8 datasets found
  1. T

    United States Average Weekly Hours

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +12more
    csv, excel, json, xml
    Updated Jul 8, 2023
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    TRADING ECONOMICS (2023). United States Average Weekly Hours [Dataset]. https://tradingeconomics.com/united-states/average-weekly-hours
    Explore at:
    csv, excel, xml, jsonAvailable download formats
    Dataset updated
    Jul 8, 2023
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Mar 31, 2006 - Jun 30, 2025
    Area covered
    United States
    Description

    Average Weekly Hours in the United States decreased to 34.20 Hours in June from 34.30 Hours in May of 2025. This dataset provides - United States Average Weekly Hours - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  2. Philippines Hours Worked Per Week (HWPW): At Work

    • ceicdata.com
    + more versions
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    CEICdata.com, Philippines Hours Worked Per Week (HWPW): At Work [Dataset]. https://www.ceicdata.com/en/philippines/labour-force-survey-employment-hours-worked-per-week/hours-worked-per-week-hwpw-at-work
    Explore at:
    Dataset provided by
    CEIC Data
    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
    Philippines
    Variables measured
    Hours Worked
    Description

    Philippines Hours Worked Per Week (HWPW): At Work data was reported at 48,753.000 Person th in Feb 2025. This records an increase from the previous number of 48,075.000 Person th for Jan 2025. Philippines Hours Worked Per Week (HWPW): At Work data is updated monthly, averaging 47,289.500 Person th from Jan 2021 (Median) to Feb 2025, with 50 observations. The data reached an all-time high of 50,191.000 Person th in Dec 2023 and a record low of 41,037.000 Person th in Jan 2021. Philippines Hours Worked Per Week (HWPW): At Work data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.G027: Labour Force Survey: Employment: Hours Worked Per Week.

  3. Actual hours worked by industry, annual

    • www150.statcan.gc.ca
    • open.canada.ca
    • +2more
    Updated Jan 24, 2025
    + more versions
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    Government of Canada, Statistics Canada (2025). Actual hours worked by industry, annual [Dataset]. http://doi.org/10.25318/1410003701-eng
    Explore at:
    Dataset updated
    Jan 24, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Number of employed persons by actual hours worked, class of worker, North American Industry Classification System (NAICS), and gender.

  4. N

    Normal, IL annual median income by work experience and sex dataset: Aged...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Normal, IL annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/normal-il-income-by-gender/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Illinois, Normal
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Normal. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

    Key observations: Insights from 2023

    Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Normal, the median income for all workers aged 15 years and older, regardless of work hours, was $41,421 for males and $25,263 for females.

    These income figures highlight a substantial gender-based income gap in Normal. Women, regardless of work hours, earn 61 cents for each dollar earned by men. This significant gender pay gap, approximately 39%, underscores concerning gender-based income inequality in the town of Normal.

    - Full-time workers, aged 15 years and older: In Normal, among full-time, year-round workers aged 15 years and older, males earned a median income of $70,419, while females earned $58,364, leading to a 17% gender pay gap among full-time workers. This illustrates that women earn 83 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

    Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in Normal.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

    Gender classifications include:

    • Male
    • Female

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    Variables / Data Columns

    • Year: This column presents the data year. Expected values are 2010 to 2023
    • Male Total Income: Annual median income, for males regardless of work hours
    • Male FT Income: Annual median income, for males working full time, year-round
    • Male PT Income: Annual median income, for males working part time
    • Female Total Income: Annual median income, for females regardless of work hours
    • Female FT Income: Annual median income, for females working full time, year-round
    • Female PT Income: Annual median income, for females working part time

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Normal median household income by race. You can refer the same here

  5. Australia Actual Hours Worked: Average per Employed Person: Males: 35-39...

    • ceicdata.com
    Updated Jan 15, 2025
    + more versions
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    CEICdata.com (2025). Australia Actual Hours Worked: Average per Employed Person: Males: 35-39 Hours [Dataset]. https://www.ceicdata.com/en/australia/actual-hours-worked/actual-hours-worked-average-per-employed-person-males-3539-hours
    Explore at:
    Dataset updated
    Jan 15, 2025
    Dataset provided by
    CEIC Data
    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
    Australia
    Variables measured
    Hours Worked
    Description

    Australia Actual Hours Worked: Average per Employed Person: Males: 35-39 Hours data was reported at 37.371 Hour in Mar 2025. This records a decrease from the previous number of 37.418 Hour for Feb 2025. Australia Actual Hours Worked: Average per Employed Person: Males: 35-39 Hours data is updated monthly, averaging 37.189 Hour from Jan 1991 (Median) to Mar 2025, with 411 observations. The data reached an all-time high of 37.461 Hour in Jul 2024 and a record low of 36.456 Hour in Apr 1993. Australia Actual Hours Worked: Average per Employed Person: Males: 35-39 Hours data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.G053: Actual Hours Worked.

  6. N

    Normal, IL annual income distribution by work experience and gender dataset:...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Normal, IL annual income distribution by work experience and gender dataset: Number of individuals ages 15+ with income, 2023 // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/babaf22e-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Illinois, Normal
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Normal. The dataset can be utilized to gain insights into gender-based income distribution within the Normal population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within Normal, among individuals aged 15 years and older with income, there were 17,652 men and 20,441 women in the workforce. Among them, 8,361 men were engaged in full-time, year-round employment, while 7,140 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 9.81% fell within the income range of under $24,999, while 8.80% of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 27.02% of men in full-time roles earned incomes exceeding $100,000, while 17.46% of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)
    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Normal median household income by race. You can refer the same here

  7. T

    United States Initial Jobless Claims

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 3, 2025
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    TRADING ECONOMICS (2025). United States Initial Jobless Claims [Dataset]. https://tradingeconomics.com/united-states/jobless-claims
    Explore at:
    csv, xml, excel, jsonAvailable download formats
    Dataset updated
    Jul 3, 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 7, 1967 - Jul 5, 2025
    Area covered
    United States
    Description

    Initial Jobless Claims in the United States decreased to 227 thousand in the week ending July 5 of 2025 from 232 thousand in the previous week. This dataset provides the latest reported value for - United States Initial Jobless Claims - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  8. N

    Greenland, AR annual median income by work experience and sex dataset : Aged...

    • neilsberg.com
    csv, json
    Updated Jan 9, 2024
    + more versions
    Share
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    Neilsberg Research (2024). Greenland, AR annual median income by work experience and sex dataset : Aged 15+, 2010-2022 (in 2022 inflation-adjusted dollars) [Dataset]. https://www.neilsberg.com/research/datasets/948fdf3a-9816-11ee-99cf-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Jan 9, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Greenland
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2010-2022 5-Year Estimates. To portray the income for both the genders (Male and Female), we conducted an initial analysis and categorization of the data. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Greenland. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

    Key observations: Insights from 2021

    Based on our analysis ACS 2017-2021 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Greenland, the median income for all workers aged 15 years and older, regardless of work hours, was $36,859 for males and $29,500 for females.

    These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 20% between the median incomes of males and females in Greenland. With women, regardless of work hours, earning 80 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Greenland.

    - Full-time workers, aged 15 years and older: In Greenland, among full-time, year-round workers aged 15 years and older, males earned a median income of $42,657, while females earned $41,692, resulting in a 2% gender pay gap among full-time workers. This illustrates that women earn 98 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the city of Greenland.

    Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Greenland.

    https://i.neilsberg.com/ch/greenland-ar-income-by-gender.jpeg" alt="Greenland, AR gender based income disparity">

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

    Gender classifications include:

    • Male
    • Female

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    Variables / Data Columns

    • Year: This column presents the data year. Expected values are 2010 to 2022
    • Male Total Income: Annual median income, for males regardless of work hours
    • Male FT Income: Annual median income, for males working full time, year-round
    • Male PT Income: Annual median income, for males working part time
    • Female Total Income: Annual median income, for females regardless of work hours
    • Female FT Income: Annual median income, for females working full time, year-round
    • Female PT Income: Annual median income, for females working part time

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Greenland median household income by gender. You can refer the same here

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    Learn how you can add new datasets to our index.

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TRADING ECONOMICS (2023). United States Average Weekly Hours [Dataset]. https://tradingeconomics.com/united-states/average-weekly-hours

United States Average Weekly Hours

United States Average Weekly Hours - Historical Dataset (2006-03-31/2025-06-30)

Explore at:
csv, excel, xml, jsonAvailable download formats
Dataset updated
Jul 8, 2023
Dataset authored and provided by
TRADING ECONOMICS
License

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

Time period covered
Mar 31, 2006 - Jun 30, 2025
Area covered
United States
Description

Average Weekly Hours in the United States decreased to 34.20 Hours in June from 34.30 Hours in May of 2025. This dataset provides - United States Average Weekly Hours - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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