87 datasets found
  1. National Compensation Survey - Modeled Wage Estimates

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

  2. Data from: Occupational Employment Statistics

    • icpsr.umich.edu
    Updated Jun 26, 2015
    + more versions
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    United States Department of Labor. Bureau of Labor Statistics (2015). Occupational Employment Statistics [Dataset]. https://www.icpsr.umich.edu/web/NADAC/studies/36219
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    Dataset updated
    Jun 26, 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/36219/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/36219/terms

    Area covered
    Virgin Islands of the United States, United States, Puerto Rico, Guam
    Description

    The Occupational Employment Statistics (OES) program conducts a semiannual survey designed 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 for the nation as a whole, by state, by metropolitan or nonmetropolitan area, and by industry or ownership. The Bureau of Labor Statistics produces occupational employment and wage estimates for approximately 415 industry classifications at the national level. The industry classifications correspond to the sector, 3-, 4-, and selected 5- and 6-digit North American Industry Classification System (NAICS) industrial groups. The OES program surveys approximately 200,000 establishments per panel (every six months), taking three years to fully collect the sample of 1.2 million establishments. To reduce respondent burden, the collection is on a three-year survey cycle that ensures that establishments are surveyed at most once every three years. The estimates for occupations in nonfarm establishments are based on OES data collected for the reference months of May and November. The OES survey is a federal-state cooperative program between the Bureau of Labor Statistics (BLS) and State Workforce Agencies (SWAs). 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 OES survey make these estimates possible. The OES features several arts-related occupations, particularly in the Arts, Design, Entertainment, Sports, and Media Occupations group (Standard Occupational Classification (SOC) code 27-0000). Several featured occupation groups include the following: Art and Design Workers (SOC 27-1000) Art Directors Fine Artists, including Painters, Sculptors, and Illustrators Multimedia Artists and Animators Fashion Designers Graphic Designers Set and Exhibit Designers Entertainers and Performers, Sports and Related Workers (SOC 27-2000) Actors Producers and Directors Athletes Coaches and Scouts Dancers Choreographers Music Directors and Composers Musicians and Singers Media and Communication Workers (SOC 27-3000) Radio and Television Announcers Reports and Correspondents Public Relations Specialists Writers and Authors Data for years 1997 through the latest release and can be found on the OES Data page. Also, see OES News Releases sections for current estimates and news releases. Users can analyze the data for the nation as a whole, by state, by metropolitan or nonmetropolitan area, and by industry or ownership. As well, OES Charts are available. Users may also explore data using OES Maps. If preferred, data can also be accessed via the Multi-Screen Data Search or Text Files using the OES Databases page.

  3. Jobs paid below minimum wage by category

    • ons.gov.uk
    • cy.ons.gov.uk
    xls
    Updated Oct 23, 2025
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    Office for National Statistics (2025). Jobs paid below minimum wage by category [Dataset]. https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/earningsandworkinghours/datasets/jobspaidbelowminimumwagebycategory
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    xlsAvailable download formats
    Dataset updated
    Oct 23, 2025
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Number of UK jobs paid below minimum wage by sex, age, occupation and industry, and region. Annual estimates, 1998 to 2025. Annual Survey of Hours and Earnings.

  4. Wage Estimates

    • kaggle.com
    zip
    Updated Jun 29, 2017
    + more versions
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    US Bureau of Labor Statistics (2017). Wage Estimates [Dataset]. https://www.kaggle.com/bls/wage-estimates
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    zip(4529907 bytes)Available download formats
    Dataset updated
    Jun 29, 2017
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    Authors
    US Bureau of Labor Statistics
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context:

    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. 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.

    Direct estimates are based on survey responses only from the particular geographic area to which the estimate refers. In contrast, modeled wage estimates use survey responses from larger areas to fill in information for smaller areas where the sample size is not sufficient to produce direct estimates. Modeled wage estimates require the assumption that the patterns to responses in the larger area hold in the smaller area.

    The sample size for the NCS is not large enough to produce direct estimates by area, occupation, and job characteristic for all of the areas for which the OES publishes estimates by area and occupation. The NCS sample consists of 6 private industry panels with approximately 3,300 establishments sampled per panel, and 1,600 sampled state and local government units. The OES full six-panel sample consists of nearly 1.2 million establishments.

    The sample establishments are classified in industry categories based on the North American Industry Classification System (NAICS). Within an establishment, specific job categories are selected to represent broader occupational definitions. Jobs are classified according to the Standard Occupational Classification (SOC) system.

    Content:

    Summary: Average hourly wage estimates for civilian workers in occupations by job characteristic and work levels. These data are available at the national, state, metropolitan, and nonmetropolitan area levels.

    Frequency of Observations: Data are available on an annual basis, typically in May.

    Data Characteristics: All hourly wages are published to the nearest cent.

    Acknowledgements:

    This dataset was taken directly from the Bureau of Labor Statistics and converted to CSV format.

    Inspiration:

    This dataset contains the estimated wages of civilian workers in the United States. Wage changes in certain industries may be indicators for growth or decline. Which industries have had the greatest increases in wages? Combine this dataset with the Bureau of Labor Statistics Consumer Price Index dataset and find out what kinds of jobs you would need to afford your snacks and instant coffee!

  5. Wages

    • open.canada.ca
    csv
    Updated Nov 19, 2025
    + more versions
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    Employment and Social Development Canada (2025). Wages [Dataset]. https://open.canada.ca/data/en/dataset/adad580f-76b0-4502-bd05-20c125de9116
    Explore at:
    csvAvailable download formats
    Dataset updated
    Nov 19, 2025
    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

  6. 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
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    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.

  7. Employment Cost Index

    • catalog.data.gov
    Updated May 16, 2022
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    Bureau of Labor Statistics (2022). Employment Cost Index [Dataset]. https://catalog.data.gov/dataset/employment-cost-index-24b79
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    Dataset updated
    May 16, 2022
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    Description

    The Employment Cost Index (ECI) component of the National Compensation Survey (NCS) that measures changes in labor costs. The ECI is a quarterly measure of the change in the cost of labor, free from the influence of employment shifts among occupations and industries. The compensation series includes changes in wages and salaries plus employer costs for employee benefits. The wage and salary series and benefit series provide the change for the two components of compensation. Employee benefit costs are calculated as cost-per-hour-worked for 21 benefits, ranging from employer payments for Social Security to paid time off for holidays. For information and data please visit: https://www.bls.gov/ncs/

  8. T

    United States Employment Rate

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Sep 15, 2025
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    TRADING ECONOMICS (2025). United States Employment Rate [Dataset]. https://tradingeconomics.com/united-states/employment-rate
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    excel, xml, json, csvAvailable download formats
    Dataset updated
    Sep 15, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 31, 1948 - Sep 30, 2025
    Area covered
    United States
    Description

    Employment Rate in the United States increased to 59.70 percent in September from 59.60 percent in August of 2025. This dataset provides - United States Employment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

  9. 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

  10. F

    Employment Cost Index: Wages and salaries for All Civilian workers in All...

    • fred.stlouisfed.org
    json
    Updated Jul 31, 2025
    + more versions
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    (2025). Employment Cost Index: Wages and salaries for All Civilian workers in All industries and occupations [Dataset]. https://fred.stlouisfed.org/series/CIS1020000000000I
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 31, 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 for All Civilian workers in All industries and occupations (CIS1020000000000I) from Q1 2001 to Q2 2025 about ECI, occupation, civilian, salaries, workers, wages, industry, and USA.

  11. 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.

  12. Wage rates by occupation

    • open.canada.ca
    • data.ontario.ca
    docx, html, zip
    Updated Nov 12, 2025
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    Government of Ontario (2025). Wage rates by occupation [Dataset]. https://open.canada.ca/data/dataset/1dc7cdcd-5a1c-450a-9544-2a98a3011d61
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    docx, zip, htmlAvailable download formats
    Dataset updated
    Nov 12, 2025
    Dataset provided by
    Government of Ontariohttps://www.ontario.ca/
    License

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

    Time period covered
    Jan 1, 2001 - Dec 31, 2015
    Description

    Occupations are classified using the three digit National Occupational Classification (NOC) codes. Wages include: average hourly wage rate, average weekly wage rate, median hourly wage rate and median weekly wage rate.

  13. U.S. unemployment rate 2025, by occupation

    • statista.com
    Updated Sep 15, 2025
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    Statista (2025). U.S. unemployment rate 2025, by occupation [Dataset]. https://www.statista.com/statistics/217782/unemployment-rate-in-the-united-states-by-occupation/
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    Dataset updated
    Sep 15, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Aug 2025
    Area covered
    United States
    Description

    In August 2025, the unemployment rate for those aged 16 and over in the United States came to 4.5 percent. Service occupations had an unemployment rate of 5.7 percent in that month. The underemployment rate of the country can be accessed here and the monthly unemployment rate here. Unemployment by occupation in the U.S. The United States Bureau of Labor Statistics publish data on the unemployment situation within certain occupations in the United States on a monthly basis. According to latest data released from May 2023, transportation and material moving occupations experienced the highest level of unemployment that month, with a rate of around 5.6 percent. Second ranked was farming, fishing, and forestry occupations with a rate of 4.9 percent. Total (not seasonally adjusted) unemployment was reported at 3.6 percent in March 2023. Other data on the U.S. unemployment rate by industry and class of worker shows comparable results. It should be noted that the data were not seasonally adjusted to account for normal seasonal fluctuations in unemployment. The monthly unemployment by occupation data can be compared to the seasonally adjusted monthly unemployment rate. In March 2023, the seasonally adjusted unemployment rate was 3.5 percent, which was an increase from the previous month. The annual unemployment rate in 2022 was 3.6 percent, down from a high of 9.6 in 2010. Unemployment in the United States trended downward after the coronavirus pandemic, and is now experiencing consistently low rates - a sign of economic stability. Individuals who opt to leave the workforce and stop looking for employment are not included among the unemployed. The civilian labor force participation rate in the U.S. rose to 62.2 percent in 2022, down from 67.1 percent in 2000, before the financial crisis.

  14. Labour statistics consistent with the System of National Accounts (SNA), by...

    • www150.statcan.gc.ca
    • open.canada.ca
    • +1more
    Updated May 20, 2025
    + more versions
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    Government of Canada, Statistics Canada (2025). Labour statistics consistent with the System of National Accounts (SNA), by job category and industry [Dataset]. http://doi.org/10.25318/3610048901-eng
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    Dataset updated
    May 20, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Labour statistics by job category, for Canada, the provinces and territories, annual.

  15. Total employment figures and unemployment rate in the United States...

    • statista.com
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    Statista, Total employment figures and unemployment rate in the United States 1980-2025 [Dataset]. https://www.statista.com/statistics/269959/employment-in-the-united-states/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2025, it was estimated that over 163 million Americans were in some form of employment, while 4.16 percent of the total workforce was unemployed. This was the lowest unemployment rate since the 1950s, although these figures are expected to rise in 2023 and beyond. 1980s-2010s Since the 1980s, the total United States labor force has generally risen as the population has grown, however, the annual average unemployment rate has fluctuated significantly, usually increasing in times of crisis, before falling more slowly during periods of recovery and economic stability. For example, unemployment peaked at 9.7 percent during the early 1980s recession, which was largely caused by the ripple effects of the Iranian Revolution on global oil prices and inflation. Other notable spikes came during the early 1990s; again, largely due to inflation caused by another oil shock, and during the early 2000s recession. The Great Recession then saw the U.S. unemployment rate soar to 9.6 percent, following the collapse of the U.S. housing market and its impact on the banking sector, and it was not until 2016 that unemployment returned to pre-recession levels. 2020s 2019 had marked a decade-long low in unemployment, before the economic impact of the Covid-19 pandemic saw the sharpest year-on-year increase in unemployment since the Great Depression, and the total number of workers fell by almost 10 million people. Despite the continuation of the pandemic in the years that followed, alongside the associated supply-chain issues and onset of the inflation crisis, unemployment reached just 3.67 percent in 2022 - current projections are for this figure to rise in 2023 and the years that follow, although these forecasts are subject to change if recent years are anything to go by.

  16. s

    Data from: Employment by occupation

    • ethnicity-facts-figures.service.gov.uk
    csv
    Updated Jul 27, 2022
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    Race Disparity Unit (2022). Employment by occupation [Dataset]. https://www.ethnicity-facts-figures.service.gov.uk/work-pay-and-benefits/employment/employment-by-occupation/latest
    Explore at:
    csv(309 KB)Available download formats
    Dataset updated
    Jul 27, 2022
    Dataset authored and provided by
    Race Disparity Unit
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    United Kingdom
    Description

    39.8% of workers from the Indian ethnic group were in 'professional' jobs in 2021 – the highest percentage out of all ethnic groups in this role.

  17. i

    Average wages of the main job by period, type of working day, occupation and...

    • ine.es
    csv, html, json +4
    Updated Nov 14, 2025
    + more versions
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    INE - Instituto Nacional de Estadística (2025). Average wages of the main job by period, type of working day, occupation and decile [Dataset]. https://www.ine.es/jaxiT3/Tabla.htm?t=66244&L=1
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    xls, txt, csv, json, xlsx, text/pc-axis, htmlAvailable download formats
    Dataset updated
    Nov 14, 2025
    Dataset authored and provided by
    INE - Instituto Nacional de Estadística
    License

    https://www.ine.es/aviso_legalhttps://www.ine.es/aviso_legal

    Time period covered
    Jan 1, 2011 - Jan 1, 2024
    Variables measured
    Decile, Employment, Type of data, National Total, Type of working day, Salary/Labour Line Items
    Description

    Economically Active Population Survey: Average wages of the main job by period, type of working day, occupation and decile. Annual. National.

  18. EARN06: Gross weekly earnings by occupation

    • ons.gov.uk
    • cy.ons.gov.uk
    xls
    Updated Nov 11, 2025
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    Office for National Statistics (2025). EARN06: Gross weekly earnings by occupation [Dataset]. https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/earningsandworkinghours/datasets/grossweeklyearningsbyoccupationearn06
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    xlsAvailable download formats
    Dataset updated
    Nov 11, 2025
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Gross weekly and hourly earnings by level of occupation, UK, quarterly, not seasonally adjusted. Labour Force Survey. These are official statistics in development.

  19. D

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

    • data.cdc.gov
    csv, xlsx, xml
    Updated May 14, 2025
    + more versions
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    NCHS/Division of Analysis and Epidemiology (2025). DQS Health care employment and wages, by selected occupations: United States [Dataset]. https://data.cdc.gov/National-Center-for-Health-Statistics/DQS-Health-care-employment-and-wages-by-selected-o/7siw-u4fz
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    xlsx, csv, xmlAvailable download formats
    Dataset updated
    May 14, 2025
    Dataset authored and provided by
    NCHS/Division of Analysis and Epidemiology
    License

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

    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 a wide range of health topics with the NCHS Data Query System (DQS), available from: https://www.cdc.gov/nchs/dataquery/index.htm.

  20. EMP13: Employment by industry

    • ons.gov.uk
    • cy.ons.gov.uk
    xls
    Updated Nov 11, 2025
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    Office for National Statistics (2025). EMP13: Employment by industry [Dataset]. https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/datasets/employmentbyindustryemp13
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Nov 11, 2025
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Employment by industry and sex, UK, published quarterly, non-seasonally adjusted. Labour Force Survey. These are official statistics in development.

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Bureau of Labor Statistics (2022). National Compensation Survey - Modeled Wage Estimates [Dataset]. https://catalog.data.gov/dataset/national-compensation-survey-modeled-wage-estimates-5de7e
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National Compensation Survey - Modeled Wage Estimates

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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.

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