95 datasets found
  1. U.S. wealth distribution Q2 2024

    • statista.com
    • ai-chatbox.pro
    Updated Oct 29, 2024
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    Statista (2024). U.S. wealth distribution Q2 2024 [Dataset]. https://www.statista.com/statistics/203961/wealth-distribution-for-the-us/
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    Dataset updated
    Oct 29, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In the first quarter of 2024, almost two-thirds percent of the total wealth in the United States was owned by the top 10 percent of earners. In comparison, the lowest 50 percent of earners only owned 2.5 percent of the total wealth. Income inequality in the U.S. Despite the idea that the United States is a country where hard work and pulling yourself up by your bootstraps will inevitably lead to success, this is often not the case. In 2023, 7.4 percent of U.S. households had an annual income under 15,000 U.S. dollars. With such a small percentage of people in the United States owning such a vast majority of the country’s wealth, the gap between the rich and poor in America remains stark. The top one percent The United States follows closely behind China as the country with the most billionaires in the world. Elon Musk alone held around 219 billion U.S. dollars in 2022. Over the past 50 years, the CEO-to-worker compensation ratio has exploded, causing the gap between rich and poor to grow, with some economists theorizing that this gap is the largest it has been since right before the Great Depression.

  2. U.S. household income distribution 2023

    • statista.com
    Updated Sep 16, 2024
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    Statista (2024). U.S. household income distribution 2023 [Dataset]. https://www.statista.com/statistics/203183/percentage-distribution-of-household-income-in-the-us/
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    Dataset updated
    Sep 16, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, just over 50 percent of Americans had an annual household income that was less than 75,000 U.S. dollars. The median household income was 80,610 U.S. dollars in 2023. Income and wealth in the United States After the economic recession in 2009, income inequality in the U.S. is more prominent across many metropolitan areas. The Northeast region is regarded as one of the wealthiest in the country. Maryland, New Jersey, and Massachusetts were among the states with the highest median household income in 2020. In terms of income by race and ethnicity, the average income of Asian households was 94,903 U.S. dollars in 2020, while the median income for Black households was around half of that figure. What is the U.S. poverty threshold? The U.S. Census Bureau annually updates its list of poverty levels. Preliminary estimates show that the average poverty threshold for a family of four people was 26,500 U.S. dollars in 2021, which is around 100 U.S. dollars less than the previous year. There were an estimated 37.9 million people in poverty across the United States in 2021, which was around 11.6 percent of the population. Approximately 19.5 percent of those in poverty were Black, while 8.2 percent were white.

  3. F

    Share of Net Worth Held by the Top 1% (99th to 100th Wealth Percentiles)

    • fred.stlouisfed.org
    json
    Updated Jun 20, 2025
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    (2025). Share of Net Worth Held by the Top 1% (99th to 100th Wealth Percentiles) [Dataset]. https://fred.stlouisfed.org/series/WFRBST01134
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    jsonAvailable download formats
    Dataset updated
    Jun 20, 2025
    License

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

    Description

    Graph and download economic data for Share of Net Worth Held by the Top 1% (99th to 100th Wealth Percentiles) (WFRBST01134) from Q3 1989 to Q1 2025 about net worth, wealth, percentile, Net, and USA.

  4. U.S. household income lowest quintile versus top five percent 2023

    • statista.com
    Updated Sep 17, 2024
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    Statista (2024). U.S. household income lowest quintile versus top five percent 2023 [Dataset]. https://www.statista.com/statistics/203265/household-income-of-low-paid-and-high-paid-workers-in-the-us/
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    Dataset updated
    Sep 17, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Between 1990 and 2023, the mean household income for the low-paid workers in the lowest quintile went from 15,940 U.S. dollars in 1990 to 17,650 U.S. dollars in 2023, while the mean income of the top five percent increased from 285,000 U.S. dollars to 467,100 U.S. dollars over the same period. The income for this period has been adjusted to the 2023 U.S. dollar value.

  5. H

    Data from: The Distribution of Top Incomes in Five Anglo-Saxon Countries...

    • dataverse.harvard.edu
    Updated Jul 23, 2013
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    Tony Atkinson; Andrew Leigh (2013). The Distribution of Top Incomes in Five Anglo-Saxon Countries Over the Long-Run [Dataset]. http://doi.org/10.7910/DVN/VJLFQV
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 23, 2013
    Dataset provided by
    Harvard Dataverse
    Authors
    Tony Atkinson; Andrew Leigh
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Taking five Anglo-Saxon countries that have relatively similar backgrounds and tax systems – Australia, Canada, New Zealand, the UK, and the US – we see that the shares of the very richest exhibit a strikingly similar pattern, falling in the three decades after World War II, before rising sharply from the mid-1970s onwards. The share of the top 1 percent is highly correlated across Anglo-Saxon countries, more so than with the share of the next 4 percent. Controlling for country and year fixed effects, we find that a reduction in the marginal tax rate on wage income is associated with an increase in the share of the top percentile group. Likewise, a fall in the marginal tax rate on investment income (based on a lagged moving average) is associated with a rise in the share of the top percentile group.

  6. Table 3.1a Percentile points from 1 to 99 for total income before and after...

    • gov.uk
    Updated Mar 12, 2025
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    HM Revenue & Customs (2025). Table 3.1a Percentile points from 1 to 99 for total income before and after tax [Dataset]. https://www.gov.uk/government/statistics/percentile-points-from-1-to-99-for-total-income-before-and-after-tax
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    HM Revenue & Customs
    Description

    The table only covers individuals who have some liability to Income Tax. The percentile points have been independently calculated on total income before tax and total income after tax.

    These statistics are classified as accredited official statistics.

    You can find more information about these statistics and collated tables for the latest and previous tax years on the Statistics about personal incomes page.

    Supporting documentation on the methodology used to produce these statistics is available in the release for each tax year.

    Note: comparisons over time may be affected by changes in methodology. Notably, there was a revision to the grossing factors in the 2018 to 2019 publication, which is discussed in the commentary and supporting documentation for that tax year. Further details, including a summary of significant methodological changes over time, data suitability and coverage, are included in the Background Quality Report.

  7. U.S. household income percentage distribution 2023, by race and ethnicity

    • statista.com
    Updated Sep 16, 2024
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    Statista (2024). U.S. household income percentage distribution 2023, by race and ethnicity [Dataset]. https://www.statista.com/statistics/203207/percentage-distribution-of-household-income-in-the-us-by-ethnic-group/
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    Dataset updated
    Sep 16, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, about 26.9 percent of Asian private households in the U.S. had an annual income of 200,000 U.S. dollars and more. Comparatively, around 13.9 percent of Black households had an annual income under 15,000 U.S. dollars.

  8. F

    Median Personal Income in the United States

    • fred.stlouisfed.org
    json
    Updated Sep 10, 2024
    + more versions
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    (2024). Median Personal Income in the United States [Dataset]. https://fred.stlouisfed.org/series/MEPAINUSA646N
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    jsonAvailable download formats
    Dataset updated
    Sep 10, 2024
    License

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

    Area covered
    United States
    Description

    Graph and download economic data for Median Personal Income in the United States (MEPAINUSA646N) from 1974 to 2023 about personal income, personal, median, income, and USA.

  9. F

    Net Worth Held by the Bottom 50% (1st to 50th Wealth Percentiles)

    • fred.stlouisfed.org
    json
    Updated Jun 20, 2025
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    (2025). Net Worth Held by the Bottom 50% (1st to 50th Wealth Percentiles) [Dataset]. https://fred.stlouisfed.org/series/WFRBLB50107
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 20, 2025
    License

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

    Description

    Graph and download economic data for Net Worth Held by the Bottom 50% (1st to 50th Wealth Percentiles) (WFRBLB50107) from Q3 1989 to Q1 2025 about net worth, wealth, percentile, Net, and USA.

  10. Average income of the top percentile households in Israel 2013-2021

    • statista.com
    Updated Oct 9, 2024
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    Statista (2024). Average income of the top percentile households in Israel 2013-2021 [Dataset]. https://www.statista.com/statistics/1497463/israel-annual-average-income-of-top-percentile-households/
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    Dataset updated
    Oct 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Israel
    Description

    In 2021, the average income of households among Israel's highest one percent of earners, reached 4.7 million Israeli shekels, about 1.2 million U.S. dollars. Moreover, incomes peaked in 2017, due to a one-time tax incentive introduced by the government to release "trapped" capital gains tax. Overall, the average income of wealthy families in the country increased by 62 percent between 2013 and 2021.

  11. Household income among the top one percent of earners in Israel 2013-2021,...

    • statista.com
    Updated Oct 16, 2024
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    Statista (2024). Household income among the top one percent of earners in Israel 2013-2021, by source [Dataset]. https://www.statista.com/statistics/1497622/israel-annual-household-income-top-percentile-by-source/
    Explore at:
    Dataset updated
    Oct 16, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Israel
    Description

    Income from capital was the main source of annual household income for the top percentile of earners in Israel during 2021. That year, earnings from capital reached 3.1 million Israeli shekels on average, about 818,000 U.S. dollars, which represented about 66 percent of annual income. Over the period observed, capital income grew significantly, peaking in 2017 at 4.6 million Israeli shekels, about 1.2 million U.S. dollars. The 2017 spike was due to a government decision to implement a one-time tax incentive to release "trapped" capital gains taxes. On the other hand, employment income accounted for almost 28 percent of household earnings among the wealthiest in the country.

  12. F

    Consumer Unit Characteristics: Percent Elementary (1-8) by Number of...

    • fred.stlouisfed.org
    json
    Updated Sep 25, 2024
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    (2024). Consumer Unit Characteristics: Percent Elementary (1-8) by Number of Earners: Single Consumers, No Earner [Dataset]. https://fred.stlouisfed.org/series/CXU980290LB0702M
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 25, 2024
    License

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

    Description

    Graph and download economic data for Consumer Unit Characteristics: Percent Elementary (1-8) by Number of Earners: Single Consumers, No Earner (CXU980290LB0702M) from 1984 to 2023 about elementary, consumer unit, education, percent, consumer, and USA.

  13. Single-earner and dual-earner census families by number of children

    • www150.statcan.gc.ca
    • ouvert.canada.ca
    • +2more
    Updated Jun 27, 2024
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    Government of Canada, Statistics Canada (2024). Single-earner and dual-earner census families by number of children [Dataset]. http://doi.org/10.25318/1110002801-eng
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    Dataset updated
    Jun 27, 2024
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Families of tax filers; Single-earner and dual-earner census families by number of children (final T1 Family File; T1FF).

  14. N

    Income Distribution by Quintile: Mean Household Income in Florence, SC //...

    • neilsberg.com
    csv, json
    Updated Mar 3, 2025
    + more versions
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    Neilsberg Research (2025). Income Distribution by Quintile: Mean Household Income in Florence, SC // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/florence-sc-median-household-income/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Mar 3, 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
    South Carolina, Florence
    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) 2019-2023 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 Florence, SC, 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 10,346, while the mean income for the highest quintile (20% of households with the highest income) is 208,770. This indicates that the top earners earn 20 times compared to the lowest earners.
    • *Top 5%: * The mean household income for the wealthiest population (top 5%) is 368,659, which is 176.59% higher compared to the highest quintile, and 3563.30% higher compared to the lowest quintile.
    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 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 2023 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 Florence median household income. You can refer the same here

  15. a

    Incomes Occupations and Earnings - Seattle Neighborhoods

    • data-seattlecitygis.opendata.arcgis.com
    • data.seattle.gov
    • +1more
    Updated Mar 8, 2024
    + more versions
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    City of Seattle ArcGIS Online (2024). Incomes Occupations and Earnings - Seattle Neighborhoods [Dataset]. https://data-seattlecitygis.opendata.arcgis.com/datasets/SeattleCityGIS::incomes-occupations-and-earnings-seattle-neighborhoods
    Explore at:
    Dataset updated
    Mar 8, 2024
    Dataset authored and provided by
    City of Seattle ArcGIS Online
    Area covered
    Seattle
    Description

    Table from the American Community Survey (ACS) 5-year series on income and earning related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B19025 Aggregate Household Income, B19013 Median Household Income, B19001 Household Income, B19113 Median Family Household Income, B19101 Family Household Income, B19202 Median Nonfamily Household Income, B19201 Nonfamily Household Income, B19301 Per Capita Income/B19313 Aggregate Income/B01001 Sex by Age, C24010 Sex by Occupation of the Civilian Employed Population 16 years and Over, B20017 Median Earnings by Sex by Work Experience for the Population 16 years and over with Earnings, B20001 Sex by Earnings for the Population 16 years and over with Earnings. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.Table created for and used in the Neighborhood Profiles application.Vintages: 2023ACS Table(s): B19013, B19001, B19113, B19101, B19202, B19201, B19301, B19313, B01001, C24010, B20017, B20001, B19025Data downloaded from: Census Bureau's Explore Census Data The 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. 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: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 2020 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.

  16. F

    Income Before Taxes: Income Before Taxes by Deciles of Income Before Taxes:...

    • fred.stlouisfed.org
    json
    Updated Sep 25, 2024
    + more versions
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    (2024). Income Before Taxes: Income Before Taxes by Deciles of Income Before Taxes: Highest 10 Percent (91st to 100th Percentile) [Dataset]. https://fred.stlouisfed.org/series/CXUINCBEFTXLB1511M
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 25, 2024
    License

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

    Description

    Graph and download economic data for Income Before Taxes: Income Before Taxes by Deciles of Income Before Taxes: Highest 10 Percent (91st to 100th Percentile) (CXUINCBEFTXLB1511M) from 2014 to 2023 about percentile, tax, income, and USA.

  17. N

    Income Distribution by Quintile: Mean Household Income in Winchester, VA //...

    • neilsberg.com
    csv, json
    Updated Mar 3, 2025
    + more versions
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    Neilsberg Research (2025). Income Distribution by Quintile: Mean Household Income in Winchester, VA // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/winchester-va-median-household-income/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Mar 3, 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
    Winchester, Virginia
    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) 2019-2023 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 Winchester, VA, 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 14,125, while the mean income for the highest quintile (20% of households with the highest income) is 215,015. This indicates that the top earners earn 15 times compared to the lowest earners.
    • *Top 5%: * The mean household income for the wealthiest population (top 5%) is 344,621, which is 160.28% higher compared to the highest quintile, and 2439.79% higher compared to the lowest quintile.
    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 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 2023 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 Winchester median household income. You can refer the same here

  18. N

    Dickey, ND 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). Dickey, ND 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/dickey-nd-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
    North Dakota, Dickey
    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 Dickey. 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 Dickey, the median income for all workers aged 15 years and older, regardless of work hours, was $44,375 for males and $43,750 for females.

    Based on these incomes, we observe a gender gap percentage of approximately 1%, indicating a significant disparity between the median incomes of males and females in Dickey. Women, regardless of work hours, still earn 99 cents to each dollar earned by men, highlighting an ongoing gender-based wage gap.

    - Full-time workers, aged 15 years and older: In Dickey, for full-time, year-round workers aged 15 years and older, the Census reported a median income of $43,750 for females, while data for males was unavailable due to an insufficient number of sample observations.

    As there was no available median income data for males, conducting a comprehensive assessment of gender-based pay disparity in Dickey was not feasible.

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

  19. 2023 American Community Survey: S2002 | Median Earnings in the Past 12...

    • data.census.gov
    Updated Apr 1, 2010
    + more versions
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    ACS (2010). 2023 American Community Survey: S2002 | Median Earnings in the Past 12 Months (in 2023 Inflation-Adjusted Dollars) of Workers by Sex and Women's Earnings as a Percentage of Men's Earnings by Selected Characteristics (ACS 1-Year Estimates Subject Tables) [Dataset]. https://data.census.gov/table/ACSST1Y2023.S2002?q=Populations+and+People&t=Employment+and+Labor+Force+Status:Age+and+Sex
    Explore at:
    Dataset updated
    Apr 1, 2010
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2023
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..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 roughly 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 ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Industry titles and their 4-digit codes are based on the 2022 North American Industry Classification System. The Industry categories adhere to the guidelines issued in Clarification Memorandum No. 2, "NAICS Alternate Aggregation Structure for Use By U.S. Statistical Agencies," issued by the Office of Management and Budget..Occupation titles and their 4-digit codes are based on the 2018 Standard Occupational Classification..The Class of Worker status "unpaid family workers" may have earnings. Earnings reflect any earnings from all jobs held during the 12 months prior to the ACS interview. The Class of Worker status reflects the job or business held the week prior to the ACS interview, or the last job held by the respondent..When information is missing or inconsistent, the Census Bureau logically assigns an acceptable value using the response to a related question or questions. If a logical assignment is not possible, data are filled using a statistical process called allocation, which uses a similar individual or household to provide a donor value. The "Allocated" section is the number of respondents who received an allocated value for a particular subject..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended dist...

  20. T

    United States Personal Income

    • tradingeconomics.com
    • tr.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated May 30, 2025
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    TRADING ECONOMICS (2025). United States Personal Income [Dataset]. https://tradingeconomics.com/united-states/personal-income
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    csv, json, xml, excelAvailable download formats
    Dataset updated
    May 30, 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
    Feb 28, 1959 - May 31, 2025
    Area covered
    United States
    Description

    Personal Income in the United States decreased 0.40 percent in May of 2025 over the previous month. This dataset provides the latest reported value for - United States Personal Income - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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Statista (2024). U.S. wealth distribution Q2 2024 [Dataset]. https://www.statista.com/statistics/203961/wealth-distribution-for-the-us/
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U.S. wealth distribution Q2 2024

Explore at:
22 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Oct 29, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
United States
Description

In the first quarter of 2024, almost two-thirds percent of the total wealth in the United States was owned by the top 10 percent of earners. In comparison, the lowest 50 percent of earners only owned 2.5 percent of the total wealth. Income inequality in the U.S. Despite the idea that the United States is a country where hard work and pulling yourself up by your bootstraps will inevitably lead to success, this is often not the case. In 2023, 7.4 percent of U.S. households had an annual income under 15,000 U.S. dollars. With such a small percentage of people in the United States owning such a vast majority of the country’s wealth, the gap between the rich and poor in America remains stark. The top one percent The United States follows closely behind China as the country with the most billionaires in the world. Elon Musk alone held around 219 billion U.S. dollars in 2022. Over the past 50 years, the CEO-to-worker compensation ratio has exploded, causing the gap between rich and poor to grow, with some economists theorizing that this gap is the largest it has been since right before the Great Depression.

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