100+ datasets found
  1. U.S. Gini gap between rich and poor 2023, by state

    • statista.com
    Updated Oct 25, 2024
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    Statista (2024). U.S. Gini gap between rich and poor 2023, by state [Dataset]. https://www.statista.com/statistics/227249/greatest-gap-between-rich-and-poor-by-us-state/
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    Dataset updated
    Oct 25, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    New York was the state with the greatest gap between rich and poor, with a Gini coefficient score of 0.52 in 2023. Although not a state, District of Columbia was among the highest Gini coefficients in the United States that year.

  2. Income Inequality in U.S. Counties

    • hub.arcgis.com
    Updated Sep 28, 2015
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    Urban Observatory by Esri (2015). Income Inequality in U.S. Counties [Dataset]. https://hub.arcgis.com/maps/b2db6f24618d4aad9885d2dd51024842
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    Dataset updated
    Sep 28, 2015
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    Description

    Income InequalityThe level of income inequality among households in a county can be measured using the Gini index. A Gini index varies between zero and one. A value of one indicates perfect inequality, where only one household in the county has any income. A value of zero indicates perfect equality, where all households in the county have equal income.The United States, as a country, has a Gini Index of 0.47 for this time period. For comparision in this map, the purple counties have greater income inequality, while orange counties have less inequality of incomes. For reference, Brazil has an index of 0.58 (relatively high inequality) and Denmark has an index of 0.24 (relatively low inequality).The 5-year Gini index for the U.S. was 0.4695 in 2007-2011 and 0.467 in 2006-2010. Appalachian Regional Commission, September 2013Data source: U.S. Census Bureau, 5-Year American Community Survey, 2006-2010 & 2007-2011

  3. U.S. wealth distribution Q2 2024

    • statista.com
    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.

  4. U.S. household income Gini Index 1990-2023

    • statista.com
    Updated Sep 16, 2024
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    Statista (2024). U.S. household income Gini Index 1990-2023 [Dataset]. https://www.statista.com/statistics/219643/gini-coefficient-for-us-individuals-families-and-households/
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    Dataset updated
    Sep 16, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2023, according to the Gini coefficient, household income distribution in the United States was 0.47. This figure was at 0.43 in 1990, which indicates an increase in income inequality in the U.S. over the past 30 years. What is the Gini coefficient? The Gini coefficient, or Gini index, is a statistical measure of economic inequality and wealth distribution among a population. A value of zero represents perfect economic equality, and a value of one represents perfect economic inequality. The Gini coefficient helps to visualize income inequality in a more digestible way. For example, according to the Gini coefficient, the District of Columbia and the state of New York have the greatest amount of income inequality in the U.S. with a score of 0.51, and Utah has the greatest income equality with a score of 0.43. The Gini coefficient around the world The Gini coefficient is also an effective measure to help picture income inequality around the world. For example, in 2018 income inequality was highest in South Africa, while income inequality was lowest in Slovenia.

  5. Income Inequality

    • data.ca.gov
    pdf, xlsx, zip
    Updated Aug 28, 2024
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    Income Inequality [Dataset]. https://data.ca.gov/dataset/income-inequality
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    pdf, xlsx, zipAvailable download formats
    Dataset updated
    Aug 28, 2024
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    License

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

    Description

    This table contains data on income inequality. The primary measure is the Gini index – a measure of the extent to which the distribution of income among families/households within a community deviates from a perfectly equal distribution. The index ranges from 0.0, when all families (households) have equal shares of income (implies perfect equality), to 1.0 when one family (household) has all the income and the rest have none (implies perfect inequality). Index data is provided for California and its counties, regions, and large cities/towns. The data is from the U.S. Census Bureau, American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Income is linked to acquiring resources for healthy living. Both household income and the distribution of income across a society independently contribute to the overall health status of a community. On average Western industrialized nations with large disparities in income distribution tend to have poorer health status than similarly advanced nations with a more equitable distribution of income. Approximately 119,200 (5%) of the 2.4 million U.S. deaths in 2000 are attributable to income inequality. The pathways by which income inequality act to increase adverse health outcomes are not known with certainty, but policies that provide for a strong safety net of health and social services have been identified as potential buffers. More information about the data table and a data dictionary can be found in the About/Attachments section.

  6. F

    GINI Index for the United States

    • fred.stlouisfed.org
    json
    Updated Sep 19, 2024
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    (2024). GINI Index for the United States [Dataset]. https://fred.stlouisfed.org/series/SIPOVGINIUSA
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    jsonAvailable download formats
    Dataset updated
    Sep 19, 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 GINI Index for the United States (SIPOVGINIUSA) from 1963 to 2022 about gini, indexes, and USA.

  7. U.S. quarterly wealth distribution 1989-2024, by income percentile

    • statista.com
    Updated Mar 19, 2025
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    Statista (2025). U.S. quarterly wealth distribution 1989-2024, by income percentile [Dataset]. https://www.statista.com/statistics/299460/distribution-of-wealth-in-the-united-states/
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    Dataset updated
    Mar 19, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In the third quarter of 2024, the top ten percent of earners in the United States held over 67 percent of total wealth. This is fairly consistent with the second quarter of 2024. Comparatively, the wealth of the bottom 50 percent of earners has been slowly increasing since the start of the 2010s, though remains low. Wealth distribution in the United States by generation can be found here.

  8. U.S. household income distribution 2023

    • flwrdeptvarieties.store
    • statista.com
    Updated Jul 3, 2024
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    Statista Research Department (2024). U.S. household income distribution 2023 [Dataset]. https://flwrdeptvarieties.store/?_=%2Ftopics%2F12226%2Feconomic-inequality-worldwide%2F%23zUpilBfjadnZ6q5i9BcSHcxNYoVKuimb
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    Dataset updated
    Jul 3, 2024
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    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.

  9. F

    Share of Net Worth Held by the Top 0.1% (99.9th to 100th Wealth Percentiles)...

    • fred.stlouisfed.org
    json
    Updated Mar 21, 2025
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    Share of Net Worth Held by the Top 0.1% (99.9th to 100th Wealth Percentiles) [Dataset]. https://fred.stlouisfed.org/series/WFRBSTP1300
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    jsonAvailable download formats
    Dataset updated
    Mar 21, 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 0.1% (99.9th to 100th Wealth Percentiles) (WFRBSTP1300) from Q3 1989 to Q4 2024 about shares, net worth, wealth, percentile, Net, and USA.

  10. a

    Income Disparity: Concentrations of Wealth and Poverty in the USA

    • chi-phi-nmcdc.opendata.arcgis.com
    • hub.arcgis.com
    Updated Apr 27, 2022
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    New Mexico Community Data Collaborative (2022). Income Disparity: Concentrations of Wealth and Poverty in the USA [Dataset]. https://chi-phi-nmcdc.opendata.arcgis.com/maps/1d4bab3a6ed74c17a2d99645ffdc931f
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    Dataset updated
    Apr 27, 2022
    Dataset authored and provided by
    New Mexico Community Data Collaborative
    Area covered
    Description

    This map shows households within high ($200,000 or more) and low (less than $25,000) annual income ranges. This is shown as a percentage of total households. The data is attached to tract, county, and state centroids and shows:Percent of households making less than $25,000 annuallyPercent of households making $200,000 or more annuallyThe data shown is household income in the past 12 months. These are the American Community Survey (ACS) most current 5-year estimates: Table B19001. The data layer is updated annually, so this map always shows the most current values from the U.S. Census Bureau. To find the layer used in this map and see the full metadata, visit this Living Atlas item.These categories were constructed using an Arcade expression, which groups the lowest census income categories and normalizes them by total households.

  11. d

    Replication Code for \"Income Inequality in the United States: Using Tax...

    • dataone.org
    • dataverse.harvard.edu
    Updated Dec 16, 2023
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    Auten, Gerald; Splinter, David (2023). Replication Code for \"Income Inequality in the United States: Using Tax Data to Measure Long-Term Trends\" [Dataset]. http://doi.org/10.7910/DVN/NZ8YIT
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    Dataset updated
    Dec 16, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Auten, Gerald; Splinter, David
    Description

    This is the replication code package for "Income Inequality in the United States: Using Tax Data to Measure Long-Term Trends," accepted in 2023 by the Journal of Political Economy.

  12. N

    Income Distribution by Quintile: Mean Household Income in United States //...

    • neilsberg.com
    csv, json
    Updated Mar 3, 2025
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    Neilsberg Research (2025). Income Distribution by Quintile: Mean Household Income in United States // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/4845fa5d-f81d-11ef-a994-3860777c1fe6/
    Explore at:
    json, csvAvailable 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
    United States
    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 United States, 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 16,840, while the mean income for the highest quintile (20% of households with the highest income) is 285,351. This indicates that the top earners earn 17 times compared to the lowest earners.
    • *Top 5%: * The mean household income for the wealthiest population (top 5%) is 515,555, which is 180.67% higher compared to the highest quintile, and 3061.49% 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 United States median household income. You can refer the same here

  13. d

    Income Inequality and Redistributive Spending in the U.S. States

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 21, 2023
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    Moldogaziev, Tima T.; Monogan III, James E.; Witko, Christopher (2023). Income Inequality and Redistributive Spending in the U.S. States [Dataset]. http://doi.org/10.7910/DVN/PQUUEF
    Explore at:
    Dataset updated
    Nov 21, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Moldogaziev, Tima T.; Monogan III, James E.; Witko, Christopher
    Description

    Data on redistributive spending in the 50 American states from 1974-2012. Also includes two Gini coefficient measures, economic measures, and demographic measures.

  14. F

    Income Inequality in Orange County, CA

    • fred.stlouisfed.org
    json
    Updated Dec 12, 2024
    + more versions
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    (2024). Income Inequality in Orange County, CA [Dataset]. https://fred.stlouisfed.org/series/2020RATIO006059
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Dec 12, 2024
    License

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

    Area covered
    Orange County, California
    Description

    Graph and download economic data for Income Inequality in Orange County, CA (2020RATIO006059) from 2010 to 2023 about Orange County, CA; inequality; Los Angeles; CA; income; and USA.

  15. H

    Data from: The Standardized World Income Inequality Database, Versions 8-9

    • dataverse.harvard.edu
    • search.dataone.org
    Updated Dec 26, 2024
    + more versions
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    Frederick Solt (2024). The Standardized World Income Inequality Database, Versions 8-9 [Dataset]. http://doi.org/10.7910/DVN/LM4OWF
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 26, 2024
    Dataset provided by
    Harvard Dataverse
    Authors
    Frederick Solt
    License

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

    Time period covered
    1960 - 2023
    Dataset funded by
    NSF
    Description

    Cross-national research on the causes and consequences of income inequality has been hindered by the limitations of the existing inequality datasets: greater coverage across countries and over time has been available from these sources only at the cost of significantly reduced comparability across observations. The goal of the Standardized World Income Inequality Database (SWIID) is to meet the needs of those engaged in broadly cross-national research by maximizing the comparability of income inequality data while maintaining the widest possible coverage across countries and over time. The SWIID’s income inequality estimates are based on thousands of reported Gini indices from hundreds of published sources, including the OECD Income Distribution Database, the Socio-Economic Database for Latin America and the Caribbean generated by CEDLAS and the World Bank, Eurostat, the World Bank’s PovcalNet, the UN Economic Commission for Latin America and the Caribbean, national statistical offices around the world, and academic studies while minimizing reliance on problematic assumptions by using as much information as possible from proximate years within the same country. The data collected and harmonized by the Luxembourg Income Study is employed as the standard. The SWIID currently incorporates comparable Gini indices of disposable and market income inequality for 199 countries for as many years as possible from 1960 to the present; it also includes information on absolute and relative redistribution.

  16. N

    United States 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). United States 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/a53c92b0-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
    United States
    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 United States. 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 United States, the median income for all workers aged 15 years and older, regardless of work hours, was $48,138 for males and $32,546 for females.

    These income figures highlight a substantial gender-based income gap in United States. Women, regardless of work hours, earn 68 cents for each dollar earned by men. This significant gender pay gap, approximately 32%, underscores concerning gender-based income inequality in the country of United States.

    - Full-time workers, aged 15 years and older: In United States, among full-time, year-round workers aged 15 years and older, males earned a median income of $67,966, while females earned $54,999, leading to a 19% gender pay gap among full-time workers. This illustrates that women earn 81 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 United States.

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

  17. F

    Income Inequality in Montgomery County, MD

    • fred.stlouisfed.org
    json
    Updated Dec 12, 2024
    + more versions
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    (2024). Income Inequality in Montgomery County, MD [Dataset]. https://fred.stlouisfed.org/series/2020RATIO024031
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Dec 12, 2024
    License

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

    Area covered
    Montgomery County, Maryland
    Description

    Graph and download economic data for Income Inequality in Montgomery County, MD (2020RATIO024031) from 2010 to 2023 about Montgomery County, MD; inequality; Washington; MD; income; and USA.

  18. T

    Income Inequality in Westchester County, NY

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Dec 20, 2023
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    TRADING ECONOMICS (2023). Income Inequality in Westchester County, NY [Dataset]. https://tradingeconomics.com/united-states/income-inequality-in-westchester-county-ny-fed-data.html
    Explore at:
    csv, xml, json, excelAvailable download formats
    Dataset updated
    Dec 20, 2023
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Westchester County, New York
    Description

    Income Inequality in Westchester County, NY was 25.51079 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in Westchester County, NY reached a record high of 25.51079 in January of 2023 and a record low of 21.21995 in January of 2010. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in Westchester County, NY - last updated from the United States Federal Reserve on March of 2025.

  19. U.S. household Gini index for income distribution 2023, by race and...

    • statista.com
    Updated Oct 25, 2024
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    Statista (2024). U.S. household Gini index for income distribution 2023, by race and ethnicity [Dataset]. https://www.statista.com/statistics/374653/gini-index-for-income-distribution-equality-for-us-families-by-race-origin/
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    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 Gini index for Black households in the United States stood at 0.5, which was higher than the national index that year. The Census Bureau defines the Gini index as “a statistical measure of income inequality ranging from zero to one. A measure of one indicates perfect inequality, i.e., one household having all the income and the rest having none. A measure of zero indicates perfect equality, i.e., all households having an equal share of income.”

  20. T

    Income Inequality in Palm Beach County, FL

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Feb 8, 2020
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    TRADING ECONOMICS (2020). Income Inequality in Palm Beach County, FL [Dataset]. https://tradingeconomics.com/united-states/income-inequality-in-palm-beach-county-fl-fed-data.html
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    json, xml, csv, excelAvailable download formats
    Dataset updated
    Feb 8, 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
    Palm Beach County, Florida
    Description

    Income Inequality in Palm Beach County, FL was 19.40377 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in Palm Beach County, FL reached a record high of 19.47998 in January of 2022 and a record low of 16.92851 in January of 2010. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in Palm Beach County, FL - last updated from the United States Federal Reserve on March of 2025.

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Link copied
Close
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Statista (2024). U.S. Gini gap between rich and poor 2023, by state [Dataset]. https://www.statista.com/statistics/227249/greatest-gap-between-rich-and-poor-by-us-state/
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U.S. Gini gap between rich and poor 2023, by state

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13 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Oct 25, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2023
Area covered
United States
Description

New York was the state with the greatest gap between rich and poor, with a Gini coefficient score of 0.52 in 2023. Although not a state, District of Columbia was among the highest Gini coefficients in the United States that year.

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