100+ datasets found
  1. F

    Multiple Jobholders as a Percent of Employed

    • fred.stlouisfed.org
    json
    Updated Nov 20, 2025
    + more versions
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    (2025). Multiple Jobholders as a Percent of Employed [Dataset]. https://fred.stlouisfed.org/series/LNS12026620
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    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 Multiple Jobholders as a Percent of Employed (LNS12026620) from Jan 1994 to Sep 2025 about multiple jobholders, 16 years +, percent, household survey, employment, and USA.

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

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

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

  3. F

    Multiple Jobholders, Primary and Secondary Jobs Both Full Time

    • fred.stlouisfed.org
    json
    Updated Sep 5, 2025
    + more versions
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    (2025). Multiple Jobholders, Primary and Secondary Jobs Both Full Time [Dataset]. https://fred.stlouisfed.org/series/LNU02026631
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    jsonAvailable download formats
    Dataset updated
    Sep 5, 2025
    License

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

    Description

    Graph and download economic data for Multiple Jobholders, Primary and Secondary Jobs Both Full Time (LNU02026631) from Jan 1994 to Aug 2025 about multiple jobholders, full-time, 16 years +, household survey, employment, and USA.

  4. Number of employees worldwide 1991-2025

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Number of employees worldwide 1991-2025 [Dataset]. https://www.statista.com/statistics/1258612/global-employment-figures/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    World
    Description

    In 2025, there were estimated to be approximately *** billion people employed worldwide, compared to **** billion people in 1991 - an increase of around *** billion people. There was a noticeable fall in global employment between 2019 and 2020, when the number of employed people fell from due to the sudden economic shock caused by the COVID-19 pandemic. Formal vs. Informal employment globally Worldwide, there is a large gap between the informally and formally employed. Most informally employed workers reside in the Global South, especially Africa and Southeast Asia. Moreover, men are slightly more likely to be informally employed than women. The majority of informal work, nearly ** percent, is within the agricultural sector, with domestic work and construction following behind. Women’s employment As the number of employees has risen globally, so has the number of employed women. Overall, care roles such as nursing and midwifery have the highest shares of female employees globally. Moreover, while the gender pay gap has shrunk over time, it still exists. As of 2024, the uncontrolled gender pay gap was ****, meaning women made, on average, ** cents per every dollar earned by men.

  5. U.S. full-time employees unadjusted monthly number 2022-2024

    • statista.com
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    Statista, U.S. full-time employees unadjusted monthly number 2022-2024 [Dataset]. https://www.statista.com/statistics/192361/unadjusted-monthly-number-of-full-time-employees-in-the-us/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 2022 - Oct 2024
    Area covered
    United States
    Description

    As of October 2024, there were 133.89 million full-time employees in the United States. This is a slight decrease from the previous month, when there were 134.15 million full-time employees. The impact COVID-19 on employment In December 2019, the COVID-19 virus began its spread across the globe. Since being classified as a pandemic, the virus caused a global health crisis that has taken the lives of millions of people worldwide. The COVID-19 pandemic changed many facets of society, most significantly, the economy. In the first years, many businesses across all industries were forced to shut down, with large numbers of employees being laid off. The economy continued its recovery in 2022 with the nationwide unemployment rate returning to a more normal 3.4 percent as of April 2023. Unemployment benefits Because so many people in the United States lost their jobs, record numbers of individuals applied for unemployment insurance for the first time. As an early response to this nation-wide upheaval, the government issued relief checks and extended the benefits paid by unemployment insurance. In May 2020, the amount of unemployment insurance benefits paid rose to 23.73 billion U.S. dollars. As of December 2022, this value had declined to 2.24 billion U.S. dollars.

  6. d

    Employment: Labor Force Status (1983-2012)

    • catalog.data.gov
    • datasets.ai
    • +2more
    Updated Dec 2, 2020
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    University of New Mexico, Bureau of Business and Economic Research (BBER) (Point of Contact) (2020). Employment: Labor Force Status (1983-2012) [Dataset]. https://catalog.data.gov/dataset/employment-labor-force-status-1983-2012
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    Dataset updated
    Dec 2, 2020
    Dataset provided by
    University of New Mexico, Bureau of Business and Economic Research (BBER) (Point of Contact)
    Description

    Civilian labor force data consists of the number of employed persons, the number of unemployed persons, an unemployment rate and the total count of both employed and unemployed persons (total civilian labor force). Labor force refers to an estimate of the number of persons, 16 years of age and older, classified as employed or unemployed. The civilian labor force, which is presented in these data tables, excludes the Armed Forces, i.e., the civilian labor force equals employed civilians plus the unemployed. Employed persons are those individuals, 16 years of age and older, who did any work at all during the survey week as paid employees, in their own business, profession or farm, or who worked 15 hours or more as unpaid workers in a family operated business. Also counted as employed are those persons who had jobs or businesses from which they were temporarily absent because of illness, bad weather, vacation, labor-management dispute, or personal reasons. Individuals are counted only once even though they may hold more than one job. Unemployed persons comprise all persons who did not work during the survey week but who made specific efforts to find a job within the previous four weeks and were available for work during the survey week (except for temporary illness). Also included as unemployed are those who did not work at all, were available for work, but were not actively seeking work because they were either waiting to be called back to a job from which they were laid off or waiting to report to a new job within 30 days. The unemployment rate represents the number of unemployed persons as a percent of the total civilian labor force.

  7. Employed persons having more than one job by sex

    • db.nomics.world
    • ec.europa.eu
    • +1more
    Updated Jun 12, 2025
    + more versions
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    DBnomics (2025). Employed persons having more than one job by sex [Dataset]. https://db.nomics.world/Eurostat/tqoe3a5
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    Dataset updated
    Jun 12, 2025
    Dataset provided by
    Eurostathttps://ec.europa.eu/eurostat
    Authors
    DBnomics
    Description

    Percentage of persons with more than one job as a share of all persons in employment. The indicator refers to persons who had more than one job or business during the reference week, not due to change of job or business (persons having changed job or business during the reference week are not considered as having more than one job).

  8. U.S. workers working hybrid or remote vs on-site 2019-Q2 2024

    • statista.com
    Updated Jan 6, 2023
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    Statista (2023). U.S. workers working hybrid or remote vs on-site 2019-Q2 2024 [Dataset]. https://www.statista.com/statistics/1356325/hybrid-vs-remote-work-us/
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    Dataset updated
    Jan 6, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Hybrid models of working are on the rise in the United States according to survey data covering worker habits between 2019 and 2024. In the second quarter of 2024, ** percent of U.S. workers reported working in a hybrid manner. The emergence of the COVID-19 pandemic saw a record number of people working remotely to help curb the spread of the virus. Since then, many workers have found a new shape to their home and working lives, finding that a hybrid model of working is more flexible than always being required to work on-site.

  9. Percentage of persons having a second job by household composition

    • ec.europa.eu
    Updated Sep 9, 2025
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    Eurostat (2025). Percentage of persons having a second job by household composition [Dataset]. http://doi.org/10.2908/LFST_HH2JTY
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    application/vnd.sdmx.data+csv;version=1.0.0, tsv, application/vnd.sdmx.genericdata+xml;version=2.1, application/vnd.sdmx.data+csv;version=2.0.0, application/vnd.sdmx.data+xml;version=3.0.0, jsonAvailable download formats
    Dataset updated
    Sep 9, 2025
    Dataset authored and provided by
    Eurostathttps://ec.europa.eu/eurostat
    License

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

    Time period covered
    2006 - 2024
    Area covered
    Euro area – 20 countries (from 2023), Netherlands, Norway, France, Malta, Spain, Cyprus, Sweden, Portugal, Croatia
    Description

    The data collection 'LFS - specific topics, household statistics' covers a range of statistics on number, characteristics and typologies of households, based on the European Union Labour Force Survey (EU-LFS). The data collection also encompasses some labour market indicators broken down by household composition. Only annual data are available.

    General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metada. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

  10. a

    Employment Rate (Quarterly)

    • dataportal-blackcountry.opendata.arcgis.com
    Updated Sep 15, 2023
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    christopher_styche (2023). Employment Rate (Quarterly) [Dataset]. https://dataportal-blackcountry.opendata.arcgis.com/items/1bac5fe1e31d467e9d66f0e1a2a5fea2
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    Dataset updated
    Sep 15, 2023
    Dataset authored and provided by
    christopher_styche
    Area covered
    Description

    Indicator : Employment RateTheme : PeopleSource : ONS Annual Population SurveyFrequency : QuarterlyDefinition : Employment measures the number of people in paid work or who had a job that they were temporarily away from (for example, because they were on holiday or off sick). This differs from the number of jobs because some people have more than one job. The employment rate is the proportion of people aged between 16 and 64 years who are in employment.Latest Period : Year to December 2023Released : April 2024Next Update : July 2024 Link : https://www.nomisweb.co.uk/

  11. T

    United States Employment Rate

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

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

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

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

  12. Female Employment vs Socioeconimic Factors

    • kaggle.com
    zip
    Updated Mar 16, 2022
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    Pontiac Bandit (2022). Female Employment vs Socioeconimic Factors [Dataset]. https://www.kaggle.com/mdmuhtasimbillah/female-employment-vs-socioeconimic-factors
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    zip(1084 bytes)Available download formats
    Dataset updated
    Mar 16, 2022
    Authors
    Pontiac Bandit
    License

    https://www.worldbank.org/en/about/legal/terms-of-use-for-datasetshttps://www.worldbank.org/en/about/legal/terms-of-use-for-datasets

    Description

    Context

    Women roughly occupy half of the world's population but when it comes to the total workforce of a country, the percentage of male and female workers are rarely similar. This is even more prominent for the developing and underdeveloped countries. While several reasons such as the insufficient access to education, religious superstitions, lack of adequate infrastructures are responsible for this discrepancy, it goes way beyond these. And to show the effects of multiple socioeconomic factors on the participation of women in the total workforce, percentage of female employment in the total labor force has been considered. Using multiple linear regression model, the relationship between these factors can be analyzed.

    Content

    For the current study, the data set has been chosen from a survey performed on the population of Bangladesh. The datasets selected for this study span over 25 years (from 1995 to 2019). Data has been collected separately from multiple datasets from the World Bank databank for the employed women percentage and the related predictor variables. These datasets were compiled into one dataset and it corresponds to the 25 data points for the variables. There is one response variable which is the percentage of the employed women and 10 exlnanatory variables of predictors. Brief descriptions of these variables are given below.

    PerFemEmploy Employment to population ratio (%) of women who are of age 15 or older. Employment to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15 and older are generally considered the working-age population.

    FertilityRate Fertility rate (birth per women). Total fertility rate represents the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with age-specific fertility rates of the specified year.

    RatioMaletoFemale Ratio of female to male labor force participation rate. Labor force participation rate is the proportion of the population ages 15 and older that is economically active: all people who supply labor for the production of goods and services during a specified period. Ratio of female to male labor force participation rate is calculated by dividing female labor force participation rate by male labor force participation rate and multiplying by 100.

    PerFemEmployers Employers, female (% of female employment). Employers are those workers who, working on their own account or with one or a few partners, hold the type of jobs defined as a "self-employment jobs" i.e. jobs where the remuneration is directly dependent upon the profits derived from the goods and services produced), and, in this capacity, have engaged, on a continuous basis, one or more persons to work for them as employee(s).

    Agriculture Employment in agriculture, female (% of female employment). Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The agriculture sector consists of activities in agriculture, hunting, forestry and fishing, in accordance with division 1 (ISIC 2) or categories A-B (ISIC 3) or category A (ISIC 4).

    Industry Employment in industry, female (% of female employment). The industry sector consists of mining and quarrying, manufacturing, construction, and public utilities (electricity, gas, and water), in accordance with divisions 2-5 (ISIC 2) or categories C-F (ISIC 3) or categories B-F (ISIC 4).

    Services Employment in services, female (% of female employment). The services sector consists of wholesale and retail trade and restaurants and hotels; transport, storage, and communications; financing, insurance, real estate, and business services; and community, social, and personal services, in accordance with divisions 6-9 (ISIC 2) or categories G-Q (ISIC 3) or categories G-U (ISIC 4).

    Wage.Salaried Wage and salaried workers, female (% of female employment). Wage and salaried workers (employees) are those workers who hold the type of jobs defined as "paid employment jobs," where the incumbents hold explicit (written or oral) or implicit employment contracts that give them a basic remuneration that is not directly dependent upon the revenue of the unit for which they work.

    ContrFamWorkers Contributing family workers, female (% of female employment). Contribut...

  13. s

    Data from: Employment by occupation

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

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

    Area covered
    United Kingdom
    Description

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

  14. C

    Employment and Unemployment

    • data.ccrpc.org
    csv
    Updated Dec 9, 2024
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    Champaign County Regional Planning Commission (2024). Employment and Unemployment [Dataset]. https://data.ccrpc.org/dataset/employment-and-unemployment
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    csvAvailable download formats
    Dataset updated
    Dec 9, 2024
    Dataset authored and provided by
    Champaign County Regional Planning Commission
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Description

    The employment and unemployment indicator shows several data points. The first figure is the number of people in the labor force, which includes the number of people who are either working or looking for work. The second two figures, the number of people who are employed and the number of people who are unemployed, are the two subcategories of the labor force. The unemployment rate is a calculation of the number of people who are in the labor force and unemployed as a percentage of the total number of people in the labor force.

    The unemployment rate does not include people who are not employed and not in the labor force. This includes adults who are neither working nor looking for work. For example, full-time students may choose not to seek any employment during their college career, and are thus not considered in the unemployment rate. Stay-at-home parents and other caregivers are also considered outside of the labor force, and therefore outside the scope of the unemployment rate.

    The unemployment rate is a key economic indicator, and is illustrative of economic conditions in the county at the individual scale.

    There are additional considerations to the unemployment rate. Because it does not count those who are outside the labor force, it can exclude individuals who were looking for a job previously, but have since given up. The impact of this on the overall unemployment rate is difficult to quantify, but it is important to note because it shows that no statistic is perfect.

    The unemployment rates for Champaign County, the City of Champaign, and the City of Urbana are extremely similar between 2000 and 2023.

    All three areas saw a dramatic increase in the unemployment rate between 2006 and 2009. The unemployment rates for all three areas decreased overall between 2010 and 2019. However, the unemployment rate in all three areas rose sharply in 2020 due to the effects of the COVID-19 pandemic. The unemployment rate in all three areas dropped again in 2021 as pandemic restrictions were removed, and were almost back to 2019 rates in 2022. However, the unemployment rate in all three areas rose slightly from 2022 to 2023.

    This data is sourced from the Illinois Department of Employment Security’s Local Area Unemployment Statistics (LAUS), and from the U.S. Bureau of Labor Statistics.

    Sources: Illinois Department of Employment Security, Local Area Unemployment Statistics (LAUS); U.S. Bureau of Labor Statistics.

  15. u

    Employment: Labor Force Status (1983-2012)

    • gstore.unm.edu
    zip
    Updated Apr 15, 2009
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    Earth Data Analysis Center (2009). Employment: Labor Force Status (1983-2012) [Dataset]. https://gstore.unm.edu/apps/rgis/datasets/1939ba79-5317-4a53-8e3e-3eb20ba43b8e/metadata/FGDC-STD-001-1998.html
    Explore at:
    zipAvailable download formats
    Dataset updated
    Apr 15, 2009
    Dataset provided by
    Earth Data Analysis Center
    Time period covered
    Jan 1, 1983
    Area covered
    West Bounding Coordinate -109.050177 East Bounding Coordinate -103.002069 North Bounding Coordinate 37.000293 South Bounding Coordinate 31.332174, New Mexico
    Description

    Civilian labor force data consists of the number of employed persons, the number of unemployed persons, an unemployment rate and the total count of both employed and unemployed persons (total civilian labor force). Labor force refers to an estimate of the number of persons, 16 years of age and older, classified as employed or unemployed. The civilian labor force, which is presented in these data tables, excludes the Armed Forces, i.e., the civilian labor force equals employed civilians plus the unemployed. Employed persons are those individuals, 16 years of age and older, who did any work at all during the survey week as paid employees, in their own business, profession or farm, or who worked 15 hours or more as unpaid workers in a family operated business. Also counted as employed are those persons who had jobs or businesses from which they were temporarily absent because of illness, bad weather, vacation, labor-management dispute, or personal reasons. Individuals are counted only once even though they may hold more than one job. Unemployed persons comprise all persons who did not work during the survey week but who made specific efforts to find a job within the previous four weeks and were available for work during the survey week (except for temporary illness). Also included as unemployed are those who did not work at all, were available for work, but were not actively seeking work because they were either waiting to be called back to a job from which they were laid off or waiting to report to a new job within 30 days. The unemployment rate represents the number of unemployed persons as a percent of the total civilian labor force.

  16. Share of people working remotely, hybrid working, or at work in the UK...

    • statista.com
    Updated Sep 30, 2024
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    Statista (2024). Share of people working remotely, hybrid working, or at work in the UK 2020-2025 [Dataset]. https://www.statista.com/statistics/1207746/coronavirus-working-location-trends-britain/
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    Dataset updated
    Sep 30, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    May 2020 - Oct 2025
    Area covered
    United Kingdom
    Description

    In October 2025, approximately 13 percent of workers in Great Britain worked from home exclusively, with a further 27 percent working from home and travelling to work, while 45 percent only travelled to work. During this time period, the share of people only travelling to work was highest in March 2022, at 60 percent of respondents, with the peak for only working from home occurring in June 2020. In general, hybrid working has become steadily more popular than fully remote working, with the highest share of people hybrid working in November 2023, when 31 percent of people advising they were hybrid working. What type of workers are most likely to work from home? In 2020, over half of people working in the agriculture sector mainly worked from home, which was the highest share among UK industry sectors at that time. While this industry was one of the most accessible for mainly working at home, just six percent of workers in the accommodation and food services sector mainly did this, the lowest of any sector. In the same year, men were slightly more likely to mainly work from home than women, while the most common age group for mainly working from home was those aged 75 and over, at 45.4 percent. Over a long-term period, the share of people primarily home working has grown from 11.1 percent in 1998, to approximately 17.4 percent in 2020. Growth of Flexible working in the UK According to a survey conducted in 2023, working from home either on a regular, or ad hoc basis was the most common type of flexible working arrangement offered by organizations in the UK, at 62 percent of respondents. Other popular flexible working arrangements include the ability to work flexible hours, work part-time, or take career breaks. Since 2013, for example, the number of employees in the UK that can work flextime has increased from 3.2 million, to around 4.2 million by 2024. When asked why flexible work was important to them, most UK workers said that it supported a better work-life balance, with 41 percent expressing that it made their commute to work more manageable.

  17. Job tenure by professional status and occupation

    • ec.europa.eu
    Updated Oct 10, 2025
    + more versions
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    Eurostat (2025). Job tenure by professional status and occupation [Dataset]. http://doi.org/10.2908/LFSA_QOE_4A2
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    application/vnd.sdmx.data+csv;version=2.0.0, application/vnd.sdmx.genericdata+xml;version=2.1, tsv, json, application/vnd.sdmx.data+xml;version=3.0.0, application/vnd.sdmx.data+csv;version=1.0.0Available download formats
    Dataset updated
    Oct 10, 2025
    Dataset authored and provided by
    Eurostathttps://ec.europa.eu/eurostat
    License

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

    Time period covered
    2000 - 2024
    Area covered
    Cyprus, Malta, Montenegro, Norway, Finland, Germany, Italy, Lithuania, Romania, Spain
    Description

    The "Quality of employment" framework developed under the lead of UNECE (United Nations Economic Commission for Europe) represents a neutral and comprehensive approach to assess quality of employment in its multiple facets. It defines 68 indicators on seven dimensions that address employment quality from the perspective of the employed person. Its design also facilitates international comparison. For statistical institutes, researchers and policy users looking to build and analyse datasets using these indicators, the framework is explained in a Handbook on measuring quality of employment published by UNECE. Using the UNECE framework, Eurostat has compiled data on employment quality for the EU countries that is provided in the Eurostat database.

    LFS in one of the sources which provides data for filling some of the indicators. The section 'Quality of employment' reports annual results from the EU-LFS concerning some of those indicators.

    In particular:

    • Long working hours in main job: percentage of employed persons usually working 49 hours or more per week;
    • Weekly working hours: Average number of usual weekly working hours of employed persons;
    • Work on weekends: Percentage of employed persons usually working at Saturday or Sunday;
    • Job tenure Percentage of employed persons by duration of employment with current employer by number of years;
    • Temporary employment agency workers: Percentage of employed persons working for a temporary work agency;
    • Precarious employment: Percentage of employees with a short-term contract of up to 3 months.

    More information on Eurostat indicators about Quality of employment is available on the Quality of employment webpage.

    General information on the EU-LFS can be found in the ESMS page for 'https://ec.europa.eu/eurostat/cache/metadata/en/employ_esms.htm" target="_parent">Employment and unemployment (LFS). Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

  18. i

    Inactive persons who have worked previously and left their last job more...

    • ine.es
    csv, html, json +4
    Updated May 22, 2013
    + more versions
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    INE - Instituto Nacional de Estadística (2013). Inactive persons who have worked previously and left their last job more than 1 year ago by professional situation of last job, sex and Autonomous Community. Percentages with respect to the total of each [Dataset]. https://www.ine.es/jaxiT3/Tabla.htm?t=956&L=1
    Explore at:
    html, txt, json, csv, text/pc-axis, xls, xlsxAvailable download formats
    Dataset updated
    May 22, 2013
    Dataset authored and provided by
    INE - Instituto Nacional de Estadística
    License

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

    Time period covered
    Jan 1, 2005 - Jan 1, 2012
    Variables measured
    Age, Sex, Unit, Collective, Employment, Economic sector, Job search time, Occupational status, Type of working day, Socioeconomic condition, and 6 more
    Description

    Economically Active Population Survey (EAPS): Inactive persons who have worked previously and left their last job more than 1 year ago by professional situation of last job, sex and Autonomous Community. Percentages with respect to the total of each. Annual. Autonomous Communities and Cities.

  19. i

    Unemployed population who have previously worked and left their last job...

    • ine.es
    csv, html, json +4
    Updated May 22, 2013
    + more versions
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    INE - Instituto Nacional de Estadística (2013). Unemployed population who have previously worked and left their last job more than 1 year ago by professional situation, sex and age group. Percentages with regards to the total of each professional situation [Dataset]. https://www.ine.es/jaxiT3/Tabla.htm?t=777&L=1
    Explore at:
    text/pc-axis, xls, csv, json, txt, xlsx, htmlAvailable download formats
    Dataset updated
    May 22, 2013
    Dataset authored and provided by
    INE - Instituto Nacional de Estadística
    License

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

    Time period covered
    Jan 1, 2005 - Jan 1, 2012
    Variables measured
    Age, Sex, Unit, Collective, Employment, Economic sector, Job search time, Occupational status, Type of working day, Socioeconomic condition, and 6 more
    Description

    Economically Active Population Survey (EAPS): Unemployed population who have previously worked and left their last job more than 1 year ago by professional situation, sex and age group. Percentages with regards to the total of each professional situation. Annual. National.

  20. The Impacts of Working Remotely and in an Office

    • kaggle.com
    zip
    Updated Jun 20, 2023
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    Mohamed Elzeini (2023). The Impacts of Working Remotely and in an Office [Dataset]. https://www.kaggle.com/datasets/mohamedelzeini/the-impacts-of-working-remotely-and-in-an-office/code
    Explore at:
    zip(908091 bytes)Available download formats
    Dataset updated
    Jun 20, 2023
    Authors
    Mohamed Elzeini
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Description

    THE IMPACTS OF WORKING REMOTELY AND IN AN OFFICE

    Abstract: Working from home nowadays, particularly after COVID-19 hit the world, became the preferable choice for many employees because it gives flexibility and saves more time, according to them. However, many studies revealed that working from home caused a negative effect on many employees’ mental and physical health, such as isolation and back pain. The careless and unplanned way of living while working remotely, such as lack of socialization and equipment for a healthy home office, is the cause for that negative effect. In this paper, we explore the reasons that lead to the negative impact of working remotely on mental and physical health and investigate whether employees are aware of the negative and the positive effects of working either from home or in an office. Our investigation involved a questionnaire handed to hundred employees and revealed that the majority of them were aware of the negative and the positive impacts of working remotely and in an office and suggest, therefore, a mixed-mode of working to obtain the best advantages of both modes.

    Keywords: COVID-19; working from home; working in an office; questionnaire; advantages; disadvantages; negative impact; positive impact; mental health; physical health; work experience

    1. Introduction

    Who would not like to wake up late and avoid the traffic every morning? I always had dreamed of that, and I guess you too. Working from home, which provides these advantages, has become the preferred choice for many employees and employers for the sake of getting more flexibility, increasing productivity, and saving time and money (Ipsen et al., 2021). I have noticed, especially during the COVID-19 pandemic, that many people switched willingly to work from home, expecting their life would totally improve. On the other hand, many people do not have the office work option. For instance, people work in the human resources, marketing, and customer service sectors (Iacurci, 2021). They work remotely until a hundred percent effective covid vaccine is developed. However, many studies, such as "Survey reveals the mental and physical health impacts of home working during Covid-19" by RSPH (2021), revealed that people who work from home are likely to suffer from mental and physical disorders.

    In fact, the reason for the negative impact is not the work from home. Rather, it is the unmanaged lifestyle that comes with working from home. Of course, many other jobs still need people to be physically present, such as working in hospitals and beauty centers. However, Iacurci (2021) suggests that people will work remotely even after the pandemic finishes and the economy reopens. While many people are switching to work from home, and many others hoping so, it might be an opportunity for them to know the negative impact of working remotely, such as isolation and back pain, due to lack of socialization and equipment for a healthy home office. I am not willing to tell people what they should do in order to work healthily from home because this is not my study field. However, because I have experienced that negative impact, I will only give hints about the consequences, which could happen if they did not take care of themselves when working from home. Thus, this research investigated hundred people who have already worked before, regardless of gender identity, whether they are aware of the negative and the positive impacts of working from home in order to take care of themselves.

    2. Literature review

    Reviewing Worker's and Employees' Opinions in Working from Home

    Before the COVID-19 pandemic, people could choose between working from home and in an office. However, many people are forced or got the opportunity to work from home to reduce the number of new daily infections during the pandemic. Thus, it was an opportunity for researchers to do research on a large number of people to figure out how working from home experience affected them. Also, after the pandemic is over, what would they prefer if they could choose between working remotely or being physically in an office.

    In the study, "Six key advantages and disadvantages of working from home in Europe during COVID-19," Ipsen et al. (2021) investigated employees who have experience with working from home during the pandemic in 29 European countries. They used first the six key advantages and disadvantages approach, which involves the employees' opinions in working from home. Although the employees mentioned 16 disadvantages and 11 advantages, its results indicate that "the majority (55%) of employees were mostly positive about WFH" (p. 11). However, they assumed that maybe there are other circumstances that make the employees prefer working remotely over in an office. Hence, Ipsen et al. (2021) used the six factors approach, which involved the employe...

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(2025). Multiple Jobholders as a Percent of Employed [Dataset]. https://fred.stlouisfed.org/series/LNS12026620

Multiple Jobholders as a Percent of Employed

LNS12026620

Explore at:
11 scholarly articles cite this dataset (View in Google Scholar)
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 Multiple Jobholders as a Percent of Employed (LNS12026620) from Jan 1994 to Sep 2025 about multiple jobholders, 16 years +, percent, household survey, employment, and USA.

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