100+ datasets found
  1. T

    United States Average Hourly Wages

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, United States Average Hourly Wages [Dataset]. https://tradingeconomics.com/united-states/wages
    Explore at:
    json, csv, xml, excelAvailable 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, 1964 - May 31, 2025
    Area covered
    United States
    Description

    Wages in the United States increased to 31.18 USD/Hour in May from 31.06 USD/Hour in April of 2025. This dataset provides - United States Average Hourly Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  2. U.S. wage and salary accruals 2023, by industry

    • statista.com
    Updated Oct 15, 2024
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    Statista (2024). U.S. wage and salary accruals 2023, by industry [Dataset]. https://www.statista.com/statistics/243834/annual-mean-wages-and-salary-per-employee-in-the-us-by-industry/
    Explore at:
    Dataset updated
    Oct 15, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, the average wage and salary per full-time equivalent employee in the mining industry in the United States was at 126,707 U.S. dollars. The highest wage and salary per FTE was found in the information industry, at 164,400 U.S. dollars.

  3. U.S. median earnings for people with and without disabilities from 2008 to...

    • statista.com
    Updated Jun 26, 2025
    + more versions
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    Statista (2025). U.S. median earnings for people with and without disabilities from 2008 to 2023 [Dataset]. https://www.statista.com/statistics/978989/disability-annual-earnings-us/
    Explore at:
    Dataset updated
    Jun 26, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In the United States, the median salary for people with a disability was considerably lower throughout the years under consideration. In 2023, the median salary for people with a disability was ****** U.S. dollars. Conversely, the median salary for people without a disability in the same year was ****** U.S. dollars. This statistic presents the median annual salary of people with and without disabilities in the U.S. from 2008 to 2023.

  4. F

    Average Hourly Earnings of All Employees, Manufacturing

    • fred.stlouisfed.org
    json
    Updated Jun 6, 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
    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 All Employees, Manufacturing (CES3000000003) from Mar 2006 to May 2025 about earnings, establishment survey, hours, wages, manufacturing, employment, and USA.

  5. N

    United States Median Income by Age Groups Dataset: A Comprehensive Breakdown...

    • neilsberg.com
    csv, json
    Updated Feb 25, 2025
    + more versions
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    Neilsberg Research (2025). United States Median Income by Age Groups Dataset: A Comprehensive Breakdown of United States Annual Median Income Across 4 Key Age Groups // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/united-states-median-household-income-by-age/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 25, 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
    United States
    Variables measured
    Income for householder under 25 years, Income for householder 65 years and over, Income for householder between 25 and 44 years, Income for householder between 45 and 64 years
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It delineates income distributions across four age groups (Under 25 years, 25 to 44 years, 45 to 64 years, and 65 years and over) following an initial analysis and categorization. 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 the distribution of median household income among distinct age brackets of householders in United States. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in United States. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

    Key observations: Insights from 2023

    In terms of income distribution across age cohorts, in United States, householders within the 45 to 64 years age group have the highest median household income at $94,847, followed by those in the 25 to 44 years age group with an income of $87,575. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $57,108. Notably, householders within the under 25 years age group, had the lowest median household income at $43,534.

    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.

    Age groups classifications include:

    • Under 25 years
    • 25 to 44 years
    • 45 to 64 years
    • 65 years and over

    Variables / Data Columns

    • Age Of The Head Of Household: This column presents the age of the head of household
    • Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

    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 United States median household income by age. You can refer the same here

  6. F

    Employed full time: Median usual weekly nominal earnings (second quartile):...

    • fred.stlouisfed.org
    json
    Updated Apr 16, 2025
    + more versions
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    (2025). Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Bachelor's degree and higher: 25 years and over [Dataset]. https://fred.stlouisfed.org/series/LEU0252918500Q
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Apr 16, 2025
    License

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

    Description

    Graph and download economic data for Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Bachelor's degree and higher: 25 years and over (LEU0252918500Q) from Q1 2000 to Q1 2025 about second quartile, full-time, 25 years +, tertiary schooling, salaries, workers, earnings, education, wages, median, employment, and USA.

  7. U.S. mean earnings 2005-2023, by educational attainment

    • statista.com
    • ai-chatbox.pro
    Updated Oct 28, 2024
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    Statista (2024). U.S. mean earnings 2005-2023, by educational attainment [Dataset]. https://www.statista.com/statistics/184242/mean-earnings-by-educational-attainment/
    Explore at:
    Dataset updated
    Oct 28, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2023 the mean earnings of Bachelor's degree holders in the United States amounted to 86,970 U.S. dollars. People with higher education degrees tended to earn more than those without. For example, high school graduates, including those with a GED, had mean earnings of 46,720 U.S. dollars.

  8. U.S. median family income 2023, by state

    • statista.com
    Updated Oct 25, 2024
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    Statista (2024). U.S. median family income 2023, by state [Dataset]. https://www.statista.com/statistics/236804/median-family-income-in-the-united-states-by-state/
    Explore at:
    Dataset updated
    Oct 25, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, the median annual family income in the District of Columbia was 157,210 U.S. dollars, the highest of any state. Comparatively, the median family income for Mississippi was 72,259 U.S. dollars. For the United States as a whole, the median annual family income was 96,401 U.S. dollars.

  9. F

    Average Weekly Earnings of All Employees, Total Private

    • fred.stlouisfed.org
    json
    Updated Jun 6, 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
    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 Weekly Earnings of All Employees, Total Private (CES0500000011) from Mar 2006 to May 2025 about earnings, establishment survey, private, employment, and USA.

  10. 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
    Normal, Illinois
    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

  11. N

    Income Distribution by Quintile: Mean Household Income in Mulberry Grove, IL...

    • neilsberg.com
    csv, json
    Updated Jan 11, 2024
    + more versions
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    Neilsberg Research (2024). Income Distribution by Quintile: Mean Household Income in Mulberry Grove, IL [Dataset]. https://www.neilsberg.com/research/datasets/94cf37c4-7479-11ee-949f-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Jan 11, 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
    Mulberry Grove, Illinois
    Variables measured
    Income Level, Mean Household Income
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. It delineates income distributions across income quintiles (mentioned above) following an initial analysis and categorization. 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 the mean household income for each of the five quintiles in Mulberry Grove, IL, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

    Key observations

    • Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 1,865, while the mean income for the highest quintile (20% of households with the highest income) is 130,895. This indicates that the top earners earn 70 times compared to the lowest earners.
    • *Top 5%: * The mean household income for the wealthiest population (top 5%) is 177,976, which is 135.97% higher compared to the highest quintile, and 9542.95% higher compared to the lowest quintile.

    Mean household income by quintiles in Mulberry Grove, IL (in 2022 inflation-adjusted dollars))

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

    Income Levels:

    • Lowest Quintile
    • Second Quintile
    • Third Quintile
    • Fourth Quintile
    • Highest Quintile
    • Top 5 Percent

    Variables / Data Columns

    • Income Level: This column showcases the income levels (As mentioned above).
    • Mean Household Income: Mean household income, in 2022 inflation-adjusted dollars for the specific income level.

    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 Mulberry Grove median household income. You can refer the same here

  12. N

    Iowa City, IA Median Income by Age Groups Dataset: A Comprehensive Breakdown...

    • neilsberg.com
    csv, json
    Updated Feb 25, 2025
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    Neilsberg Research (2025). Iowa City, IA Median Income by Age Groups Dataset: A Comprehensive Breakdown of Iowa City Annual Median Income Across 4 Key Age Groups // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/iowa-city-ia-median-household-income-by-age/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 25, 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
    Iowa City, Iowa
    Variables measured
    Income for householder under 25 years, Income for householder 65 years and over, Income for householder between 25 and 44 years, Income for householder between 45 and 64 years
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It delineates income distributions across four age groups (Under 25 years, 25 to 44 years, 45 to 64 years, and 65 years and over) following an initial analysis and categorization. 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 the distribution of median household income among distinct age brackets of householders in Iowa City. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Iowa City. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

    Key observations: Insights from 2023

    In terms of income distribution across age cohorts, in Iowa City, householders within the 45 to 64 years age group have the highest median household income at $96,545, followed by those in the 25 to 44 years age group with an income of $71,760. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $63,413. Notably, householders within the under 25 years age group, had the lowest median household income at $23,018.

    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.

    Age groups classifications include:

    • Under 25 years
    • 25 to 44 years
    • 45 to 64 years
    • 65 years and over

    Variables / Data Columns

    • Age Of The Head Of Household: This column presents the age of the head of household
    • Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

    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 Iowa City median household income by age. You can refer the same here

  13. Average weekly earnings by industry, annual

    • www150.statcan.gc.ca
    • open.canada.ca
    • +2more
    Updated Mar 27, 2025
    + more versions
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    Government of Canada, Statistics Canada (2025). Average weekly earnings by industry, annual [Dataset]. http://doi.org/10.25318/1410020401-eng
    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.

  14. Latin America & Caribbean: real salary growth 2006-2017

    • statista.com
    Updated Aug 12, 2024
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    Statista (2024). Latin America & Caribbean: real salary growth 2006-2017 [Dataset]. https://www.statista.com/statistics/976828/average-real-wage-growth-rate-latin-america-caribbean/
    Explore at:
    Dataset updated
    Aug 12, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Caribbean, Latin America, LAC
    Description

    This statistic presents a timeline with the real growth of average wages in Latin America and the Caribbean from 2006 to 2017. The source estimated that average salaries in the region had increased 0.7 percent in 2017, compared to the previous year.

  15. U.S. average annual pay of employees in New Jersey 2001-2023

    • statista.com
    Updated Sep 12, 2024
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    Statista (2024). U.S. average annual pay of employees in New Jersey 2001-2023 [Dataset]. https://www.statista.com/statistics/305775/new-jersey-annual-pay/
    Explore at:
    Dataset updated
    Sep 12, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2023, the average annual pay of employees in New Jersey totaled to 80,570 U.S. dollars. This is both an increase from the previous year, and from 2001 levels, when this figure stood at 44,320 U.S. dollars.

  16. N

    Sterling, CO Median Income by Age Groups Dataset: A Comprehensive Breakdown...

    • neilsberg.com
    csv, json
    Updated Feb 25, 2025
    + more versions
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    Neilsberg Research (2025). Sterling, CO Median Income by Age Groups Dataset: A Comprehensive Breakdown of Sterling Annual Median Income Across 4 Key Age Groups // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/sterling-co-median-household-income-by-age/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 25, 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
    Colorado, Sterling
    Variables measured
    Income for householder under 25 years, Income for householder 65 years and over, Income for householder between 25 and 44 years, Income for householder between 45 and 64 years
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It delineates income distributions across four age groups (Under 25 years, 25 to 44 years, 45 to 64 years, and 65 years and over) following an initial analysis and categorization. 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 the distribution of median household income among distinct age brackets of householders in Sterling. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Sterling. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

    Key observations: Insights from 2023

    In terms of income distribution across age cohorts, in Sterling, householders within the 25 to 44 years age group have the highest median household income at $53,605, followed by those in the 45 to 64 years age group with an income of $44,459. Meanwhile householders within the under 25 years age group report the second lowest median household income of $43,533. Notably, householders within the 65 years and over age group, had the lowest median household income at $38,469.

    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.

    Age groups classifications include:

    • Under 25 years
    • 25 to 44 years
    • 45 to 64 years
    • 65 years and over

    Variables / Data Columns

    • Age Of The Head Of Household: This column presents the age of the head of household
    • Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

    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 Sterling median household income by age. You can refer the same here

  17. U.S. average annual pay of employees in Ohio 2001-2023

    • statista.com
    Updated Sep 12, 2024
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    Statista (2024). U.S. average annual pay of employees in Ohio 2001-2023 [Dataset]. https://www.statista.com/statistics/305773/ohio-annual-pay/
    Explore at:
    Dataset updated
    Sep 12, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2023, the average annual pay of employees in Ohio totaled to 63,083 U.S. dollars. This is both an increase from the previous year, and from 2001 levels when this figure stood at 33,283 U.S. dollars.

  18. Employee wages 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). Employee wages by industry, annual [Dataset]. http://doi.org/10.25318/1410006401-eng
    Explore at:
    Dataset updated
    Jan 24, 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.

  19. T

    United States - Employed full time: Wage and salary workers: Some college or...

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Aug 26, 2020
    + more versions
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    TRADING ECONOMICS (2020). United States - Employed full time: Wage and salary workers: Some college or associate degree: 25 years and over: Black or African American [Dataset]. https://tradingeconomics.com/united-states/employed-full-time-wage-and-salary-workers-some-college-or-associate-degree-25-years-and-over-black-or-african-american-fed-data.html
    Explore at:
    excel, json, xml, csvAvailable download formats
    Dataset updated
    Aug 26, 2020
    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 1, 1976 - Dec 31, 2025
    Area covered
    United States
    Description

    United States - Employed full time: Wage and salary workers: Some college or associate degree: 25 years and over: Black or African American was 4318.00000 Thous. of Persons in January of 2024, according to the United States Federal Reserve. Historically, United States - Employed full time: Wage and salary workers: Some college or associate degree: 25 years and over: Black or African American reached a record high of 4425.00000 in January of 2023 and a record low of 3267.00000 in January of 2004. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Wage and salary workers: Some college or associate degree: 25 years and over: Black or African American - last updated from the United States Federal Reserve on June of 2025.

  20. ACS Median Household Income Variables - Boundaries

    • hub.arcgis.com
    • coronavirus-resources.esri.com
    • +10more
    Updated Oct 22, 2018
    + more versions
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    Esri (2018). ACS Median Household Income Variables - Boundaries [Dataset]. https://hub.arcgis.com/maps/45ede6d6ff7e4cbbbffa60d34227e462
    Explore at:
    Dataset updated
    Oct 22, 2018
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer shows median household income by race and by age of householder. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Median income and income source is based on income in past 12 months of survey. This layer is symbolized to show median household income. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B19013B, B19013C, B19013D, B19013E, B19013F, B19013G, B19013H, B19013I, B19049, B19053Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

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TRADING ECONOMICS, United States Average Hourly Wages [Dataset]. https://tradingeconomics.com/united-states/wages

United States Average Hourly Wages

United States Average Hourly Wages - Historical Dataset (1964-01-31/2025-05-31)

Explore at:
37 scholarly articles cite this dataset (View in Google Scholar)
json, csv, xml, excelAvailable 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, 1964 - May 31, 2025
Area covered
United States
Description

Wages in the United States increased to 31.18 USD/Hour in May from 31.06 USD/Hour in April 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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