100+ datasets found
  1. Occupational Outlook Handbook

    • catalog.data.gov
    • gimi9.com
    Updated May 16, 2022
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    Bureau of Labor Statistics (2022). Occupational Outlook Handbook [Dataset]. https://catalog.data.gov/dataset/occupational-outlook-handbook-51009
    Explore at:
    Dataset updated
    May 16, 2022
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    Description

    The Occupational Outlook Handbook (OOH) is a nationally recognized source of career information, designed to provide valuable assistance to individuals making decisions about their future work lives. The Handbook is revised every two years. The OOH offers information on the hundreds of occupations that provide the majority of jobs in the United States. Each occupational profile describes the typical duties performed by the occupation, the work environment of that occupation, the typical education and training needed to enter the occupation, the median pay for workers in the occupation, and the job outlook over the coming decade for that occupation. For information on occupations, please visit: https://www.bls.gov/ooh/

  2. d

    BLS Jobs Data - Change from the Previous Month

    • catalog.data.gov
    • opendata.maryland.gov
    • +1more
    Updated Jun 21, 2025
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    opendata.maryland.gov (2025). BLS Jobs Data - Change from the Previous Month [Dataset]. https://catalog.data.gov/dataset/bls-jobs-data-change-from-the-previous-month
    Explore at:
    Dataset updated
    Jun 21, 2025
    Dataset provided by
    opendata.maryland.gov
    Description

    This dataset represents the CHANGE in the number of jobs per industry category and sub-category from the previous month, not the raw counts of actual jobs. The data behind these monthly change values is from the Bureau of Labor Statistics (BLS) Current Employment Statistics (CES) program. CES data represents businesses and government agencies, providing detailed industry data on employment on nonfarm payrolls.

  3. Occupational Employment and Wage Statistics (OEWS)

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

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

    Description

    The Occupational Employment and Wage Statistics (OEWS) Survey is a federal-state cooperative program between the Bureau of Labor Statistics (BLS) and State Workforce Agencies (SWAs). The BLS provides the procedures and technical support, draws the sample, and produces the survey materials, while the SWAs collect the data. SWAs from all fifty states, plus the District of Columbia, Puerto Rico, Guam, and the Virgin Islands participate in the survey. Occupational employment and wage rate estimates at the national level are produced by BLS using data from the fifty states and the District of Columbia. Employers who respond to states' requests to participate in the OEWS survey make these estimates possible.

    The OEWS survey collects data from a sample of establishments and calculates employment and wage estimates by occupation, industry, and geographic area. The semiannual survey covers all non-farm industries. Data are collected by the Employment Development Department in cooperation with the Bureau of Labor Statistics, US Department of Labor. The OEWS Program estimates employment and wages for approximately 830 occupations. It also produces employment and wage estimates for statewide, Metropolitan Statistical Areas (MSAs), and Balance of State areas. Estimates are a snapshot in time and should not be used as a time series.

    The OEWS estimates are published annually.

    SOURCE: https://www.bls.gov/oes/oes_emp.htm

  4. w

    BLS Jobs by Industry Category

    • data.wu.ac.at
    • opendata.maryland.gov
    • +3more
    csv, json, rdf, xml
    Updated Apr 20, 2018
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    State of Maryland (2018). BLS Jobs by Industry Category [Dataset]. https://data.wu.ac.at/schema/data_gov/ODE1ZjgyMTctN2Y0ZS00MTE0LTkyOGYtOTEwYjIwZjhhNGY4
    Explore at:
    xml, rdf, csv, jsonAvailable download formats
    Dataset updated
    Apr 20, 2018
    Dataset provided by
    State of Maryland
    Description

    Data from the Bureau of Labor Statistics (BLS) Current Employment Statistics (CES) program. CES data represents businesses and government agencies, providing detailed industry data on employment on nonfarm payrolls.

  5. Employment and Labor Force - Monthly

    • citydata.mesaaz.gov
    • data.mesaaz.gov
    csv, xlsx, xml
    Updated Dec 1, 2025
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    Bureau of Labor Statistics (2025). Employment and Labor Force - Monthly [Dataset]. https://citydata.mesaaz.gov/Economic-Development/Employment-and-Labor-Force-Monthly/3vbg-xf63
    Explore at:
    xml, xlsx, csvAvailable download formats
    Dataset updated
    Dec 1, 2025
    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

  6. USA Bureau of Labor Statistics

    • kaggle.com
    zip
    Updated Aug 30, 2019
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    US Bureau of Labor Statistics (2019). USA Bureau of Labor Statistics [Dataset]. https://www.kaggle.com/bls/bls
    Explore at:
    zip(0 bytes)Available download formats
    Dataset updated
    Aug 30, 2019
    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 Bureau of Labor Statistics (BLS) is a unit of the United States Department of Labor. It is the principal fact-finding agency for the U.S. government in the broad field of labor economics and statistics and serves as a principal agency of the U.S. Federal Statistical System. The BLS is a governmental statistical agency that collects, processes, analyzes, and disseminates essential statistical data to the American public, the U.S. Congress, other Federal agencies, State and local governments, business, and labor representatives. Source: https://en.wikipedia.org/wiki/Bureau_of_Labor_Statistics

    Content

    Bureau of Labor Statistics including CPI (inflation), employment, unemployment, and wage data.

    Update Frequency: Monthly

    Querying BigQuery Tables

    Fork this kernel to get started.

    Acknowledgements

    https://bigquery.cloud.google.com/dataset/bigquery-public-data:bls

    https://cloud.google.com/bigquery/public-data/bureau-of-labor-statistics

    Dataset Source: http://www.bls.gov/data/

    This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

    Banner Photo by Clark Young from Unsplash.

    Inspiration

    What is the average annual inflation across all US Cities? What was the monthly unemployment rate (U3) in 2016? What are the top 10 hourly-waged types of work in Pittsburgh, PA for 2016?

  7. F

    All Employees, Government

    • fred.stlouisfed.org
    json
    Updated Nov 20, 2025
    + more versions
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    (2025). All Employees, Government [Dataset]. https://fred.stlouisfed.org/series/USGOVT
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Nov 20, 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, Government (USGOVT) from Jan 1939 to Sep 2025 about establishment survey, government, employment, and USA.

  8. Employment Projections

    • catalog.data.gov
    • data.wu.ac.at
    Updated May 16, 2022
    + more versions
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    Bureau of Labor Statistics (2022). Employment Projections [Dataset]. https://catalog.data.gov/dataset/employment-projections-c37a6
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    Dataset updated
    May 16, 2022
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    Description

    The Employment Projections (EP) program develops information about the labor market for the Nation as a whole for 10 years in the future. For more information visit: https://www.bls.gov/emp/

  9. F

    Job Openings: Government

    • fred.stlouisfed.org
    json
    Updated Sep 30, 2025
    + more versions
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    (2025). Job Openings: Government [Dataset]. https://fred.stlouisfed.org/series/JTS9000JOL
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 30, 2025
    License

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

    Description

    Graph and download economic data for Job Openings: Government (JTS9000JOL) from Dec 2000 to Aug 2025 about job openings, vacancy, government, and USA.

  10. BLS - Current Employment Statistics - CES (National)

    • datalumos.org
    Updated Oct 3, 2025
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    United States Department of Labor. Bureau of Labor Statistics (2025). BLS - Current Employment Statistics - CES (National) [Dataset]. http://doi.org/10.3886/E238628V1
    Explore at:
    Dataset updated
    Oct 3, 2025
    Dataset provided by
    United States Department of Laborhttp://www.dol.gov/
    Bureau of Labor Statisticshttp://www.bls.gov/
    Authors
    United States Department of Labor. Bureau of Labor Statistics
    License

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

    Time period covered
    1939 - 2025
    Description

    The Current Employment Statistics (CES) program produces detailed industry estimates of nonfarm employment, hours, and earnings of workers on payrolls. CES National Estimates produces data for the nation, and CES State and Metro Area produces estimates for all 50 States, the District of Columbia, Puerto Rico, the Virgin Islands, and about 450 metropolitan areas and divisions.See ces-schemas.txt for a listing of the columns and a few rows of the zipped tables.See ce.series for a summary of each the tablesSee Handbook of Methods (https://www.bls.gov/opub/hom/ces/presentation.htm) for background of the data collection and presentation.See the pdf files for screenshots of the home pages.

  11. Job Openings and Labor Turnover Survey (JOLTS)

    • db.nomics.world
    Updated Oct 1, 2025
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    DBnomics (2025). Job Openings and Labor Turnover Survey (JOLTS) [Dataset]. https://db.nomics.world/BLS/jt
    Explore at:
    Dataset updated
    Oct 1, 2025
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    Authors
    DBnomics
    Description

    The Job Openings and Labor Turnover Survey program provides national estimates of rates and levels for job openings, hires, and total separations. Total separations are further broken out into quits, layoffs and discharges, and other separations.

  12. Occupational Employment and Wage Statistics (OES)

    • s.cnmilf.com
    • gimi9.com
    • +1more
    Updated May 16, 2022
    + more versions
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    Bureau of Labor Statistics (2022). Occupational Employment and Wage Statistics (OES) [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/occupational-employment-and-wage-statistics-oes
    Explore at:
    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

  13. Occupation, Salary and Likelihood of Automation

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

    About this Dataset

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

    How to Cite this Dataset

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

    Salary Data

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

    Automation Data

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

    License

    License was not specified at the source.

    Splash Banner

    Photo by Alex Knight on Unsplash

  14. Modeled Wage Estimates

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

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

  15. T

    Vital Signs: Jobs by Industry (Location Quotient) by County (2022)

    • data.bayareametro.gov
    csv, xlsx, xml
    Updated Dec 14, 2022
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    (2022). Vital Signs: Jobs by Industry (Location Quotient) by County (2022) [Dataset]. https://data.bayareametro.gov/Economy/Vital-Signs-Jobs-by-Industry-Location-Quotient-by-/uijm-ykyx
    Explore at:
    xlsx, csv, xmlAvailable download formats
    Dataset updated
    Dec 14, 2022
    Description

    VITAL SIGNS INDICATOR
    Jobs by Industry (EC1)

    FULL MEASURE NAME
    Employment by place of work by industry sector

    LAST UPDATED
    December 2022

    DESCRIPTION
    Jobs by industry refers to both the change in employment levels by industry and the proportional mix of jobs by economic sector. This measure reflects the changing industry trends that affect our region’s workers.

    DATA SOURCE
    Bureau of Labor Statistics, Quarterly Census of Employment and Wages (QCEW) - https://www.bls.gov/cew/downloadable-data-files.htm
    1990-2021

    CONTACT INFORMATION
    vitalsigns.info@bayareametro.gov

    METHODOLOGY NOTES (across all datasets for this indicator)
    Quarterly Census of Employment and Wages (QCEW) employment data is reported by the place of work and represent the number of covered workers who worked during, or received pay for, the pay period that included the 12th day of the month. Covered employees in the private-sector and in the state and local government include most corporate officials, all executives, all supervisory personnel, all professionals, all clerical workers, many farmworkers, all wage earners, all piece workers and all part-time workers. Workers on paid sick leave, paid holiday, paid vacation and the like are also covered.

    Besides excluding the aforementioned national security agencies, QCEW excludes proprietors, the unincorporated self-employed, unpaid family members, certain farm and domestic workers exempted from having to report employment data and railroad workers covered by the railroad unemployment insurance system. Excluded as well are workers who earned no wages during the entire applicable pay period because of work stoppages, temporary layoffs, illness or unpaid vacations.

    The location quotient (LQ) is used to evaluate level of concentration or clustering of an industry within the Bay Area and within each county of the region. A location quotient greater than 1 means there is a strong concentration for of jobs in an industry sector. For the Bay Area, the LQ is calculated as the share of the region’s employment in a particular sector divided by the share of California's employment in that same sector. For each county, the LQ is calculated as the share of the county’s employment in a particular sector divided by the share of the region’s employment in that same sector.

    Data is mainly pulled from aggregation level 73, which is county-level summarized at the North American Industry Classification System (NAICS) supersector level (12 sectors). This aggregation level exhibits the least loss due to data suppression, in the magnitude of 1-2 percent for regional employment, and is therefore preferred. However, the supersectors group together NAICS 11 Agriculture, Forestry, Fishing and Hunting; NAICS 21 Mining and NAICS 23 Construction. To provide a separate tally of Agriculture, Forestry, Fishing and Hunting, the aggregation level 74 data was used for NAICS codes 11, 21 and 23.

    QCEW reports on employment in Public Administration as NAICS 92. However, many government activities are reported with an industry specific code - such as transportation or utilities even if those may be public governmental entities. In 2021 for the Bay Area, the largest industry groupings under public ownership are Education and health services (58%); Public administration (29%) and Trade, transportation, and utilities (29%). With the exception of Education and health services, all other public activities were coded as government/public administration, regardless of industry group.

    For the county data there were some industries that reported 0 jobs or did not report jobs at the desired aggregation/NAICS level for the following counties/years:

    Farm:
    (aggregation level: 74, NAICS code: 11) - Contra Costa: 2008-2010 - Marin: 1990-2006, 2008-2010, 2014-2020 - Napa: 1990-2004, 2013-2021 - San Francisco: 2019-2020 - San Mateo: 2013

    Information:
    (aggregation level: 73, NAICS code: 51) - Solano: 2001

    Financial Activities:
    (aggregation level: 73, NAICS codes: 52, 53) - Solano: 2001

    Unclassified:
    (aggregation level: 73, NAICS code: 99) - All nine Bay Area counties: 1990-2000 - Marin, Napa, San Mateo, and Solano: 2020 - Napa: 2019 - Solano: 2001

  16. BLS - State and Metro Area Employment, Hours, & Earnings

    • datalumos.org
    Updated Oct 3, 2025
    + more versions
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    United States Department of Labor. Bureau of Labor Statistics (2025). BLS - State and Metro Area Employment, Hours, & Earnings [Dataset]. http://doi.org/10.3886/E238634V1
    Explore at:
    Dataset updated
    Oct 3, 2025
    Dataset provided by
    United States Department of Laborhttp://www.dol.gov/
    Bureau of Labor Statisticshttp://www.bls.gov/
    Authors
    United States Department of Labor. Bureau of Labor Statistics
    License

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

    Time period covered
    1939 - 2025
    Description

    The Current Employment Statistics (CES) program produces detailed industry estimates of employment, hours, and earnings of workers on nonfarm payrolls. CES State and Metro Area produces data for all 50 States, the District of Columbia, Puerto Rico, the Virgin Islands, and about 430 metropolitan areas and divisions. CES National Estimates produces estimates for the nation.Each month, CES surveys approximately 121,000 businesses and government agencies, representing 631,000 individual worksites.See sme-schemas.txt for a listing of the columns and a few rows of each of the tables.See Handbook of Methods (https://www.bls.gov/opub/hom/sae/) for background of the data collection and presentation methodsSee the pdf files for screenshots of the home pages.

  17. Quarterly Census Employment and Wage (QCEW)

    • datasets.ai
    • catalog.data.gov
    0
    Updated May 16, 2022
    + more versions
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    U.S. Department of Labor Bureau of Labor Statistics (2022). Quarterly Census Employment and Wage (QCEW) [Dataset]. https://datasets.ai/datasets/quarterly-census-employment-and-wage-qcew-f4418
    Explore at:
    0Available download formats
    Dataset updated
    May 16, 2022
    Dataset provided by
    United States Department of Laborhttp://www.dol.gov/
    Bureau of Labor Statisticshttp://www.bls.gov/
    Authors
    U.S. Department of Labor Bureau of Labor Statistics
    Description

    The Quarterly Census of Employment and Wages (QCEW) program publishes a quarterly count of employment and wages reported by employers covering 98 percent of U.S. jobs, available at the county, MSA, state and national levels by industry.

    More information and details about the data provided can be found at http://www.bls.gov/cew

  18. GOPI Resource - Change in Number of Jobs in Maryland by Month

    • data.wu.ac.at
    csv, json, xml
    Updated Apr 27, 2017
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    U.S. Bureau of Labor Statistics (2017). GOPI Resource - Change in Number of Jobs in Maryland by Month [Dataset]. https://data.wu.ac.at/schema/data_maryland_gov/Yml0cC1xcGF5
    Explore at:
    json, xml, csvAvailable download formats
    Dataset updated
    Apr 27, 2017
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    Area covered
    Maryland
    Description

    This dataset represents the CHANGE in the number of jobs per industry category and sub-category from the previous month, not the raw counts of actual jobs. The data behind these monthly change values is from the Bureau of Labor Statistics (BLS) Current Employment Statistics (CES) program. CES data represents businesses and government agencies, providing detailed industry data on employment on nonfarm payrolls.

  19. Quarterly Census of Employment and Wages, May 2020

    • kaggle.com
    zip
    Updated Feb 1, 2021
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    Davin Cermak (2021). Quarterly Census of Employment and Wages, May 2020 [Dataset]. https://www.kaggle.com/davincermak/quarterly-census-of-employment-and-wages-may-2020
    Explore at:
    zip(509024 bytes)Available download formats
    Dataset updated
    Feb 1, 2021
    Authors
    Davin Cermak
    License

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

    Description

    Context

    In May 2020, the United States suffered one of the largest single-month job losses in its history as state and local government imposed public policy measures to slow the spread of the COVID-19 virus which, in many cases, forced businesses to close or significantly curtail business activity. But not all counties experienced job losses compared to the prior year. Instead, some supported job gains. Can location quotients, which measure the importance of jobs in specific industries, be efficient predictors of job losses? Are there certain businesses, or groups of businesses, that had an effect on job gains/losses?

    Content

    The file data.csv contains Quarterly Census of Employment and Wage data published by the U.S. Bureau of Labor Statistics (https://www.bls.gov/cew/). The data is combined data from 2019 and May 2020, for each county, or county-equivalent, in the U.S.

    area_fips: FIPS codes for U.S. county and county-equivalent entities area_title: Name of county may2020_empl_yy_pc: Year-over-year percent change in county total employment in May 2020 may2020_empl: Count of total employment in May 2020 naics_1111 to naics_9999: Employment concentration/location quotient for each 4-digit NAICS sectors. A location quotient less than 1.0 indicates that the count's share of sector employment to total employment is lower than the same ratio in the U.S overall, while a location quotient greater than 1.0 means that the county's share of sector employment to total employment is higher than the U.S. ratio. A description of the NAICS 4-digit numeric codes can be found at https://www.bls.gov/cew/classifications/industry/industry-titles.htm.

  20. T

    Employment and Labor Force - Annual

    • citydata.mesaaz.gov
    • data.mesaaz.gov
    csv, xlsx, xml
    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
    Explore at:
    csv, xml, xlsxAvailable 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

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Bureau of Labor Statistics (2022). Occupational Outlook Handbook [Dataset]. https://catalog.data.gov/dataset/occupational-outlook-handbook-51009
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Occupational Outlook Handbook

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Dataset updated
May 16, 2022
Dataset provided by
Bureau of Labor Statisticshttp://www.bls.gov/
Description

The Occupational Outlook Handbook (OOH) is a nationally recognized source of career information, designed to provide valuable assistance to individuals making decisions about their future work lives. The Handbook is revised every two years. The OOH offers information on the hundreds of occupations that provide the majority of jobs in the United States. Each occupational profile describes the typical duties performed by the occupation, the work environment of that occupation, the typical education and training needed to enter the occupation, the median pay for workers in the occupation, and the job outlook over the coming decade for that occupation. For information on occupations, please visit: https://www.bls.gov/ooh/

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