100+ datasets found
  1. T

    United States Average Hourly Wages

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 15, 2025
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    TRADING ECONOMICS (2025). United States Average Hourly Wages [Dataset]. https://tradingeconomics.com/united-states/wages
    Explore at:
    json, csv, xml, excelAvailable download formats
    Dataset updated
    Jun 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, 1964 - Jun 30, 2025
    Area covered
    United States
    Description

    Wages in the United States increased to 31.24 USD/Hour in June from 31.15 USD/Hour in May of 2025. This dataset provides - United States Average Hourly Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  2. F

    Average Hourly Earnings of Production and Nonsupervisory Employees, Total...

    • fred.stlouisfed.org
    json
    Updated Jun 6, 2025
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    (2025). Average Hourly Earnings of Production and Nonsupervisory Employees, Total Private [Dataset]. https://fred.stlouisfed.org/series/AHETPI
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 6, 2025
    License

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

    Description

    Graph and download economic data for Average Hourly Earnings of Production and Nonsupervisory Employees, Total Private (AHETPI) from Jan 1964 to May 2025 about nonsupervisory, headline figure, earnings, average, establishment survey, hours, wages, production, private, employment, and USA.

  3. Employee wages by industry, monthly, unadjusted for seasonality

    • www150.statcan.gc.ca
    • datasets.ai
    • +4more
    Updated Jul 11, 2025
    + more versions
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    Government of Canada, Statistics Canada (2025). Employee wages by industry, monthly, unadjusted for seasonality [Dataset]. http://doi.org/10.25318/1410006301-eng
    Explore at:
    Dataset updated
    Jul 11, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Average hourly and weekly wage rate, and median hourly and weekly wage rate by North American Industry Classification System (NAICS), type of work, gender, and age group.

  4. T

    WAGES by Country Dataset

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 26, 2017
    + more versions
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    TRADING ECONOMICS (2017). WAGES by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/wages
    Explore at:
    xml, excel, csv, jsonAvailable download formats
    Dataset updated
    May 26, 2017
    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
    2025
    Area covered
    World
    Description

    This dataset provides values for WAGES reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

  5. F

    Average Weekly Earnings of All Employees, Total Private

    • fred.stlouisfed.org
    json
    Updated Jul 3, 2025
    + more versions
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    (2025). Average Weekly Earnings of All Employees, Total Private [Dataset]. https://fred.stlouisfed.org/series/CES0500000011
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 3, 2025
    License

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

    Description

    Graph and download economic data for Average Weekly Earnings of All Employees, Total Private (CES0500000011) from Mar 2006 to Jun 2025 about earnings, establishment survey, private, employment, and USA.

  6. N

    Norway, IA 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). Norway, IA 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/norway-ia-income-by-gender/
    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
    Norway, Iowa
    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 Norway. 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 Norway, the median income for all workers aged 15 years and older, regardless of work hours, was $49,167 for males and $38,750 for females.

    These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 21% between the median incomes of males and females in Norway. With women, regardless of work hours, earning 79 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Norway.

    - Full-time workers, aged 15 years and older: In Norway, among full-time, year-round workers aged 15 years and older, males earned a median income of $63,333, while females earned $38,750, leading to a 39% gender pay gap among full-time workers. This illustrates that women earn 61 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.

    Remarkably, across all roles, including non-full-time employment, women displayed a lower gender pay gap percentage. This indicates that Norway offers better opportunities for women in non-full-time positions.

    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 Norway median household income by race. You can refer the same here

  7. Earnings and hours worked, all employees: ASHE Table 1

    • ons.gov.uk
    • cy.ons.gov.uk
    zip
    Updated Oct 29, 2024
    + more versions
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    Office for National Statistics (2024). Earnings and hours worked, all employees: ASHE Table 1 [Dataset]. https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/earningsandworkinghours/datasets/allemployeesashetable1
    Explore at:
    zipAvailable download formats
    Dataset updated
    Oct 29, 2024
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

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

    Description

    Annual estimates of paid hours worked and earnings for UK employees by sex, and full-time and part-time.

  8. EARN01: Average weekly earnings

    • ons.gov.uk
    • cy.ons.gov.uk
    xls
    Updated Jun 10, 2025
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    Office for National Statistics (2025). EARN01: Average weekly earnings [Dataset]. https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/earningsandworkinghours/datasets/averageweeklyearningsearn01
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 10, 2025
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

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

    Description

    Average weekly earnings at sector level headline estimates, Great Britain, monthly, seasonally adjusted. Monthly Wages and Salaries Survey.

  9. U.S. median household income 1990-2023

    • statista.com
    Updated Sep 16, 2024
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    Statista (2024). U.S. median household income 1990-2023 [Dataset]. https://www.statista.com/statistics/200838/median-household-income-in-the-united-states/
    Explore at:
    Dataset updated
    Sep 16, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    This statistic shows the median household income in the United States from 1990 to 2023 in 2023 U.S. dollars. The median household income was 80,610 U.S. dollars in 2023, an increase from the previous year. Household incomeThe median household income depicts the income of households, including the income of the householder and all other individuals aged 15 years or over living in the household. Income includes wages and salaries, unemployment insurance, disability payments, child support payments received, regular rental receipts, as well as any personal business, investment, or other kinds of income received routinely. The median household income in the United States varies from state to state. In 2020, the median household income was 86,725 U.S. dollars in Massachusetts, while the median household income in Mississippi was approximately 44,966 U.S. dollars at that time. Household income is also used to determine the poverty line in the United States. In 2021, about 11.6 percent of the U.S. population was living in poverty. The child poverty rate, which represents people under the age of 18 living in poverty, has been growing steadily over the first decade since the turn of the century, from 16.2 percent of the children living below the poverty line in year 2000 to 22 percent in 2010. In 2021, it had lowered to 15.3 percent. The state with the widest gap between the rich and the poor was New York, with a Gini coefficient score of 0.51 in 2019. The Gini coefficient is calculated by looking at average income rates. A score of zero would reflect perfect income equality and a score of one indicates a society where one person would have all the money and all other people have nothing.

  10. Average weekly earnings by industry, annual

    • www150.statcan.gc.ca
    • open.canada.ca
    • +2more
    Updated Mar 27, 2025
    + more versions
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    Average weekly earnings by industry, annual [Dataset]. https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1410020401
    Explore at:
    Dataset updated
    Mar 27, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Average weekly earnings by North American Industry Classification System (NAICS), type of employee and overtime status, last 5 years.

  11. N

    Big Flats, Wisconsin annual median income by work experience and sex...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Big Flats, Wisconsin 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/big-flats-wi-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
    Wisconsin, Big Flats
    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 Big Flats town. 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 Big Flats town, the median income for all workers aged 15 years and older, regardless of work hours, was $32,237 for males and $23,333 for females.

    These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 28% between the median incomes of males and females in Big Flats town. With women, regardless of work hours, earning 72 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thetown of Big Flats town.

    - Full-time workers, aged 15 years and older: In Big Flats town, among full-time, year-round workers aged 15 years and older, males earned a median income of $51,927, while females earned $29,028, leading to a 44% gender pay gap among full-time workers. This illustrates that women earn 56 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.

    Remarkably, across all roles, including non-full-time employment, women displayed a lower gender pay gap percentage. This indicates that Big Flats town offers better opportunities for women in non-full-time positions.

    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 Big Flats town median household income by race. You can refer the same here

  12. T

    Montenegro Average Monthly Wages

    • tradingeconomics.com
    • tr.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated May 15, 2025
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    TRADING ECONOMICS (2025). Montenegro Average Monthly Wages [Dataset]. https://tradingeconomics.com/montenegro/wages
    Explore at:
    excel, xml, json, csvAvailable download formats
    Dataset updated
    May 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
    Dec 31, 2003 - May 31, 2025
    Area covered
    Montenegro
    Description

    Wages in Montenegro increased to 1208 EUR/Month in May from 1202 EUR/Month in April of 2025. This dataset provides - Montenegro Average Monthly Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  13. EHQ08 - Average Earnings, Hours Worked, Employment and Labour Costs -...

    • data.gov.ie
    Updated May 27, 2025
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    data.gov.ie (2025). EHQ08 - Average Earnings, Hours Worked, Employment and Labour Costs - Dataset - data.gov.ie [Dataset]. https://data.gov.ie/dataset/ehq08-average-earnings-hours-worked-employment-and-labour-costs
    Explore at:
    Dataset updated
    May 27, 2025
    Dataset provided by
    data.gov.ie
    License

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

    Description

    Average Earnings, Hours Worked, Employment and Labour Costs

  14. Egypt Wages: Weekly Average

    • ceicdata.com
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    CEICdata.com, Egypt Wages: Weekly Average [Dataset]. https://www.ceicdata.com/en/egypt/wages-and-salaries/wages-weekly-average
    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
    Dec 1, 2012 - Dec 1, 2023
    Area covered
    Egypt
    Variables measured
    Wage/Earnings
    Description

    Egypt Wages: Weekly Average data was reported at 1,251.000 EGP in 2023. This records an increase from the previous number of 1,052.000 EGP for 2022. Egypt Wages: Weekly Average data is updated yearly, averaging 534.000 EGP from Dec 1999 (Median) to 2023, with 25 observations. The data reached an all-time high of 1,283.000 EGP in 2019 and a record low of 143.000 EGP in 1999. Egypt Wages: Weekly Average data remains active status in CEIC and is reported by Central Agency for Public Mobilization and Statistics. The data is categorized under Global Database’s Egypt – Table EG.G018: Wages and Salaries.

  15. F

    Average Hourly Earnings of All Employees, Manufacturing

    • fred.stlouisfed.org
    json
    Updated Jul 3, 2025
    + more versions
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    (2025). Average Hourly Earnings of All Employees, Manufacturing [Dataset]. https://fred.stlouisfed.org/series/CES3000000003
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 3, 2025
    License

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

    Description

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

  16. T

    Croatia Average Net Monthly Wages

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +12more
    csv, excel, json, xml
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    TRADING ECONOMICS, Croatia Average Net Monthly Wages [Dataset]. https://tradingeconomics.com/croatia/wages
    Explore at:
    json, csv, excel, xmlAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 31, 1992 - Apr 30, 2025
    Area covered
    Croatia
    Description

    Wages in Croatia decreased to 1439 EUR/Month in April from 1448 EUR/Month in March of 2025. This dataset provides the latest reported value for - Croatia Average Monthly Wages - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  17. F

    Average Hourly Earnings of All Employees, Construction

    • fred.stlouisfed.org
    json
    Updated Jul 3, 2025
    + more versions
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    (2025). Average Hourly Earnings of All Employees, Construction [Dataset]. https://fred.stlouisfed.org/series/CES2000000003
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 3, 2025
    License

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

    Description

    Graph and download economic data for Average Hourly Earnings of All Employees, Construction (CES2000000003) from Mar 2006 to Jun 2025 about earnings, establishment survey, hours, construction, wages, employment, and USA.

  18. N

    Big Sandy, MT 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). Big Sandy, MT 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/research/datasets/a503a401-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
    Big Sandy, Montana
    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 Big Sandy. 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 Big Sandy, the median income for all workers aged 15 years and older, regardless of work hours, was $31,875 for males and $30,694 for females.

    Based on these incomes, we observe a gender gap percentage of approximately 4%, indicating a significant disparity between the median incomes of males and females in Big Sandy. Women, regardless of work hours, still earn 96 cents to each dollar earned by men, highlighting an ongoing gender-based wage gap.

    - Full-time workers, aged 15 years and older: In Big Sandy, among full-time, year-round workers aged 15 years and older, males earned a median income of $47,778, while females earned $45,000, resulting in a 6% gender pay gap among full-time workers. This illustrates that women earn 94 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 town of Big Sandy.

    Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Big Sandy, showcasing a consistent income pattern irrespective of employment status.

    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 Big Sandy median household income by race. You can refer the same here

  19. T

    Russia Average Monthly Wages

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated May 15, 2025
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    TRADING ECONOMICS (2025). Russia Average Monthly Wages [Dataset]. https://tradingeconomics.com/russia/wages
    Explore at:
    excel, csv, xml, jsonAvailable download formats
    Dataset updated
    May 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, 1990 - Mar 31, 2025
    Area covered
    Russia
    Description

    Wages in Russia increased to 97645 RUB/Month in March from 89646 RUB/Month in February of 2025. This dataset provides the latest reported value for - Russia Average Monthly Wages - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  20. R

    Russia Average Monthly Nominal Wages: SB: Omsk Region

    • ceicdata.com
    Updated Mar 21, 2025
    Share
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    CEICdata.com (2025). Russia Average Monthly Nominal Wages: SB: Omsk Region [Dataset]. https://www.ceicdata.com/en/russia/average-monthly-wages-by-region
    Explore at:
    Dataset updated
    Mar 21, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2013 - Dec 1, 2024
    Area covered
    Russia
    Variables measured
    Wage/Earnings
    Description

    Average Monthly Nominal Wages: SB: Omsk Region data was reported at 64,427.600 RUB in 2024. This records an increase from the previous number of 55,227.200 RUB for 2023. Average Monthly Nominal Wages: SB: Omsk Region data is updated yearly, averaging 13,524.800 RUB from Dec 1992 (Median) to 2024, with 33 observations. The data reached an all-time high of 64,427.600 RUB in 2024 and a record low of 5.400 RUB in 1992. Average Monthly Nominal Wages: SB: Omsk Region data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Demographic and Labour Market – Table RU.GC008: Average Monthly Wages: by Region.

Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
TRADING ECONOMICS (2025). United States Average Hourly Wages [Dataset]. https://tradingeconomics.com/united-states/wages

United States Average Hourly Wages

United States Average Hourly Wages - Historical Dataset (1964-01-31/2025-06-30)

Explore at:
36 scholarly articles cite this dataset (View in Google Scholar)
json, csv, xml, excelAvailable download formats
Dataset updated
Jun 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, 1964 - Jun 30, 2025
Area covered
United States
Description

Wages in the United States increased to 31.24 USD/Hour in June from 31.15 USD/Hour in May of 2025. This dataset provides - United States Average Hourly Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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