63 datasets found
  1. 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.

  2. 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.

  3. 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/
    Explore at:
    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.

  4. 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.

  5. 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.

  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. N

    United States annual median income by work experience and sex dataset: Aged...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
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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

  8. U.S. households Gini index for income distribution equality 1990-2023

    • statista.com
    Updated Oct 25, 2024
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    Statista (2024). U.S. households Gini index for income distribution equality 1990-2023 [Dataset]. https://www.statista.com/statistics/374610/gini-index-for-income-distribution-equality-for-us-households/
    Explore at:
    Dataset updated
    Oct 25, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2023, the Gini Index for all U.S. households was 0.49. The U.S. 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.”

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

    • flwrdeptvarieties.store
    • statista.com
    Updated Nov 15, 2024
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    Statista Research Department (2024). Gini index: inequality of income distribution in China 2005-2023 [Dataset]. https://flwrdeptvarieties.store/?_=%2Ftopics%2F7157%2Fregional-disparities-in-china%2F%23zUpilBfjadnL7vc%2F8wIHANZKd8oHtis%3D
    Explore at:
    Dataset updated
    Nov 15, 2024
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    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 46.5 (0.465) 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 0.32 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 0.47 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.

  10. F

    Income Before Taxes: Wages and Salaries by Quintiles of Income Before Taxes:...

    • fred.stlouisfed.org
    json
    Updated Sep 25, 2024
    + more versions
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    (2024). Income Before Taxes: Wages and Salaries by Quintiles of Income Before Taxes: Lowest 20 Percent (1st to 20th Percentile) [Dataset]. https://fred.stlouisfed.org/series/CXU900000LB0102M
    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: Wages and Salaries by Quintiles of Income Before Taxes: Lowest 20 Percent (1st to 20th Percentile) (CXU900000LB0102M) from 1984 to 2023 about percentile, salaries, tax, wages, income, and USA.

  11. Inequality in the U.S. - share of citizens who see the nation divided

    • statista.com
    Updated Sep 29, 2011
    + more versions
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    Statista (2011). Inequality in the U.S. - share of citizens who see the nation divided [Dataset]. https://www.statista.com/statistics/204661/share-of-us-citizens-who-say-the-nation-is-divided-by-selected-characteristics/
    Explore at:
    Dataset updated
    Sep 29, 2011
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Sep 22, 2011 - Sep 25, 2011
    Area covered
    United States
    Description

    The statistic shows a representative survey on the public view on whether the United States are divided into 'haves' and have-nots'. The survey was done from September 22 to September 25, 2011. About 53 percent of respondents with an income of less than 30,000 U.S. dollars think the nation is divided.

  12. 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/
    Explore at:
    Dataset updated
    Oct 25, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, the 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.”

  13. U.S. Gini index for income distribution equality by race/origin 2023

    • statista.com
    Updated Oct 23, 2024
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    Statista (2024). U.S. Gini index for income distribution equality by race/origin 2023 [Dataset]. https://www.statista.com/statistics/374612/gini-index-for-income-distribution-equality-for-us-households-by-race-hispanic-origin/
    Explore at:
    Dataset updated
    Oct 23, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, the Gini index for households of Asian origin in the United States stood at 0.48. 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 rest having none. A measure of zero indicates perfect equality, i.e., all households having an equal share of income.”

  14. N

    Monterey County, CA annual median income by work experience and sex dataset:...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Monterey County, CA 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/monterey-county-ca-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
    Monterey County, California
    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 Monterey County. 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 Monterey County, the median income for all workers aged 15 years and older, regardless of work hours, was $42,319 for males and $32,491 for females.

    These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 23% between the median incomes of males and females in Monterey County. With women, regardless of work hours, earning 77 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecounty of Monterey County.

    - Full-time workers, aged 15 years and older: In Monterey County, among full-time, year-round workers aged 15 years and older, males earned a median income of $59,998, while females earned $53,465, resulting in a 11% gender pay gap among full-time workers. This illustrates that women earn 89 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the county of Monterey County.

    Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Monterey County.

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

  15. U.S. median household income 1967-2023, by race and ethnicity

    • statista.com
    Updated Oct 28, 2024
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    U.S. median household income 1967-2023, by race and ethnicity [Dataset]. https://www.statista.com/statistics/1086359/median-household-income-race-us/
    Explore at:
    Dataset updated
    Oct 28, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In the U.S., median household income rose from 51,570 U.S. dollars in 1967 to 80,610 dollars in 2023. In terms of broad ethnic groups, Black Americans have consistently had the lowest median income in the given years, while Asian Americans have the highest; median income in Asian American households has typically been around double that of Black Americans.

  16. U.S. wealth distribution 1990-2024, by generation

    • statista.com
    Updated Aug 26, 2024
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    Statista (2024). U.S. wealth distribution 1990-2024, by generation [Dataset]. https://www.statista.com/statistics/1376622/wealth-distribution-for-the-us-generation/
    Explore at:
    Dataset updated
    Aug 26, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In the first quarter of 2024, 51.8 percent of the total wealth in the United States was owned by members of the baby boomer generation. In comparison, millennials own around 9.4 percent of total wealth in the U.S. In terms of population distribution, there is almost an equal share of millennials and baby boomers in the United States.

  17. U.S. household income distribution 2023

    • statista.com
    • flwrdeptvarieties.store
    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/
    Explore at:
    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.

  18. Gini coefficient income distribution inequality in Latin America 2022, by...

    • statista.com
    Updated Dec 2, 2024
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    Gini coefficient income distribution inequality in Latin America 2022, by country [Dataset]. https://www.statista.com/statistics/980285/income-distribution-gini-coefficient-latin-america-caribbean-country/
    Explore at:
    Dataset updated
    Dec 2, 2024
    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, Brazil was the most unequal country in Latin America as of 2022. Brazil's Gini coefficient amounted to 52.9. Dominican Republic recorded the lowest Gini coefficient at 38.5, 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 38 and 54 points according to the latest available data from the reporting period 2010-2021. 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.

  19. U.S. wealth distribution Q3 2024, by generation

    • statista.com
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    Statista, U.S. wealth distribution Q3 2024, by generation [Dataset]. https://www.statista.com/statistics/1376620/wealth-distribution-for-the-us/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In the third quarter of 2024, 51.6 percent of the total wealth in the United States was owned by members of the baby boomer generation. In comparison, millennials owned around ten percent of total wealth in the U.S. In terms of population distribution, there is almost an equal share of millennials and baby boomers in the United States.

  20. U.S household income shares of quintiles 1970-2023

    • statista.com
    Updated Sep 17, 2024
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    Statista (2024). U.S household income shares of quintiles 1970-2023 [Dataset]. https://www.statista.com/statistics/203247/shares-of-household-income-of-quintiles-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

    About 50.4 percent of the household income of private households in the U.S. were earned by the highest quintile in 2023, which are the upper 20 percent of the workers. In contrast to that, in the same year, only 3.5 percent of the household income was earned by the lowest quintile. This relation between the quintiles is indicative of the level of income inequality in the United States. Income inequalityIncome inequality is a big topic for public discussion in the United States. About 65 percent of U.S. Americans think that the gap between the rich and the poor has gotten larger in the past ten years. This impression is backed up by U.S. census data showing that the Gini-coefficient for income distribution in the United States has been increasing constantly over the past decades for individuals and households. The Gini coefficient for individual earnings of full-time, year round workers has increased between 1990 and 2020 from 0.36 to 0.42, for example. This indicates an increase in concentration of income. In general, the Gini coefficient is calculated by looking at average income rates. A score of zero would reflect perfect income equality and a score of one indicates a society where one person would have all the money and all other people have nothing. Income distribution is also affected by region. The state of New York had the widest gap between rich and poor people in the United States, with a Gini coefficient of 0.51, as of 2019. In global comparison, South Africa led the ranking of the 20 countries with the biggest inequality in income distribution in 2018. South Africa had a score of 63 points, based on the Gini coefficient. On the other hand, the Gini coefficient stood at 16.6 in Azerbaijan, indicating that income is widely spread among the population and not concentrated on a few rich individuals or families. Slovenia led the ranking of the 20 countries with the greatest income distribution equality in 2018.

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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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19 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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