100+ datasets found
  1. Bureau of Labor Statistics Monthly Unemployment (latest 14 months)

    • hub.arcgis.com
    • coronavirus-resources.esri.com
    • +9more
    Updated Aug 16, 2022
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    Esri (2022). Bureau of Labor Statistics Monthly Unemployment (latest 14 months) [Dataset]. https://hub.arcgis.com/maps/993b8c64a67a4c6faa44a91846547786
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    Dataset updated
    Aug 16, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer contains the latest 14 months of unemployment statistics from the U.S. Bureau of Labor Statistics (BLS). The data is offered at the nationwide, state, and county geography levels. Puerto Rico is included. These are not seasonally adjusted values.The layer is updated monthly with the newest unemployment statistics available from BLS. There are attributes in the layer that specify which month is associated to each statistic. Most current month: April 2025 (preliminary values at the state and county level)The attributes included for each month are:Unemployment rate (%)Count of unemployed populationCount of employed population in the labor forceCount of people in the labor forceData obtained from the U.S. Bureau of Labor Statistics. Data downloaded: May 28th, 2025Local Area Unemployment Statistics table download: https://www.bls.gov/lau/#tablesLocal Area Unemployment FTP downloads:State and CountyNationData Notes:This layer is updated automatically when the BLS releases their most current monthly statistics. The layer always contains the most recent estimates. It is updated within days of the BLS's county release schedule. BLS releases their county statistics roughly 2 months after-the-fact. The data is joined to 2023 TIGER boundaries from the U.S. Census Bureau.Monthly values are subject to revision over time.For national values, employed plus unemployed may not sum to total labor force due to rounding.As of the January 2022 estimates released on March 18th, 2022, BLS is reporting new data for the two new census areas in Alaska - Copper River and Chugach - and historical data for the previous census area - Valdez Cordova.As of the March 17th, 2025 release, BLS now reports data for 9 planning regions in Connecticut rather than the 8 previous counties.To better understand the different labor force statistics included in this map, see the diagram below from BLS:

  2. 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

  3. F

    All Employees, Federal

    • fred.stlouisfed.org
    json
    Updated Jun 6, 2025
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    (2025). All Employees, Federal [Dataset]. https://fred.stlouisfed.org/series/CES9091000001
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 6, 2025
    License

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

    Description

    Graph and download economic data for All Employees, Federal (CES9091000001) from Jan 1939 to May 2025 about establishment survey, federal, government, employment, and USA.

  4. US Unemployment Rate by County, 1990-2016

    • kaggle.com
    zip
    Updated May 22, 2017
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    Jay Ravaliya (2017). US Unemployment Rate by County, 1990-2016 [Dataset]. https://www.kaggle.com/jayrav13/unemployment-by-county-us
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    zip(12879595 bytes)Available download formats
    Dataset updated
    May 22, 2017
    Authors
    Jay Ravaliya
    License

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

    Area covered
    United States
    Description

    Context

    This is a dataset that I built by scraping the United States Department of Labor's Bureau of Labor Statistics. I was looking for county-level unemployment data and realized that there was a data source for this, but the data set itself hadn't existed yet, so I decided to write a scraper and build it out myself.

    Content

    This data represents the Local Area Unemployment Statistics from 1990-2016, broken down by state and month. The data itself is pulled from this mapping site:

    https://data.bls.gov/map/MapToolServlet?survey=la&map=county&seasonal=u

    Further, the ever-evolving and ever-improving codebase that pulled this data is available here:

    https://github.com/jayrav13/bls_local_area_unemployment

    Acknowledgements

    Of course, a huge shoutout to bls.gov and their open and transparent data. I've certainly been inspired to dive into US-related data recently and having this data open further enables my curiosities.

    Inspiration

    I was excited about building this data set out because I was pretty sure something similar didn't exist - curious to see what folks can do with it once they run with it! A curious question I had was surrounding Unemployment vs 2016 Presidential Election outcome down to the county level. A comparison can probably lead to interesting questions and discoveries such as trends in local elections that led to their most recent election outcome, etc.

    Next Steps

    Version 1 of this is as a massive JSON blob, normalized by year / month / state. I intend to transform this into a CSV in the future as well.

  5. F

    Employment-Population Ratio

    • fred.stlouisfed.org
    json
    Updated Jun 6, 2025
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    (2025). Employment-Population Ratio [Dataset]. https://fred.stlouisfed.org/series/EMRATIO
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    jsonAvailable download formats
    Dataset updated
    Jun 6, 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-Population Ratio (EMRATIO) from Jan 1948 to May 2025 about employment-population ratio, civilian, 16 years +, household survey, employment, population, and USA.

  6. Employment and Labor Force - Monthly

    • data.mesaaz.gov
    • citydata.mesaaz.gov
    application/rdfxml +5
    Updated Jun 11, 2019
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    Bureau of Labor Statistics (2019). Employment and Labor Force - Monthly [Dataset]. https://data.mesaaz.gov/Economic-Development/Employment-and-Labor-Force-Monthly/3vbg-xf63
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    csv, xml, application/rssxml, tsv, application/rdfxml, jsonAvailable download formats
    Dataset updated
    Jun 11, 2019
    Dataset authored and provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    Description

    Monthly statistics regarding the labor force, employment and unemployment in Mesa and nearby municipalities. Unemployment rate sourced at BLS.gov Data Viewer. Employment Data - Bureau of Labor Statistics - http://www.bls.gov/data/ Local Area Unemployment Statistics (LAUS) - https://www.bls.gov/lau/ (See for next data release dates). To see how these terms are defined and what they include, please visit the Terms Glossary from the United State Department of Labor’s Bureau of Labor Statistics (BLS), which can be found at the following web address: http://www.bls.gov/bls/glossary.htm

  7. V

    Virginia Labor Force and Unemployment estimates by Month by County

    • data.virginia.gov
    csv
    Updated Jun 12, 2025
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    Office of INTERMODAL Planning and Investment (2025). Virginia Labor Force and Unemployment estimates by Month by County [Dataset]. https://data.virginia.gov/dataset/virginia-labor-force-and-unemployment-estimates-by-month-by-county
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    csv(5699066)Available download formats
    Dataset updated
    Jun 12, 2025
    Dataset authored and provided by
    Office of INTERMODAL Planning and Investment
    Area covered
    Virginia
    Description

    1990 to present (approximate 2 month lag) Virginia Labor Force and Unemployment estimates by Month by County.

    Special data considerations: Period values of "M01-M12" represent Months of Year; "M13" is the Annual Average.

    U.S. Bureau of Labor Statistics; Local Area Unemployment Statistics, table la.data.54.Virginia Data accessed from the Bureau of Labor Statistics public database LABSTAT (https://download.bls.gov/pub/time.series/la/)

    Supporting documentation can be found on the U.S. Bureau of Labor Statistics website under Local Area Unemployment Statistics, Handbook of Methods (https://www.bls.gov/opub/hom/lau/home.htm)

    Survey Description: Labor force and unemployment estimates for States and local areas are developed by State workforce agencies to measure local labor market conditions under a Federal-State cooperative program. The Department of Labor develops the concepts, definitions, and technical procedures which are used by State agencies for preparation of labor force and unemployment estimates.

    These estimates are derived from a variety of sources, including the Current Population Survey, the Current Employment Statistics survey, the Quarterly Census of Employment and Wages, various programs at the Census Bureau, and unemployment insurance claims data from the State workforce agencies.

    To establish uniform labor force concepts and definitions in all States and areas consistent with those used for the U.S. as a whole, monthly national estimates of employment and unemployment from the Current Population Survey are used as controls (benchmarks) for the State labor force statistics.

    Summary Data Available: Monthly labor force and unemployment series are available for approximately 7,500 geographic areas, including cities over 25,000 population, counties, metropolitan areas, States, and other areas.

    For each area, the following measures are presented by place of residence:

    • Total civilian labor force,
    • Total number of people employed,
    • Total number of people unemployed, and
    • Unemployment rate

    Data Characteristics: Rates are expressed as percents with one decimal place. Levels are measured as individual persons (not thousands) and are stored with no decimal places.

  8. T

    Employment and Labor Force - Annual

    • citydata.mesaaz.gov
    application/rdfxml +5
    Updated Sep 4, 2020
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    Economic Development (2020). Employment and Labor Force - Annual [Dataset]. https://citydata.mesaaz.gov/Economic-Development/Employment-and-Labor-Force-Annual/f7ya-r76p
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    tsv, application/rssxml, csv, application/rdfxml, json, xmlAvailable download formats
    Dataset updated
    Sep 4, 2020
    Dataset authored and provided by
    Economic Development
    Description

    Historical information on the Employment Dataset shows several current and historical annual statistics regarding population, the labor force, employment and unemployment in the City of Mesa. Monthly labor force, employment and unemployment information is at https://citydata.mesaaz.gov/External-Data/Employment-and-Labor-Force-Monthly/3vbg-xf63.

    Sources: Population Data - United States Census Bureau -https://www.census.gov/topics/population/data.html Employment Data - Bureau of Labor Statistics - http://www.bls.gov/data/ Local Area Unemployment Statistics (LAUS) - https://www.bls.gov/lau/ To see how these terms are defined and what they include, please visit the Terms Glossary from the United State Department of Labor’s Bureau of Labor Statistics (BLS), which can be found at the following web address: http://www.bls.gov/bls/glossary.htm

  9. 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
    Explore at:
    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

  10. Quarterly Census of Employment and Wages (QCEW)

    • catalog.data.gov
    • data.ca.gov
    Updated Nov 27, 2024
    + more versions
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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
    Explore at:
    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.

  11. U.S. seasonally adjusted unemployment rate 2023-2025

    • statista.com
    • ai-chatbox.pro
    Updated Mar 11, 2025
    + more versions
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    Statista (2025). U.S. seasonally adjusted unemployment rate 2023-2025 [Dataset]. https://www.statista.com/statistics/273909/seasonally-adjusted-monthly-unemployment-rate-in-the-us/
    Explore at:
    Dataset updated
    Mar 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 2023 - Feb 2025
    Area covered
    United States
    Description

    The seasonally-adjusted national unemployment rate is measured on a monthly basis in the United States. In February 2025, the national unemployment rate was at 4.1 percent. Seasonal adjustment is a statistical method of removing the seasonal component of a time series that is used when analyzing non-seasonal trends. U.S. monthly unemployment rate According to the Bureau of Labor Statistics - the principle fact-finding agency for the U.S. Federal Government in labor economics and statistics - unemployment decreased dramatically between 2010 and 2019. This trend of decreasing unemployment followed after a high in 2010 resulting from the 2008 financial crisis. However, after a smaller financial crisis due to the COVID-19 pandemic, unemployment reached 8.1 percent in 2020. As the economy recovered, the unemployment rate fell to 5.3 in 2021, and fell even further in 2022. Additional statistics from the BLS paint an interesting picture of unemployment in the United States. In November 2023, the states with the highest (seasonally adjusted) unemployment rate were the Nevada and the District of Columbia. Unemployment was the lowest in Maryland, at 1.8 percent. Workers in the agricultural and related industries suffered the highest unemployment rate of any industry at seven percent in December 2023.

  12. T

    United States Unemployment Rate

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    + more versions
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    TRADING ECONOMICS, United States Unemployment Rate [Dataset]. https://tradingeconomics.com/united-states/unemployment-rate
    Explore at:
    excel, xml, csv, jsonAvailable download formats
    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 - May 31, 2025
    Area covered
    United States
    Description

    Unemployment Rate in the United States remained unchanged at 4.20 percent in May. This dataset provides the latest reported value for - United States Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  13. U.S. Unemployment Rate Data

    • kaggle.com
    zip
    Updated Sep 10, 2021
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    Arpit Verma (2021). U.S. Unemployment Rate Data [Dataset]. https://www.kaggle.com/varpit94/us-unemployment-rate-data
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    zip(2789 bytes)Available download formats
    Dataset updated
    Sep 10, 2021
    Authors
    Arpit Verma
    Area covered
    United States
    Description

    Context

    U.S. Unemployment rate historical data, downloaded from U.S. Bureau of Labor Statistics website.

    Content

    Data starts from 01-Jan-1948 and is available at monthly level.

  14. American Time Use Survey, 2003-2015 [United States]: Arts Activities

    • icpsr.umich.edu
    Updated Nov 28, 2016
    + more versions
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    United States Department of Labor. Bureau of the Labor Statistics (2016). American Time Use Survey, 2003-2015 [United States]: Arts Activities [Dataset]. http://doi.org/10.3886/ICPSR36268.v3
    Explore at:
    Dataset updated
    Nov 28, 2016
    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 the Labor Statistics
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/36268/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/36268/terms

    Time period covered
    2003 - 2015
    Area covered
    United States
    Description

    The American Time Use Survey (ATUS) is the Nation's first federally administered, continuous survey on time use in the United States. The survey is sponsored by the Bureau of Labor Statistics and is conducted by the U.S. Census Bureau. This multi-year data collection contains information on the amount of time that people spent doing various activities in the years 2003 through 2015, such as work and work-related activities, personal care, household activities, consumer purchases, volunteering, and caring for and helping household members. Respondents were also asked about arts-related activities including sports, recreation, socializing, relaxing, arts and crafts, and music appreciation. Additionally, the study provides demographic information--including sex, race, age, educational attainment, occupation, income, marital status, and the presence of children in the household. For this data collection, 170,842 respondents were randomly selected from a subset of households that have completed their eighth and final month of interviews for the Current Population Survey (CPS). Respondents were interviewed only one time about how they spent their time on the previous day, where they were, and whom they were with.

  15. F

    Labor Force Participation Rate - Women

    • fred.stlouisfed.org
    json
    Updated Jun 6, 2025
    + more versions
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    (2025). Labor Force Participation Rate - Women [Dataset]. https://fred.stlouisfed.org/series/LNS11300002
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 6, 2025
    License

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

    Description

    Graph and download economic data for Labor Force Participation Rate - Women (LNS11300002) from Jan 1948 to May 2025 about females, participation, 16 years +, labor force, labor, household survey, rate, and USA.

  16. Consumer Expenditure Survey, 2013: Diary Survey Files

    • icpsr.umich.edu
    ascii, delimited +5
    Updated Oct 19, 2015
    + more versions
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    United States Department of Labor. Bureau of Labor Statistics (2015). Consumer Expenditure Survey, 2013: Diary Survey Files [Dataset]. http://doi.org/10.3886/ICPSR36275.v1
    Explore at:
    r, spss, stata, excel, sas, delimited, asciiAvailable download formats
    Dataset updated
    Oct 19, 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/36275/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/36275/terms

    Time period covered
    2013
    Area covered
    United States
    Description

    The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers, including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index. The CE program is comprised of two separate components (each with its own survey questionnaire and independent sample), the Diary Survey and the quarterly Interview Survey (ICPSR 36237). This data collection contains the Diary Survey component, which was designed to obtain data on frequently purchased smaller items, including food, housing, apparel and services, transportation, entertainment, and out-of-pocket health care costs. Each consumer unit (CU) recorded its expenditures in a diary for two consecutive 1-week periods. Although the diary was designed to collect information on expenditures that could not be easily recalled over time, respondents were asked to report all expenses (except overnight travel) that the CU incurred during the survey week. The 2013 Diary Survey release contains five sets of data files (FMLD, MEMD, EXPD, DTBD, DTID), and one processing file (DSTUB). The FMLD, MEMD, EXPD, DTBD, and DTID files are organized by the quarter of the calendar year in which the data were collected. There are four quarterly datasets for each of these files. The FMLD files contain CU characteristics, income, and summary level expenditures; the MEMD files contain member characteristics and income data; the EXPD files contain detailed weekly expenditures at the Universal Classification Code (UCC) level; the DTBD files contain the CU's reported annual income values or the mean of the five imputed income values in the multiple imputation method; and the DTID files contain the five imputed income values. Please note that the summary level expenditure and income information on the FMLD files permit the data user to link consumer spending, by general expenditure category, and household characteristics and demographics on one set of files. The DSTUB file provides the aggregation scheme used in the published consumer expenditure tables. The DSTUB file is further explained in Section III.F.6. "Processing Files" of the Diary Survey Users' Guide. A second documentation guide, the "Users' Guide to Income Imputation," includes information on how to appropriately use the imputed income data. Demographic and family characteristics data include age, sex, race, marital status, and CU relationships for each CU member. Income information was also collected, such as wage, salary, unemployment compensation, child support, and alimony, as well as information on the employment of each CU member age 14 and over. The unpublished integrated CE data tables produced by the BLS are available to download through NADAC (click on "Other" in the Dataset(s) section). The tables show average and percentile expenditures for detailed items, as well as the standard error and coefficient of variation (CV) for each spending estimate. The BLS unpublished integrated CE data tables are provided as an easy-to-use tool for obtaining spending estimates. However, users are cautioned to read the BLS explanatory letter accompanying the tables. The letter explains that estimates of average expenditures on detailed spending items (such as leisure and art-related categories) may be unreliable due to so few reports of expenditures for those items.

  17. U

    United States AHE: sa: PW: LH: Historical Sites & Other Similar Institutions...

    • ceicdata.com
    Updated Dec 17, 2020
    + more versions
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    CEICdata.com (2020). United States AHE: sa: PW: LH: Historical Sites & Other Similar Institutions [Dataset]. https://www.ceicdata.com/en/united-states/current-employment-statistics-survey-average-weekly-and-hourly-earnings-production-workers/ahe-sa-pw-lh-historical-sites--other-similar-institutions
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    Dataset updated
    Dec 17, 2020
    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
    Dec 1, 2021 - Nov 1, 2022
    Area covered
    United States
    Variables measured
    Employment
    Description

    United States AHE: sa: PW: LH: Historical Sites & Other Similar Institutions data was reported at 19.520 USD in Nov 2022. This records a decrease from the previous number of 19.900 USD for Oct 2022. United States AHE: sa: PW: LH: Historical Sites & Other Similar Institutions data is updated monthly, averaging 12.910 USD from Jan 1990 to Nov 2022, with 395 observations. The data reached an all-time high of 21.100 USD in Apr 2020 and a record low of 7.070 USD in Mar 1990. United States AHE: sa: PW: LH: Historical Sites & Other Similar Institutions data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G064: Current Employment Statistics Survey: Average Weekly and Hourly Earnings: Production Workers.

  18. U

    United States Employment: NF: IF: Web Search Portals & All Other

    • ceicdata.com
    Updated Feb 15, 2023
    + more versions
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    CEICdata.com (2023). United States Employment: NF: IF: Web Search Portals & All Other [Dataset]. https://www.ceicdata.com/en/united-states/current-employment-statistics-survey-employment-non-farm-payroll/employment-nf-if-web-search-portals--all-other
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    Dataset updated
    Feb 15, 2023
    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
    Feb 1, 2024 - Jan 1, 2025
    Area covered
    United States
    Variables measured
    Employment
    Description

    United States Employment: NF: IF: Web Search Portals & All Other data was reported at 153.000 Person th in Feb 2025. This records a decrease from the previous number of 155.700 Person th for Jan 2025. United States Employment: NF: IF: Web Search Portals & All Other data is updated monthly, averaging 57.800 Person th from Jan 1990 (Median) to Feb 2025, with 422 observations. The data reached an all-time high of 162.100 Person th in Nov 2022 and a record low of 24.600 Person th in Feb 1990. United States Employment: NF: IF: Web Search Portals & All Other data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G054: Current Employment Statistics: Employment: Non Farm Payroll.

  19. H

    Consumer Expenditure Survey (CE)

    • dataverse.harvard.edu
    Updated May 30, 2013
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    Anthony Damico (2013). Consumer Expenditure Survey (CE) [Dataset]. http://doi.org/10.7910/DVN/UTNJAH
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 30, 2013
    Dataset provided by
    Harvard Dataverse
    Authors
    Anthony Damico
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    analyze the consumer expenditure survey (ce) with r the consumer expenditure survey (ce) is the primo data source to understand how americans spend money. participating households keep a running diary about every little purchase over the year. those diaries are then summed up into precise expenditure categories. how else are you gonna know that the average american household spent $34 (±2) on bacon, $826 (±17) on cellular phones, and $13 (±2) on digital e-readers in 2011? an integral component of the market basket calculation in the consumer price index, this survey recently became available as public-use microdata and they're slowly releasing historical files back to 1996. hooray! for a t aste of what's possible with ce data, look at the quick tables listed on their main page - these tables contain approximately a bazillion different expenditure categories broken down by demographic groups. guess what? i just learned that americans living in households with $5,000 to $9,999 of annual income spent an average of $283 (±90) on pets, toys, hobbies, and playground equipment (pdf page 3). you can often get close to your statistic of interest from these web tables. but say you wanted to look at domestic pet expenditure among only households with children between 12 and 17 years old. another one of the thirteen web tables - the consumer unit composition table - shows a few different breakouts of households with kids, but none matching that exact population of interest. the bureau of labor statistics (bls) (the survey's designers) and the census bureau (the survey's administrators) have provided plenty of the major statistics and breakouts for you, but they're not psychic. if you want to comb through this data for specific expenditure categories broken out by a you-defined segment of the united states' population, then let a little r into your life. fun starts now. fair warning: only analyze t he consumer expenditure survey if you are nerd to the core. the microdata ship with two different survey types (interview and diary), each containing five or six quarterly table formats that need to be stacked, merged, and manipulated prior to a methodologically-correct analysis. the scripts in this repository contain examples to prepare 'em all, just be advised that magnificent data like this will never be no-assembly-required. the folks at bls have posted an excellent summary of what's av ailable - read it before anything else. after that, read the getting started guide. don't skim. a few of the descriptions below refer to sas programs provided by the bureau of labor statistics. you'll find these in the C:\My Directory\CES\2011\docs directory after you run the download program. this new github repository contains three scripts: 2010-2011 - download all microdata.R lo op through every year and download every file hosted on the bls's ce ftp site import each of the comma-separated value files into r with read.csv depending on user-settings, save each table as an r data file (.rda) or stat a-readable file (.dta) 2011 fmly intrvw - analysis examples.R load the r data files (.rda) necessary to create the 'fmly' table shown in the ce macros program documentation.doc file construct that 'fmly' table, using five quarters of interviews (q1 2011 thru q1 2012) initiate a replicate-weighted survey design object perform some lovely li'l analysis examples replicate the %mean_variance() macro found in "ce macros.sas" and provide some examples of calculating descriptive statistics using unimputed variables replicate the %compare_groups() macro found in "ce macros.sas" and provide some examples of performing t -tests using unimputed variables create an rsqlite database (to minimize ram usage) containing the five imputed variable files, after identifying which variables were imputed based on pdf page 3 of the user's guide to income imputation initiate a replicate-weighted, database-backed, multiply-imputed survey design object perform a few additional analyses that highlight the modified syntax required for multiply-imputed survey designs replicate the %mean_variance() macro found in "ce macros.sas" and provide some examples of calculating descriptive statistics using imputed variables repl icate the %compare_groups() macro found in "ce macros.sas" and provide some examples of performing t-tests using imputed variables replicate the %proc_reg() and %proc_logistic() macros found in "ce macros.sas" and provide some examples of regressions and logistic regressions using both unimputed and imputed variables replicate integrated mean and se.R match each step in the bls-provided sas program "integr ated mean and se.sas" but with r instead of sas create an rsqlite database when the expenditure table gets too large for older computers to handle in ram export a table "2011 integrated mean and se.csv" that exactly matches the contents of the sas-produced "2011 integrated mean and se.lst" text file click here to view these three scripts for...

  20. M

    Labor Force Participation Rate (1948-2025)

    • macrotrends.net
    csv
    Updated Jun 30, 2025
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    MACROTRENDS (2025). Labor Force Participation Rate (1948-2025) [Dataset]. https://www.macrotrends.net/3012/labor-force-participation-rate
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    csvAvailable download formats
    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

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

    Time period covered
    1948 - 2025
    Area covered
    United States
    Description

    The series comes from the 'Current Population Survey (Household Survey)' The source code is: LNS11300000

    The Labor Force Participation Rate is defined by the Current Population Survey (CPS) as “the number of people in the labor force as a percentage of the civilian noninstitutional population […] the participation rate is the percentage of the population that is either working or actively looking for work.”

    The Labor Force Participation Rate is collected in the CPS and published by the BLS. It is provided on a monthly basis, so this data is used in part by macroeconomists as an initial economic indicator of current labor market trends. The labor force participation rate helps government agencies, financial markets, and researchers gauge the overall health of the economy.

    Note that long-run changes in labor force participation may reflect secular economic trends that are unrelated to the overall health of the economy. For instance, demographic changes such as the aging of population can lead to a secular increase of exits from the labor force, shrinking the labor force and decreasing the labor force participation rate.

    For more information, see: U.S. Bureau of Labor Statistics, CES Overview (https://www.bls.gov/web/empsit/cesprog.htm) U.S. Bureau of Labor Statistics, Concepts and Definitions (CPS) (https://www.bls.gov/cps/definitions.htm#lfpr)

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Esri (2022). Bureau of Labor Statistics Monthly Unemployment (latest 14 months) [Dataset]. https://hub.arcgis.com/maps/993b8c64a67a4c6faa44a91846547786
Organization logo

Bureau of Labor Statistics Monthly Unemployment (latest 14 months)

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Dataset updated
Aug 16, 2022
Dataset authored and provided by
Esrihttp://esri.com/
Area covered
Description

This layer contains the latest 14 months of unemployment statistics from the U.S. Bureau of Labor Statistics (BLS). The data is offered at the nationwide, state, and county geography levels. Puerto Rico is included. These are not seasonally adjusted values.The layer is updated monthly with the newest unemployment statistics available from BLS. There are attributes in the layer that specify which month is associated to each statistic. Most current month: April 2025 (preliminary values at the state and county level)The attributes included for each month are:Unemployment rate (%)Count of unemployed populationCount of employed population in the labor forceCount of people in the labor forceData obtained from the U.S. Bureau of Labor Statistics. Data downloaded: May 28th, 2025Local Area Unemployment Statistics table download: https://www.bls.gov/lau/#tablesLocal Area Unemployment FTP downloads:State and CountyNationData Notes:This layer is updated automatically when the BLS releases their most current monthly statistics. The layer always contains the most recent estimates. It is updated within days of the BLS's county release schedule. BLS releases their county statistics roughly 2 months after-the-fact. The data is joined to 2023 TIGER boundaries from the U.S. Census Bureau.Monthly values are subject to revision over time.For national values, employed plus unemployed may not sum to total labor force due to rounding.As of the January 2022 estimates released on March 18th, 2022, BLS is reporting new data for the two new census areas in Alaska - Copper River and Chugach - and historical data for the previous census area - Valdez Cordova.As of the March 17th, 2025 release, BLS now reports data for 9 planning regions in Connecticut rather than the 8 previous counties.To better understand the different labor force statistics included in this map, see the diagram below from BLS:

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