77 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. Gini gap between rich and poor 2023, by state

    • statista.com
    • ai-chatbox.pro
    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.

  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. o

    Data from: GEOWEALTH-US: Spatial wealth inequality data for the United...

    • openicpsr.org
    delimited
    Updated Jun 23, 2023
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    Joel Suss; Dylan Connor; Tom Kemeny (2023). GEOWEALTH-US: Spatial wealth inequality data for the United States, 1960-2020 [Dataset]. http://doi.org/10.3886/E192306V4
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    delimitedAvailable download formats
    Dataset updated
    Jun 23, 2023
    Dataset provided by
    University of Toronto
    Arizona State University
    London School of Economics
    Authors
    Joel Suss; Dylan Connor; Tom Kemeny
    License

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

    Time period covered
    1960 - 2020
    Area covered
    United States
    Description

    Wealth inequality has been sharply rising in the United States and across many other high-income countries. Due to a lack of data, we know little about how this trend has unfolded across locations within countries. Investigating this subnational geography of wealth is crucial, as from one generation to the next, wealth powerfully shapes opportunity and disadvantage across individuals and communities. Using machine-learning-based imputation to link newly assembled national historical surveys conducted by the U.S. Federal Reserve to population survey microdata, the data presented in this paper addresses this gap. The Geographic Wealth Inequality Database ("GEOWEALTH-US") provides the first estimates of the level and distribution of wealth at various geographical scales within the United States from 1960 to 2020. The GEOWEALTH-US database enables new lines investigation into the contribution of inter-regional wealth patterns to major societal challenges including wealth concentration, spatial income inequality, equality of opportunity, housing unaffordability, and political polarization.

  5. Gini coefficient income distribution inequality in Latin America 2023, by...

    • statista.com
    • ai-chatbox.pro
    Updated May 6, 2025
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    Statista (2025). Gini coefficient income distribution inequality in Latin America 2023, by country [Dataset]. https://www.statista.com/statistics/980285/income-distribution-gini-coefficient-latin-america-caribbean-country/
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    Dataset updated
    May 6, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    LAC, Latin America
    Description

    Based on the degree of inequality in income distribution measured by the Gini coefficient, Colombia was the most unequal country in Latin America as of 2022. Colombia's Gini coefficient amounted to 54.8. The Dominican Republic recorded the lowest Gini coefficient at 37, even below Uruguay and Chile, which are some of the countries with the highest human development indexes in Latin America. The Gini coefficient explained The Gini coefficient measures the deviation of the distribution of income among individuals or households in a given country from a perfectly equal distribution. A value of 0 represents absolute equality, whereas 100 would be the highest possible degree of inequality. This measurement reflects the degree of wealth inequality at a certain moment in time, though it may fail to capture how average levels of income improve or worsen over time. What affects the Gini coefficient in Latin America? Latin America, as other developing regions in the world, generally records high rates of inequality, with a Gini coefficient ranging between 37 and 55 points according to the latest available data from the reporting period 2010-2023. According to the Human Development Report, wealth redistribution by means of tax transfers improves Latin America's Gini coefficient to a lesser degree than it does in advanced economies. Wider access to education and health services, on the other hand, have been proven to have a greater direct effect in improving Gini coefficient measurements in the region.

  6. Latin America: wealth inequality based on income concentration by country...

    • statista.com
    Updated Jul 24, 2024
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    Statista (2024). Latin America: wealth inequality based on income concentration by country 2022 [Dataset]. https://www.statista.com/statistics/1050681/latin-america-income-inequality-country/
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    Dataset updated
    Jul 24, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Latin America, LAC
    Description

    Brazil is one of the most unequal countries in terms of income in Latin America. In 2022, it was estimated that almost 57 percent of the income generated in Brazil was held by the richest 20 percent of its population. Among the Latin American countries with available data included in this graph, Colombia came in first, as the wealthiest 20 percent of the Colombian population held over 59 percent of the country's total income.

  7. Income Inequality in U.S. Counties

    • hub.arcgis.com
    Updated Sep 29, 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 29, 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

  8. F

    GINI Index for the United States

    • fred.stlouisfed.org
    json
    Updated Jun 5, 2025
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    (2025). GINI Index for the United States [Dataset]. https://fred.stlouisfed.org/series/SIPOVGINIUSA
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    jsonAvailable download formats
    Dataset updated
    Jun 5, 2025
    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 2023 about gini, indexes, and USA.

  9. 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.

  10. F

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

    • fred.stlouisfed.org
    json
    Updated Jun 20, 2025
    + more versions
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    (2025). Share of Net Worth Held by the Bottom 50% (1st to 50th Wealth Percentiles) [Dataset]. https://fred.stlouisfed.org/series/WFRBSB50215
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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 Bottom 50% (1st to 50th Wealth Percentiles) (WFRBSB50215) from Q3 1989 to Q1 2025 about net worth, wealth, percentile, Net, and USA.

  11. Data from: The impact of income, land, and wealth inequality on agricultural...

    • zenodo.org
    • datadryad.org
    bin
    Updated Jun 1, 2022
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    Michele Graziano Ceddia; Michele Graziano Ceddia (2022). Data from: The impact of income, land, and wealth inequality on agricultural expansion in Latin America [Dataset]. http://doi.org/10.5061/dryad.0sn4046
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    binAvailable download formats
    Dataset updated
    Jun 1, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Michele Graziano Ceddia; Michele Graziano Ceddia
    License

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

    Area covered
    Latin America
    Description

    Agricultural expansion remains the most prominent proximate cause of tropical deforestation in Latin America, a region characterized by deforestation rates substantially above the world average and extremely high inequality. This paper deploys several multivariate statistical models to test whether different aspects of inequality, within a context of increasing agricultural productivity, promote agricultural expansion (Jevons paradox) or contraction (land-sparing) in 10 Latin American countries over 1990–2010. Here I show the existence of distinct patterns between the instantaneous and the overall (i.e., accounting for temporal lags) effect of increasing agricultural productivity, conditional on the degree of income, land, and wealth inequality. In a context of perfect equality, the instantaneous effect of increases in agricultural productivity is to promote agricultural expansion (Jevons paradox). When temporal lags are accounted for, agricultural productivity appears to be mainly land-sparing. Increases in the level of inequality, in all its forms, promote agricultural expansion, thus eroding the land-sparing effects of increasing productivity. The results also suggest that the instantaneous impact of inequality is larger than the overall effect (accounting for temporal lags) and that the effects of income inequality are stronger than those of land and wealth inequality, respectively. Reaping the benefits of increasing agricultural productivity, and achieving sustainable agricultural intensification in Latin America, requires policy interventions that specifically address inequality.

  12. H

    Replication Data for: "Wealth and Policymaking in the U.S. House of...

    • dataverse.harvard.edu
    Updated May 19, 2025
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    Darrian Stacy (2025). Replication Data for: "Wealth and Policymaking in the U.S. House of Representatives" [Dataset]. http://doi.org/10.7910/DVN/OWY4TK
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 19, 2025
    Dataset provided by
    Harvard Dataverse
    Authors
    Darrian Stacy
    License

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

    Area covered
    United States
    Description

    Data and replication code for "Wealth and Policymaking in the U.S. House of Representatives" by Darrian Stacy.

  13. F

    Income Inequality in New York County, NY

    • fred.stlouisfed.org
    json
    Updated Dec 12, 2024
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    (2024). Income Inequality in New York County, NY [Dataset]. https://fred.stlouisfed.org/series/2020RATIO036061
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    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
    New York, New York, Manhattan, New York County
    Description

    Graph and download economic data for Income Inequality in New York County, NY (2020RATIO036061) from 2010 to 2023 about New York County, NY; inequality; New York; NY; income; and USA.

  14. o

    Replication data for: Earnings Inequality and Other Determinants of Wealth...

    • openicpsr.org
    Updated May 1, 2017
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    Jess Benhabib; Alberto Bisin; Mi Luo (2017). Replication data for: Earnings Inequality and Other Determinants of Wealth Inequality [Dataset]. http://doi.org/10.3886/E113490V1
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    Dataset updated
    May 1, 2017
    Dataset provided by
    American Economic Association
    Authors
    Jess Benhabib; Alberto Bisin; Mi Luo
    Description

    We study the relation between the distribution of labor earnings and the distribution of wealth. We show, theoretically as well as empirically, that while labor earnings and precautionary savings are important determinants of wealth inequality factors, they cannot by themselves account for the thick tail of (the large top shares in) the observed distribution of wealth. Other determinants, like stochastic returns to wealth, as well as savings rates and rates of returns increasing in wealth, need to be accounted for.

  15. Global wealth distribution 2023, by region

    • statista.com
    • ai-chatbox.pro
    Updated Jun 16, 2025
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    Statista (2025). Global wealth distribution 2023, by region [Dataset]. https://www.statista.com/statistics/1341660/global-wealth-distribution-region/
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    Dataset updated
    Jun 16, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Worldwide
    Description

    In 2023, the Middle East and North Africa, and Latin America were the regions with the lowest level of distribution of wealth worldwide, with the richest ten percent holding around ** percent of the total wealth. On the other hand, in Europe, the richest ten percent held around ** percent of the wealth. East and South Asia were the regions where the poorest half of the population held the highest share of the wealth, but still only around **** percent, underlining the high levels of wealth inequalities worldwide.

  16. Gini coefficient income distribution inequality in Brazil 2010-2023

    • ai-chatbox.pro
    • statista.com
    Updated May 6, 2025
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    Statista (2025). Gini coefficient income distribution inequality in Brazil 2010-2023 [Dataset]. https://www.ai-chatbox.pro/?_=%2Fstatistics%2F981226%2Fincome-distribution-gini-coefficient-brazil%2F%23XgboD02vawLKoDs%2BT%2BQLIV8B6B4Q9itA
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    Dataset updated
    May 6, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Brazil
    Description

    Between 2010 and 2023, Brazil's data on the degree of inequality in wealth distribution based on the Gini coefficient reached 52. That year, Brazil was deemed one of the most unequal country in Latin America. Prior to 2010, wealth distribution in Brazil had shown signs of improvement, with the Gini coefficient decreasing in the previous 3 reporting periods. The Gini coefficient measures the deviation of the distribution of income (or consumption) among individuals or households in a given country from a perfectly equal distribution. A value of 0 represents absolute equality, whereas 100 would be the highest possible degree of inequality.

  17. F

    Income Inequality in Denver County, CO

    • fred.stlouisfed.org
    json
    Updated Dec 12, 2024
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    (2024). Income Inequality in Denver County, CO [Dataset]. https://fred.stlouisfed.org/series/2020RATIO008031
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    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
    Denver County, Denver, Colorado
    Description

    Graph and download economic data for Income Inequality in Denver County, CO (2020RATIO008031) from 2010 to 2023 about Denver County, CO; Denver; inequality; CO; income; and USA.

  18. Gini index: inequality of income distribution in China 2005-2023

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Gini index: inequality of income distribution in China 2005-2023 [Dataset]. https://www.statista.com/statistics/250400/inequality-of-income-distribution-in-china-based-on-the-gini-index/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    This statistic shows the inequality of income distribution in China from 2005 to 2023 based on the Gini Index. In 2023, China reached a score of ************ points. The Gini Index is a statistical measure that is used to represent unequal distributions, e.g. income distribution. It can take any value between 1 and 100 points (or 0 and 1). The closer the value is to 100 the greater is the inequality. 40 or 0.4 is the warning level set by the United Nations. The Gini Index for South Korea had ranged at about **** in 2022. Income distribution in China The Gini coefficient is used to measure the income inequality of a country. The United States, the World Bank, the US Central Intelligence Agency, and the Organization for Economic Co-operation and Development all provide their own measurement of the Gini coefficient, varying in data collection and survey methods. According to the United Nations Development Programme, countries with the largest income inequality based on the Gini index are mainly located in Africa and Latin America, with South Africa displaying the world's highest value in 2022. The world's most equal countries, on the contrary, are situated mostly in Europe. The United States' Gini for household income has increased by around ten percent since 1990, to **** in 2023. Development of inequality in China Growing inequality counts as one of the biggest social, economic, and political challenges to many countries, especially emerging markets. Over the last 20 years, China has become one of the world's largest economies. As parts of the society have become more and more affluent, the country's Gini coefficient has also grown sharply over the last decades. As shown by the graph at hand, China's Gini coefficient ranged at a level higher than the warning line for increasing risk of social unrest over the last decade. However, the situation has slightly improved since 2008, when the Gini coefficient had reached the highest value of recent times.

  19. F

    Income Inequality in Santa Cruz County, CA

    • fred.stlouisfed.org
    json
    Updated Dec 12, 2024
    + more versions
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    (2024). Income Inequality in Santa Cruz County, CA [Dataset]. https://fred.stlouisfed.org/series/2020RATIO006087
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    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
    Santa Cruz County, California
    Description

    Graph and download economic data for Income Inequality in Santa Cruz County, CA (2020RATIO006087) from 2010 to 2023 about Santa Cruz County, CA; Santa Cruz; inequality; CA; income; and USA.

  20. o

    Data and code for "Changes in the Distribution of Black and White Wealth...

    • openicpsr.org
    Updated Sep 11, 2023
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    Ellora Derenoncourt; Chi Hyun Kim; Moritz Kuhn; Moritz Schularick (2023). Data and code for "Changes in the Distribution of Black and White Wealth Since the US Civil War" [Dataset]. http://doi.org/10.3886/E193730V1
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    Dataset updated
    Sep 11, 2023
    Dataset provided by
    American Economic Association
    Authors
    Ellora Derenoncourt; Chi Hyun Kim; Moritz Kuhn; Moritz Schularick
    License

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

    Area covered
    United States
    Description

    The difference in the average wealth of Black and white Americans narrowed in the first century after the Civil War, but remained large and even widened again after 1980. Given high levels of wealth concentration both historically and today, dynamics at the average may not capture important heterogeneity in racial wealth gaps across the distribution. This paper looks into the historical evolution of the Black and white wealth distributions since Emancipation. The picture that emerges is an even starker one than racial wealth inequality at the mean. Tracing, for the first time, the evolution of wealth of the median Black household and the gap between the typical Black and white household over time, we estimate that the majority of Black households only began to dispose of measurable wealth around World War II. While the civil rights era brought substantial wealth gains for the median Black household, the gap between Black and white wealth at the median has not changed much since the 1970s. The top and the bottom of the wealth distribution show even greater persistence, with Black households consistently over-represented in the bottom half of the wealth distribution and under-represented in the top-10% over the past seven decades.

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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

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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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