100+ datasets found
  1. National Compensation Survey - Modeled Wage Estimates

    • catalog.data.gov
    • gimi9.com
    • +1more
    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. Quarterly Census of Employment and Wages (QCEW)

    • catalog.data.gov
    • data.ca.gov
    Updated Nov 27, 2024
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    California Employment Development Department (2024). Quarterly Census of Employment and Wages (QCEW) [Dataset]. https://catalog.data.gov/dataset/quarterly-census-of-employment-and-wages-qcew-a6fea
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    Dataset updated
    Nov 27, 2024
    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.

  3. Data from: Occupational Employment Statistics

    • icpsr.umich.edu
    Updated Jun 26, 2015
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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
    Puerto Rico, United States, Virgin Islands of the United States, 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.

  4. F

    Average Hourly Earnings of All Employees, Total Private

    • fred.stlouisfed.org
    json
    Updated Mar 7, 2025
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    (2025). Average Hourly Earnings of All Employees, Total Private [Dataset]. https://fred.stlouisfed.org/series/CEU0500000003
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    jsonAvailable download formats
    Dataset updated
    Mar 7, 2025
    License

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

    Description

    Graph and download economic data for Average Hourly Earnings of All Employees, Total Private (CEU0500000003) from Mar 2006 to Feb 2025 about earnings, average, establishment survey, hours, wages, private, employment, and USA.

  5. F

    Employed full time: Median usual weekly real earnings: Wage and salary...

    • fred.stlouisfed.org
    json
    Updated Jan 22, 2025
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    (2025). Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 years and over: Men [Dataset]. https://fred.stlouisfed.org/series/LES1252881900Q
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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: Median usual weekly real earnings: Wage and salary workers: 16 years and over: Men (LES1252881900Q) from Q1 1979 to Q4 2024 about full-time, males, salaries, workers, earnings, 16 years +, wages, median, real, employment, and USA.

  6. 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.

  7. 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
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    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

  8. F

    Average Hourly Earnings of All Employees, Manufacturing

    • fred.stlouisfed.org
    json
    Updated Mar 7, 2025
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    (2025). Average Hourly Earnings of All Employees, Manufacturing [Dataset]. https://fred.stlouisfed.org/series/CES3000000003
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    jsonAvailable download formats
    Dataset updated
    Mar 7, 2025
    License

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

    Description

    Graph and download economic data for Average Hourly Earnings of All Employees, Manufacturing (CES3000000003) from Mar 2006 to Feb 2025 about earnings, establishment survey, hours, wages, manufacturing, employment, and USA.

  9. Current Employment Statistics (CES)

    • catalog.data.gov
    • data.ca.gov
    • +1more
    Updated Nov 27, 2024
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    California Employment Development Department (2024). Current Employment Statistics (CES) [Dataset]. https://catalog.data.gov/dataset/current-employment-statistics-ces-5540b
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    Dataset updated
    Nov 27, 2024
    Dataset provided by
    Employment Development Departmenthttp://www.edd.ca.gov/
    Description

    The Current Employment Statistics (CES) program is a Federal-State cooperative effort in which monthly surveys are conducted to provide estimates of employment, hours, and earnings based on payroll records of business establishments. The CES survey is based on approximately 119,000 businesses and government agencies representing approximately 629,000 individual worksites throughout the United States. CES data reflect the number of nonfarm, payroll jobs. It includes the total number of persons on establishment payrolls, employed full- or part-time, who received pay (whether they worked or not) for any part of the pay period that includes the 12th day of the month. Temporary and intermittent employees are included, as are any employees who are on paid sick leave or on paid holiday. Persons on the payroll of more than one establishment are counted in each establishment. CES data excludes proprietors, self-employed, unpaid family or volunteer workers, farm workers, and household workers. Government employment covers only civilian employees; it excludes uniformed members of the armed services. The Bureau of Labor Statistics (BLS) of the U.S. Department of Labor is responsible for the concepts, definitions, technical procedures, validation, and publication of the estimates that State workforce agencies prepare under agreement with BLS.

  10. U.S. wage and salary workers median hourly earnings 1979-2023

    • statista.com
    • flwrdeptvarieties.store
    Updated Jan 14, 2025
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    Statista (2025). U.S. wage and salary workers median hourly earnings 1979-2023 [Dataset]. https://www.statista.com/statistics/185335/median-hourly-earnings-of-wage-and-salary-workers/
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    Dataset updated
    Jan 14, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2023, the median hourly earnings of wage and salary workers in the United States was 19.24 U.S. dollars. This is an increase from 1979, when median hourly earnings were at 4.44 U.S. dollars. Hourly Workers The United States national minimum wage is 7.25 U.S. dollars per hour, which has been the minimum wage since 2009. However, each state has the agency to set their state minimum wage. Furthermore, some cities are able to create their minimum wage. Many argue that the minimum wage is too low and should be raised, because it is not considered a living wage. There has been a movement to raise the minimum wage to 15 U.S. dollars per hour, called “Fight for 15” which began in the early 2010s. While there has been no movement at the federal level, some states have moved to increase their minimum wages, with at least three states and the District of Columbia setting minimum wage rates at or above 15 dollars per hour. More recently, some proponents of increasing the minimum wage say that 15 dollars is too low, and lawmakers should strive toward a higher goal, especially given that a 2021 analysis found that the minimum wage in the U.S. should be 22.88 U.S. dollars if it grew at the same rate as economic productivity. Salary Workers On the other hand, salary workers in the United States do not get paid on an hourly basis. The median weekly earnings of salary workers have significantly increased since 1979. Asian salary workers had the highest hourly earnings in the U.S. in 2021. Among female salary workers, those ages 45 to 54 years old had the highest median hourly earnings in 2021, likewise for male salary workers.

  11. T

    United States Wages and Salaries Growth

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +17more
    csv, excel, json, xml
    Updated May 6, 2023
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    TRADING ECONOMICS (2023). United States Wages and Salaries Growth [Dataset]. https://tradingeconomics.com/united-states/wage-growth
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    csv, json, xml, excelAvailable download formats
    Dataset updated
    May 6, 2023
    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, 1960 - Jan 31, 2025
    Area covered
    United States
    Description

    Wages in the United States increased 4.46 percent in January of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Wages and Salaries Growth - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  12. d

    National Compensation Survey

    • catalog.data.gov
    Updated May 16, 2022
    + more versions
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    Bureau of Labor Statisticis (2022). National Compensation Survey [Dataset]. https://catalog.data.gov/dataset/national-compensation-survey-144ec
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    Dataset updated
    May 16, 2022
    Dataset provided by
    Bureau of Labor Statisticis
    Description

    The National Compensation Survey (NCS) provides comprehensive measures of occupational wages; employment cost trends, and benefit incidence and detailed plan provisions. Detailed occupational earnings are available for metropolitan and non-metropolitan areas, broad geographic regions, and on a national basis. The index component of the NCS (ECI) measures changes in labor costs. Average hourly employer cost for employee compensation is presented in the ECEC.

  13. Compensation of employees, employment; economic activity, National Accounts

    • staging.dexes.eu
    • cbs.nl
    • +1more
    atom, json
    Updated Mar 26, 2025
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    Centraal Bureau voor de Statistiek (2025). Compensation of employees, employment; economic activity, National Accounts [Dataset]. https://staging.dexes.eu/en/dataset/compensation-of-employees-employment-economic-activity-national-accounts
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    json, atomAvailable download formats
    Dataset updated
    Mar 26, 2025
    Dataset provided by
    Statistics Netherlands
    Authors
    Centraal Bureau voor de Statistiek
    License

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

    https://opendata.cbs.nl/ODataApi/OData/85919ENGhttps://opendata.cbs.nl/ODataApi/OData/85919ENG

    Description

    This table provides annual data about the compensation of employees, the wage costs and the labour volume of employees. Compensation of employees is classified in wages and salaries and employers' social contributions. The wage costs are the total of wages, social contributions paid by employers and taxes on wage costs minus wage cost subsidies. The labour volume is given in jobs (by sex and by full-time or part-time), full-time equivalent (fte), hours paid, hours agreed and hours worked. The table additionally provides the compensation of employees, wages and salaries and wage costs related to full-time equivalents and hours worked. Data available from: 1995 Status of the figures: Data from 1995 up to and including 2022 are final. Data over 2023 are provisional. Changes as of June 24th 2024: This is a new table. Statistics Netherlands has carried out a revision of the national accounts. New statistical sources, methods and concepts are implemented in the national accounts, in order to align the picture of the Dutch economy with all underlying source data and international guidelines for the compilation of the national accounts. This table contains revised data. For further information see section 3. When will new figures be published? Provisional data are published 6 months after the end of the reporting year. Final data are released 18 months after the end of the reporting year.

  14. F

    Total wages and salaries, BLS: Adjustment for wages and salaries not covered...

    • fred.stlouisfed.org
    json
    Updated Oct 2, 2024
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    (2024). Total wages and salaries, BLS: Adjustment for wages and salaries not covered or not fully covered by unemployment insurance [Dataset]. https://fred.stlouisfed.org/series/W873RC1A027NBEA
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    jsonAvailable download formats
    Dataset updated
    Oct 2, 2024
    License

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

    Description

    Graph and download economic data for Total wages and salaries, BLS: Adjustment for wages and salaries not covered or not fully covered by unemployment insurance (W873RC1A027NBEA) from 1982 to 2023 about covered, adjusted, insurance, salaries, wages, unemployment, GDP, and USA.

  15. EARN06: Gross weekly earnings by occupation

    • ons.gov.uk
    • cy.ons.gov.uk
    xls
    Updated Feb 18, 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
    Feb 18, 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.

  16. U

    United States Employment Cost Index (ECI): sa: Compensation: Civilian...

    • ceicdata.com
    Updated Mar 29, 2018
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    CEICdata.com (2018). United States Employment Cost Index (ECI): sa: Compensation: Civilian Workers [Dataset]. https://www.ceicdata.com/en/united-states/national-compensation-survey-employment-cost-index-dec-2005100/employment-cost-index-eci-sa-compensation-civilian-workers-
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    Dataset updated
    Mar 29, 2018
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Jun 1, 2015 - Mar 1, 2018
    Area covered
    United States
    Variables measured
    Employment
    Description

    United States Employment Cost Index (ECI): sa: Compensation: Civilian Workers data was reported at 132.500 Dec2005=100 in Mar 2018. This records an increase from the previous number of 131.400 Dec2005=100 for Dec 2017. United States Employment Cost Index (ECI): sa: Compensation: Civilian Workers data is updated quarterly, averaging 110.700 Dec2005=100 from Mar 2001 (Median) to Mar 2018, with 69 observations. The data reached an all-time high of 132.500 Dec2005=100 in Mar 2018 and a record low of 84.700 Dec2005=100 in Mar 2001. United States Employment Cost Index (ECI): sa: Compensation: Civilian Workers data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G072: National Compensation Survey: Employment Cost Index: Dec 2005=100.

  17. Compensation of employees, employment; quarterly, NA, 1995-q1 2024

    • cbs.nl
    • staging.dexes.eu
    • +2more
    xml
    Updated Jun 24, 2024
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    Centraal Bureau voor de Statistiek (2024). Compensation of employees, employment; quarterly, NA, 1995-q1 2024 [Dataset]. https://www.cbs.nl/en-gb/figures/detail/84163ENG
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    xmlAvailable download formats
    Dataset updated
    Jun 24, 2024
    Dataset provided by
    Statistics Netherlands
    Authors
    Centraal Bureau voor de Statistiek
    License

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

    Area covered
    The Netherlands
    Description

    This table provides annual and quarterly data about the compensation of employees, the wage costs and the labour volume of employees. Compensation of employees is classified in wages and salaries and employers' social contributions. The wage costs are the total of wages, social contributions paid by employers and taxes on wage costs minus wage cost subsidies. The labour volume is given in jobs (by sex), full-time equivalent (fte) and hours worked. The seasonal adjusted time series about the compensation of employees and the wages & salaries are also available in this table. The table additionally provides the compensation of employees, wages and salaries and wage costs related to full-time equivalents and hours worked.

    Data available from: 1995 first quarter up to and including 2024 first quarter.

    Status of the figures: Data from 1995 up to and including 2020 are final. Data of 2021 and further are provisional. Since this table has been discontinued, data of 2021 and further will not become final.

    Changes as of June 24th 2024: None. This table has been discontinued. Statistics Netherlands has carried out a revision of the national accounts. New statistical sources, methods and concepts are implemented in the national accounts, in order to align the picture of the Dutch economy with all underlying source data and international guidelines for the compilation of the national accounts. For further information see section 3.

    When will new figures be published? Not applicable anymore.

  18. U

    United States Employment Cost Index: sa: Wages: Service Occupation

    • ceicdata.com
    Updated Apr 30, 2021
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    CEICdata.com (2021). United States Employment Cost Index: sa: Wages: Service Occupation [Dataset]. https://www.ceicdata.com/en/united-states/national-compensation-survey-employment-cost-index-jun-1989100/employment-cost-index-sa-wages-service-occupation
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    Dataset updated
    Apr 30, 2021
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Mar 1, 2003 - Dec 1, 2005
    Area covered
    United States
    Variables measured
    Employment
    Description

    United States Employment Cost Index: sa: Wages: Service Occupation data was reported at 164.100 Jun1989=100 in Dec 2005. This records an increase from the previous number of 163.200 Jun1989=100 for Sep 2005. United States Employment Cost Index: sa: Wages: Service Occupation data is updated quarterly, averaging 113.150 Jun1989=100 from Mar 1980 (Median) to Dec 2005, with 104 observations. The data reached an all-time high of 164.100 Jun1989=100 in Dec 2005 and a record low of 63.900 Jun1989=100 in Mar 1980. United States Employment Cost Index: sa: Wages: Service Occupation data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G073: National Compensation Survey: Employment Cost Index: Jun 1989=100.

  19. U

    United States Employment Cost Index: Wages: West: Mountain

    • ceicdata.com
    Updated Nov 27, 2021
    + more versions
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    CEICdata.com (2021). United States Employment Cost Index: Wages: West: Mountain [Dataset]. https://www.ceicdata.com/en/united-states/national-compensation-survey-employment-cost-index-by-region-dec-2005100/employment-cost-index-wages-west-mountain
    Explore at:
    Dataset updated
    Nov 27, 2021
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Jun 1, 2015 - Mar 1, 2018
    Area covered
    United States
    Description

    United States Employment Cost Index: Wages: West: Mountain data was reported at 132.500 Dec2005=100 in Mar 2018. This records an increase from the previous number of 130.800 Dec2005=100 for Dec 2017. United States Employment Cost Index: Wages: West: Mountain data is updated quarterly, averaging 115.200 Dec2005=100 from Mar 2006 (Median) to Mar 2018, with 49 observations. The data reached an all-time high of 132.500 Dec2005=100 in Mar 2018 and a record low of 100.600 Dec2005=100 in Mar 2006. United States Employment Cost Index: Wages: West: Mountain data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G074: National Compensation Survey: Employment Cost Index: By Region: Dec 2005=100.

  20. Employment, Hours, and Earnings - State and Metro Area

    • db.nomics.world
    Updated Mar 18, 2025
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    DBnomics (2025). Employment, Hours, and Earnings - State and Metro Area [Dataset]. https://db.nomics.world/BLS/sm
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    Dataset updated
    Mar 18, 2025
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    Authors
    DBnomics
    Description

    The Current Employment Statistics survey, as a joint Federal-State undertaking, generates State and area, as well as national, statistics on employment, hours, and earnings.

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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
Organization logo

National Compensation Survey - Modeled Wage Estimates

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.

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