39137
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    Dataset updated
    May 29, 2024
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    U.S. Bureau of Labor Statistics
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/39137/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/39137/terms

    Description

    The Employment Projections (EP) program offers insights into the labor market of the United States, projecting trends for the next decade across approximately 300 detailed industries and 800 occupations. The Bureau of Labor Statistics develops the National Employment Matrix as part of its ongoing Employment Projections program. Occupational classifications of the National Employment Matrix are based on the structure used by the Occupational Employment Statistics (OEWS) program, which is using the 2018 Standard Occupational Classification (SOC) system. Self-employed worker data are sourced from the Current Population Survey (CPS) and are distributed to relevant occupations through a crosswalk mechanism. The industrial structure relies on the 2017 North American Industry Classification System (NAICS), treating self-employment as a separate industry for analytical purposes. Arts-related occupations encompass various sectors, including motion picture and sound recording industries, broadcasting, performing arts, museums, amusement, publishing, education, design, media, and related fields. This comprehensive overview aids in understanding employment dynamics and trends within the arts and cultural sectors.

  15. DEV DQS Health care employment and wages, by selected occupations: United...

    • data.virginia.gov
    csv, json, rdf, xsl
    Updated Sep 2, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). DEV DQS Health care employment and wages, by selected occupations: United States [Dataset]. https://data.virginia.gov/dataset/dev-dqs-health-care-employment-and-wages-by-selected-occupations-united-states
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    rdf, json, csv, xslAvailable download formats
    Dataset updated
    Sep 2, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Area covered
    United States
    Description

    Data on health care employment and wages in the United States, by selected occupations. Data are from Health, United States. Source: U.S. Department of Labor, Bureau of Labor Statistics, Occupational Employment and Wage Statistics. Search, visualize, and download these and other estimates from over 120 health topics with the NCHS Data Query System (DQS), available from: https://www.cdc.gov/nchs/dataquery/index.htm.

  16. Occupation, Salary and Likelihood of Automation

    • kaggle.com
    zip
    Updated May 24, 2020
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    Larxel (2020). Occupation, Salary and Likelihood of Automation [Dataset]. https://www.kaggle.com/datasets/andrewmvd/occupation-salary-and-likelihood-of-automation
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    zip(260580 bytes)Available download formats
    Dataset updated
    May 24, 2020
    Authors
    Larxel
    Description

    About this Dataset

    This dataset combines automation probability data with a breakdown of the number of jobs and salary in each occupation by state within the USA. Automation probability was acquired from the work of Carl Benedikt Freyand Michael A. Osborne; State employment data is from the Bureau of Labor Statistics. Note that for simplicity of analysis, all jobs where data was not available or there were less than 10 employees were marked as zero.

    How to Cite this Dataset

    If you use this dataset in your research, please credit the authors.

    Salary Data

    @misc{u.s. bureau of labor statistics, title={Occupational Employment Statistics}, url={https://www.bls.gov/oes/current/oes_nat.htm}, journal={U.S. BUREAU OF LABOR STATISTICS}}

    Automation Data

    @article{frey_osborne_2017, title={The future of employment: How susceptible are jobs to computerisation?}, volume={114}, DOI={10.1016/j.techfore.2016.08.019}, journal={Technological Forecasting and Social Change}, author={Frey, Carl Benedikt and Osborne, Michael A.}, year={2017}, pages={254–280}}

    License

    License was not specified at the source.

    Splash Banner

    Photo by Alex Knight on Unsplash

  17. Quarterly Census of Employment and Wages (QCEW)

    • catalog.data.gov
    • data.ca.gov
    Updated Nov 23, 2025
    + more versions
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    California Employment Development Department (2025). Quarterly Census of Employment and Wages (QCEW) [Dataset]. https://catalog.data.gov/dataset/quarterly-census-of-employment-and-wages-qcew-a6fea
    Explore at:
    Dataset updated
    Nov 23, 2025
    Dataset provided by
    Employment Development Departmenthttp://www.edd.ca.gov/
    Description

    The Quarterly Census of Employment and Wages (QCEW) Program is a Federal-State cooperative program between the U.S. Department of Labor’s Bureau of Labor Statistics (BLS) and the California EDD’s Labor Market Information Division (LMID). The QCEW program produces a comprehensive tabulation of employment and wage information for workers covered by California Unemployment Insurance (UI) laws and Federal workers covered by the Unemployment Compensation for Federal Employees (UCFE) program. The QCEW program serves as a near census of monthly employment and quarterly wage information by 6-digit industry codes from the North American Industry Classification System (NAICS) at the national, state, and county levels. At the national level, the QCEW program publishes employment and wage data for nearly every NAICS industry. At the state and local area level, the QCEW program publishes employment and wage data down to the 6-digit NAICS industry level, if disclosure restrictions are met. In accordance with the BLS policy, data provided to the Bureau in confidence are used only for specified statistical purposes and are not published. The BLS withholds publication of Unemployment Insurance law-covered employment and wage data for any industry level when necessary to protect the identity of cooperating employers. Data from the QCEW program serve as an important input to many BLS programs. The Current Employment Statistics and the Occupational Employment Statistics programs use the QCEW data as the benchmark source for employment. The UI administrative records collected under the QCEW program serve as a sampling frame for the BLS establishment surveys. In addition, the data serve as an input to other federal and state programs. The Bureau of Economic Analysis (BEA) of the Department of Commerce uses the QCEW data as the base for developing the wage and salary component of personal income. The U.S. Department of Labor’s Employment and Training Administration (ETA) and California's EDD use the QCEW data to administer the Unemployment Insurance program. The QCEW data accurately reflect the extent of coverage of California’s UI laws and are used to measure UI revenues; national, state and local area employment; and total and UI taxable wage trends. The U.S. Department of Labor’s Bureau of Labor Statistics publishes new QCEW data in its County Employment and Wages news release on a quarterly basis. The BLS also publishes a subset of its quarterly data through the Create Customized Tables system, and full quarterly industry detail data at all geographic levels. Disclaimer: For information regarding future updates or preliminary/final data releases, please refer to the Bureau of Labor Statistics Release Calendar: https://www.bls.gov/cew/release-calendar.htm

  18. T

    Utah Occupational Employment And Wages Data By Job

    • opendata.utah.gov
    • data.virginia.gov
    csv, xlsx, xml
    Updated Dec 23, 2014
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    Bureau of Labor Statistics (2014). Utah Occupational Employment And Wages Data By Job [Dataset]. https://opendata.utah.gov/w/88ws-42u9/u7hz-5yd9?cur=hux1K6I8uHS
    Explore at:
    xml, xlsx, csvAvailable download formats
    Dataset updated
    Dec 23, 2014
    Dataset authored and provided by
    Bureau of Labor Statistics
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Area covered
    Utah
    Description

    The Occupational Employment Statistics (OES) program produces employment and wage estimates annually for over 800 occupations. These estimates are available for the nation as a whole, for individual States, and for metropolitan and nonmetropolitan areas; national occupational estimates for specific industries are also available.

  19. V

    2023 Statewide Occupational Employment & Wages Report - Kentucky

    • data.virginia.gov
    csv
    Updated Oct 24, 2025
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    Datathon 2024 (2025). 2023 Statewide Occupational Employment & Wages Report - Kentucky [Dataset]. https://data.virginia.gov/dataset/2023-statewide-occupational-employment-wages-report-kentucky
    Explore at:
    csv(133281)Available download formats
    Dataset updated
    Oct 24, 2025
    Dataset authored and provided by
    Datathon 2024
    Area covered
    Kentucky
    Description

    The most recent statewide occupational estimates available. Produced in cooperation with the United States Bureau of Labor Statistics (BLS).

  20. T

    Vital Signs: Jobs by Wage Level - Metro

    • data.bayareametro.gov
    csv, xlsx, xml
    Updated Jan 18, 2019
    + more versions
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    (2019). Vital Signs: Jobs by Wage Level - Metro [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Jobs-by-Wage-Level-Metro/bt32-8udw
    Explore at:
    xlsx, csv, xmlAvailable download formats
    Dataset updated
    Jan 18, 2019
    Description

    VITAL SIGNS INDICATOR Jobs by Wage Level (EQ1)

    FULL MEASURE NAME Distribution of jobs by low-, middle-, and high-wage occupations

    LAST UPDATED January 2019

    DESCRIPTION Jobs by wage level refers to the distribution of jobs by low-, middle- and high-wage occupations. In the San Francisco Bay Area, low-wage occupations have a median hourly wage of less than 80% of the regional median wage; median wages for middle-wage occupations range from 80% to 120% of the regional median wage, and high-wage occupations have a median hourly wage above 120% of the regional median wage.

    DATA SOURCE California Employment Development Department OES (2001-2017) http://www.labormarketinfo.edd.ca.gov/data/oes-employment-and-wages.html

    American Community Survey (2001-2017) http://api.census.gov

    CONTACT INFORMATION vitalsigns.info@bayareametro.gov

    METHODOLOGY NOTES (across all datasets for this indicator) Jobs are determined to be low-, middle-, or high-wage based on the median hourly wage of their occupational classification in the most recent year. Low-wage jobs are those that pay below 80% of the regional median wage. Middle-wage jobs are those that pay between 80% and 120% of the regional median wage. High-wage jobs are those that pay above 120% of the regional median wage. Regional median hourly wages are estimated from the American Community Survey and are published on the Vital Signs Income indicator page. For the national context analysis, occupation wage classifications are unique to each metro area. A low-wage job in New York, for instance, may be a middle-wage job in Miami. For the Bay Area in 2017, the median hourly wage for low-wage occupations was less than $20.86 per hour. For middle-wage jobs, the median ranged from $20.86 to $31.30 per hour; and for high-wage jobs, the median wage was above $31.30 per hour.

    Occupational employment and wage information comes from the Occupational Employment Statistics (OES) program. Regional and subregional data is published by the California Employment Development Department. Metro data is published by the Bureau of Labor Statistics. The OES program collects data on wage and salary workers in nonfarm establishments to produce employment and wage estimates for some 800 occupations. Data from non-incorporated self-employed persons are not collected, and are not included in these estimates. Wage estimates represent a three-year rolling average.

    Due to changes in reporting during the analysis period, subregion data from the EDD OES have been aggregated to produce geographies that can be compared over time. West Bay is San Mateo, San Francisco, and Marin counties. North Bay is Sonoma, Solano and Napa counties. East Bay is Alameda and Contra Costa counties. South Bay is Santa Clara County from 2001-2004 and Santa Clara and San Benito counties from 2005-2017.

    Due to changes in occupation classifications during the analysis period, all occupations have been reassigned to 2010 SOC codes. For pre-2009 reporting years, all employment in occupations that were split into two or more 2010 SOC occupations are assigned to the first 2010 SOC occupation listed in the crosswalk table provided by the Census Bureau. This method assumes these occupations always fall in the same wage category, and sensitivity analysis of this reassignment method shows this is true in most cases.

    In order to use OES data for time series analysis, several steps were taken to handle missing wage or employment data. For some occupations, such as airline pilots and flight attendants, no wage information was provided and these were removed from the analysis. Other occupations did not record a median hourly wage (mostly due to irregular work hours) but did record an annual average wage. Nearly all these occupations were in education (i.e. teachers). In this case, a 2080 hour-work year was assumed and [annual average wage/2080] was used as a proxy for median income. Most of these occupations were classified as high-wage, thus dispelling concern of underestimating a median wage for a teaching occupation that requires less than 2080 hours of work a year (equivalent to 12 months fulltime). Finally, the OES has missing employment data for occupations across the time series. To make the employment data comparable between years, gaps in employment data for occupations are ‘filled-in’ using linear interpolation if there are at least two years of employment data found in OES. Occupations with less than two years of employment data were dropped from the analysis. Over 80% of interpolated cells represent missing employment data for just one year in the time series. While this interpolating technique may impact year-over-year comparisons, the long-term trends represented in the analysis generally are accurate.

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Bureau of Labor Statistics (2022). Occupational Employment and Wage Statistics (OES) [Dataset]. https://catalog.data.gov/dataset/occupational-employment-and-wage-statistics-oes
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Occupational Employment and Wage Statistics (OES)

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17 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
May 16, 2022
Dataset provided by
Bureau of Labor Statisticshttp://www.bls.gov/
Description

The Occupational Employment and Wage Statistics (OES) program conducts a semi-annual survey to produce estimates of employment and wages for specific occupations. The OES program collects data on wage and salary workers in nonfarm establishments in order to produce employment and wage estimates for about 800 occupations. Data from self-employed persons are not collected and are not included in the estimates. The OES program produces these occupational estimates by geographic area and by industry. Estimates based on geographic areas are available at the National, State, Metropolitan, and Nonmetropolitan Area levels. The Bureau of Labor Statistics produces occupational employment and wage estimates for over 450 industry classifications at the national level. The industry classifications correspond to the sector, 3-, 4-, and 5-digit North American Industry Classification System (NAICS) industrial groups. More information and details about the data provided can be found at http://www.bls.gov/oes

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