100+ datasets found
  1. c

    Occupational Employment and Wage Statistics (OEWS)

    • s.cnmilf.com
    • catalog.data.gov
    Updated Nov 27, 2024
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    California Employment Development Department (2024). Occupational Employment and Wage Statistics (OEWS) [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/occupational-employment-and-wage-statistics-oews-4b4c4
    Explore at:
    Dataset updated
    Nov 27, 2024
    Dataset provided by
    California Employment Development Department
    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.

  2. Occupational Employment and Wage Statistics (OEWS)

    • data.ca.gov
    csv
    Updated Jul 14, 2025
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    California Employment Development Department (2025). Occupational Employment and Wage Statistics (OEWS) [Dataset]. https://data.ca.gov/dataset/oews
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    csv(105364359)Available download formats
    Dataset updated
    Jul 14, 2025
    Dataset provided by
    Employment Development Departmenthttp://www.edd.ca.gov/
    Authors
    California Employment Development Department
    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 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. Occupational Employment and Wage Statistics (OES)

    • catalog.data.gov
    Updated May 16, 2022
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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

  4. d

    Data from: Occupational Employment and Wage Statistics

    • catalog.data.gov
    • datasets.ai
    • +1more
    Updated Jul 6, 2024
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    data.ny.gov (2024). Occupational Employment and Wage Statistics [Dataset]. https://catalog.data.gov/dataset/occupational-employment-statistics
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    data.ny.gov
    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.

  5. A

    ‘Occupational Employment and Wage Statistics (OEWS)’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Feb 12, 2022
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘Occupational Employment and Wage Statistics (OEWS)’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-occupational-employment-and-wage-statistics-oews-24e8/f471601e/?iid=008-422&v=presentation
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    Dataset updated
    Feb 12, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘Occupational Employment and Wage Statistics (OEWS)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/ec2114b7-6b39-4b40-bb5d-bdd65a1e2382 on 12 February 2022.

    --- Dataset description provided by original source is as follows ---

    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.

    --- Original source retains full ownership of the source dataset ---

  6. 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.

  7. T

    Vital Signs: Jobs by Wage Level - Metro

    • data.bayareametro.gov
    application/rdfxml +5
    Updated Jan 18, 2019
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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
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    csv, tsv, application/rssxml, application/rdfxml, xml, jsonAvailable 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.

  8. V

    Texas Workforce Development Areas (WDA) Wages

    • data.virginia.gov
    csv
    Updated Feb 28, 2024
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    Datathon 2024 (2024). 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
    Feb 28, 2024
    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.

  9. Quarterly Census of Employment and Wages (QCEW)

    • data.ca.gov
    csv
    Updated Apr 17, 2025
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    California Employment Development Department (2025). Quarterly Census of Employment and Wages (QCEW) [Dataset]. https://data.ca.gov/dataset/quarterly-census-of-employment-and-wages
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    csv(122096044), csv(122409749), csv(123773669), csv(120584322), csv(96028431), csv(58451932)Available download formats
    Dataset updated
    Apr 17, 2025
    Dataset provided by
    Employment Development Departmenthttp://www.edd.ca.gov/
    Authors
    California Employment Development Department
    License

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

    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.

  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
    Explore at:
    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, females, full-time, salaries, workers, 16 years +, wages, services, employment, and USA.

  11. 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

  12. F

    Employed full time: Wage and salary workers: Survey researchers occupations:...

    • fred.stlouisfed.org
    json
    Updated Jan 22, 2025
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    (2025). Employed full time: Wage and salary workers: Survey researchers occupations: 16 years and over: Women [Dataset]. https://fred.stlouisfed.org/series/LEU0257864200A
    Explore at:
    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: Survey researchers occupations: 16 years and over: Women (LEU0257864200A) from 2011 to 2024 about occupation, females, full-time, salaries, workers, 16 years +, wages, employment, and USA.

  13. F

    Employment Cost Index: Wages and Salaries: Private Industry Workers: Service...

    • fred.stlouisfed.org
    json
    Updated Apr 30, 2025
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    (2025). Employment Cost Index: Wages and Salaries: Private Industry Workers: Service Occupations [Dataset]. https://fred.stlouisfed.org/series/ECISRVWAG
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Apr 30, 2025
    License

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

    Description

    Graph and download economic data for Employment Cost Index: Wages and Salaries: Private Industry Workers: Service Occupations (ECISRVWAG) from Q1 2001 to Q1 2025 about ECI, occupation, salaries, workers, private industries, wages, services, private, industry, inflation, and USA.

  14. F

    Employed full time: Wage and salary workers: Police and sheriff's patrol...

    • fred.stlouisfed.org
    json
    Updated Jan 17, 2020
    + more versions
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    (2020). Employed full time: Wage and salary workers: Police and sheriff's patrol officers occupations: 16 years and over [Dataset]. https://fred.stlouisfed.org/series/LEU0254491900A
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jan 17, 2020
    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: Police and sheriff's patrol officers occupations: 16 years and over (LEU0254491900A) from 2000 to 2019 about police, occupation, full-time, salaries, workers, 16 years +, wages, employment, and USA.

  15. Occupation, Salary and Likelihood of Automation

    • kaggle.com
    Updated May 24, 2020
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    Larxel (2020). Occupation, Salary and Likelihood of Automation [Dataset]. https://www.kaggle.com/andrewmvd/occupation-salary-and-likelihood-of-automation/activity
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 24, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    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

  16. Wages

    • open.canada.ca
    • ouvert.canada.ca
    csv
    Updated Dec 12, 2024
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    Employment and Social Development Canada (2024). Wages [Dataset]. https://open.canada.ca/data/en/dataset/adad580f-76b0-4502-bd05-20c125de9116
    Explore at:
    csvAvailable download formats
    Dataset updated
    Dec 12, 2024
    Dataset provided by
    Ministry of Employment and Social Development of Canadahttp://esdc-edsc.gc.ca/
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    The wages on the Job Bank website are specific to an occupation and provide information on the earnings of workers at the regional level. Wages for most occupations are also provided at the national and provincial level. In Canada, all jobs are associated with one specific occupational grouping which is determined by the National Occupational Classification. For most occupations, a minimum, median and maximum wage estimates are displayed. They are update annually. If you have comments or questions regarding the wage information, please contact the Labour Market Information Division at: NC-LMI-IMT-GD@hrsdc-rhdcc.gc.ca

  17. V

    Employment First Annual OVR Outcomes Current Statewide Labor & Industry - PA...

    • data.virginia.gov
    csv
    Updated Feb 20, 2024
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    Datathon 2024 (2024). Employment First Annual OVR Outcomes Current Statewide Labor & Industry - PA [Dataset]. https://data.virginia.gov/dataset/employment-first-annual-ovr-outcomes-current-statewide-labor-industry-pa
    Explore at:
    csv(12236), csv(1336)Available download formats
    Dataset updated
    Feb 20, 2024
    Dataset authored and provided by
    Datathon 2024
    Area covered
    Pennsylvania
    Description

    The following are a selection of annual outcomes of services provided by the Pennsylvania's Department of Labor & Industry's Office of Vocational Rehabilitation. Outcomes include applicants and case outcomes including employment and wages.

    Key Footnotes: 1) Employed in Competitive Labor Market means employment at or above the minimum wage in settings where most employees do not have disabilities. 2) Estimated Taxes Paid are based on a standard deduction for the year, annual tax brackets and rates established by the IRS, and flat-rate FICA, state, and local taxes. 3) Estimated Total Government Savings are estimated federal, state, and local taxes paid plus annualized public support dollars at closure. 4) Average per Person Cost for a Competitive Employment Placement is the average individual "life of case" cost for all persons having a competitive employment outcome regardless of total number of years receiving services. 5) Average per Person Cost of Services is the average individual "life of case" cost for all persons having an employment outcome regardless of total number of years receiving services. 6) Source: U.S. Department of Labor, Bureau of Labor Statistics, May 2016 State Occupational Employment and Wage Estimates, Pennsylvania, https://www.bls.gov/oes/current/oes_pa.htm#00-0000.

  18. F

    Employed full time: Wage and salary workers: Millwrights occupations: 16...

    • fred.stlouisfed.org
    json
    Updated Jan 22, 2025
    + more versions
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    (2025). Employed full time: Wage and salary workers: Millwrights occupations: 16 years and over [Dataset]. https://fred.stlouisfed.org/series/LEU0254511600A
    Explore at:
    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: Millwrights occupations: 16 years and over (LEU0254511600A) from 2000 to 2024 about occupation, full-time, salaries, workers, 16 years +, wages, employment, and USA.

  19. F

    Employed full time: Wage and salary workers: Bakers occupations: 16 years...

    • fred.stlouisfed.org
    json
    Updated Jan 22, 2025
    + more versions
    Share
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    (2025). Employed full time: Wage and salary workers: Bakers occupations: 16 years and over: Men [Dataset]. https://fred.stlouisfed.org/series/LEU0254620400A
    Explore at:
    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: Bakers occupations: 16 years and over: Men (LEU0254620400A) from 2000 to 2024 about occupation, full-time, males, salaries, workers, 16 years +, wages, employment, and USA.

  20. p

    Employment First Annual OVR Outcomes Current Statewide Labor & Industry

    • data.pa.gov
    application/rdfxml +5
    Updated Feb 8, 2023
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    Department of Labor and Industry (2023). Employment First Annual OVR Outcomes Current Statewide Labor & Industry [Dataset]. https://data.pa.gov/Employment-First/Employment-First-Annual-OVR-Outcomes-Current-State/uimv-hpcj
    Explore at:
    csv, application/rdfxml, xml, application/rssxml, json, tsvAvailable download formats
    Dataset updated
    Feb 8, 2023
    Dataset authored and provided by
    Department of Labor and Industry
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Description

    The following are a selection of annual outcomes of services provided by the Pennsylvania's Department of Labor & Industry's Office of Vocational Rehabilitation. Outcomes include applicants and case outcomes including employment and wages.

    Key Footnotes: 1) Employed in Competitive Labor Market means employment at or above the minimum wage in settings where most employees do not have disabilities. 2) Estimated Taxes Paid are based on a standard deduction for the year, annual tax brackets and rates established by the IRS, and flat-rate FICA, state, and local taxes. 3) Estimated Total Government Savings are estimated federal, state, and local taxes paid plus annualized public support dollars at closure. 4) Average per Person Cost for a Competitive Employment Placement is the average individual "life of case" cost for all persons having a competitive employment outcome regardless of total number of years receiving services. 5) Average per Person Cost of Services is the average individual "life of case" cost for all persons having an employment outcome regardless of total number of years receiving services. 6) Source: U.S. Department of Labor, Bureau of Labor Statistics, May 2016 State Occupational Employment and Wage Estimates, Pennsylvania, https://www.bls.gov/oes/current/oes_pa.htm#00-0000.

Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
California Employment Development Department (2024). Occupational Employment and Wage Statistics (OEWS) [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/occupational-employment-and-wage-statistics-oews-4b4c4

Occupational Employment and Wage Statistics (OEWS)

Explore at:
Dataset updated
Nov 27, 2024
Dataset provided by
California Employment Development Department
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.

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