60 datasets found
  1. 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.

  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. 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.

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

    • statista.com
    • flwrdeptvarieties.store
    Updated Nov 12, 2024
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    Statista (2024). 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
    Nov 12, 2024
    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 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.

  6. F

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

    • fred.stlouisfed.org
    json
    Updated Mar 21, 2025
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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
    Explore at:
    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 Bottom 50% (1st to 50th Wealth Percentiles) (WFRBSB50215) from Q3 1989 to Q4 2024 about net worth, wealth, percentile, Net, and USA.

  7. 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.

  8. 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/
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    Dataset updated
    Dec 2, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Latin America, LAC
    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.

  9. N

    Income Distribution by Quintile: Mean Household Income in Travelers Rest, SC...

    • neilsberg.com
    csv, json
    Updated Mar 3, 2025
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    Neilsberg Research (2025). Income Distribution by Quintile: Mean Household Income in Travelers Rest, SC // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/travelers-rest-sc-median-household-income/
    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
    Travelers Rest, South Carolina
    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 Travelers Rest, SC, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

    Key observations

    • Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 14,934, while the mean income for the highest quintile (20% of households with the highest income) is 184,772. This indicates that the top earners earn 12 times compared to the lowest earners.
    • *Top 5%: * The mean household income for the wealthiest population (top 5%) is 241,489, which is 130.70% higher compared to the highest quintile, and 1617.04% 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 Travelers Rest median household income. You can refer the same here

  10. U

    United States US: Gini Coefficient (GINI Index): World Bank Estimate

    • ceicdata.com
    Updated Oct 15, 2003
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    CEICdata.com (2003). United States US: Gini Coefficient (GINI Index): World Bank Estimate [Dataset]. https://www.ceicdata.com/en/united-states/poverty/us-gini-coefficient-gini-index-world-bank-estimate
    Explore at:
    Dataset updated
    Oct 15, 2003
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 1979 - Dec 1, 2016
    Area covered
    United States
    Description

    United States US: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 41.500 % in 2016. This records an increase from the previous number of 41.000 % for 2013. United States US: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 40.400 % from Dec 1979 (Median) to 2016, with 11 observations. The data reached an all-time high of 41.500 % in 2016 and a record low of 34.600 % in 1979. United States US: Gini Coefficient (GINI Index): World Bank Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Poverty. Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

  11. N

    Income Distribution by Quintile: Mean Household Income in Spokane County, WA...

    • neilsberg.com
    csv, json
    Updated Mar 3, 2025
    + more versions
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    Neilsberg Research (2025). Income Distribution by Quintile: Mean Household Income in Spokane County, WA // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/spokane-county-wa-median-household-income/
    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
    Spokane County, Washington
    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 Spokane County, WA, 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 17,330, while the mean income for the highest quintile (20% of households with the highest income) is 241,387. This indicates that the top earners earn 14 times compared to the lowest earners.
    • *Top 5%: * The mean household income for the wealthiest population (top 5%) is 417,472, which is 172.95% higher compared to the highest quintile, and 2408.96% 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 Spokane County median household income. You can refer the same here

  12. F

    Households; Net Worth, Level

    • fred.stlouisfed.org
    json
    Updated Mar 13, 2025
    + more versions
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    Households; Net Worth, Level [Dataset]. https://fred.stlouisfed.org/series/BOGZ1FL192090005Q
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Mar 13, 2025
    License

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

    Description

    Graph and download economic data for Households; Net Worth, Level (BOGZ1FL192090005Q) from Q4 1987 to Q4 2024 about net worth, Net, households, and USA.

  13. T

    United States Money Supply M2

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +17more
    csv, excel, json, xml
    Updated Mar 26, 2025
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    United States Money Supply M2 [Dataset]. https://tradingeconomics.com/united-states/money-supply-m2
    Explore at:
    json, xml, csv, excelAvailable download formats
    Dataset updated
    Mar 26, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 31, 1959 - Feb 28, 2025
    Area covered
    United States
    Description

    Money Supply M2 in the United States increased to 21447.60 USD Billion in November from 21311.20 USD Billion in October of 2024. This dataset provides - United States Money Supply M2 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  14. N

    Travelers Rest, SC households by income brackets: family, non-family, and...

    • neilsberg.com
    csv, json
    Updated Mar 3, 2025
    + more versions
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    Neilsberg Research (2025). Travelers Rest, SC households by income brackets: family, non-family, and total, in 2023 inflation-adjusted dollars [Dataset]. https://www.neilsberg.com/insights/travelers-rest-sc-median-household-income/
    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
    Travelers Rest, South Carolina
    Variables measured
    Income Level, All households, Family households, Non-Family households, Percent of All households, Percent of Family households, Percent of Non-Family households
    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 brackets (mentioned above) following an initial analysis and categorization. The percentage of all, family and nonfamily households were collected by grouping data as applicable. 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 a breakdown of households across various income brackets in Travelers Rest, SC, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Travelers Rest, SC reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Travelers Rest households based on income levels.

    Key observations

    • For Family Households: In Travelers Rest, the majority of family households, representing 12.71%, earn $150,000 to $199,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.0%, have incomes falling $50,000 to $59,999, representing a smaller but still significant segment of the community.
    • For Non-Family Households: In Travelers Rest, the majority of non-family households, accounting for 27.9%, have income $15,000 to $19,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.0%, earn $50,000 to $59,999, representing a smaller, yet notable, portion of non-family households in the community.
    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:

    • Less than $10,000
    • $10,000 to $14,999
    • $15,000 to $19,999
    • $20,000 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $59,999
    • $60,000 to $74,999
    • $75,000 to $99,999
    • $125,000 to $149,999
    • $150,000 to $199,999
    • $200,000 or more

    Variables / Data Columns

    • Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Travelers Rest, SC (As mentioned above).
    • All Households: Count of households for the specified income level
    • % All Households: Percentage of households at the specified income level relative to the total households in Travelers Rest, SC
    • Family Households: Count of family households for the specified income level
    • % Family Households: Percentage of family households at the specified income level relative to the total family households in Travelers Rest, SC
    • Non-Family Households: Count of non-family households for the specified income level
    • % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Travelers Rest, SC

    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 Travelers Rest median household income. You can refer the same here

  15. Gini coefficient income distribution inequality in Brazil 2010-2022

    • statista.com
    • flwrdeptvarieties.store
    Updated Jul 5, 2024
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    Statista (2024). Gini coefficient income distribution inequality in Brazil 2010-2022 [Dataset]. https://www.statista.com/statistics/981226/income-distribution-gini-coefficient-brazil/
    Explore at:
    Dataset updated
    Jul 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Brazil
    Description

    Between 2010 and 2022, Brazil's data on the degree of inequality in wealth distribution based on the Gini coefficient reached 52.9. That year, Brazil was deemed 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 three 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.

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

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

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

  17. F

    Median Personal Income in the United States

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

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

    Area covered
    United States
    Description

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

  18. U

    United States US: Broad Money: % of GDP

    • ceicdata.com
    Updated Nov 27, 2021
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    CEICdata.com (2021). United States US: Broad Money: % of GDP [Dataset]. https://www.ceicdata.com/en/united-states/money-supply/us-broad-money--of-gdp
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    Dataset updated
    Nov 27, 2021
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2005 - Dec 1, 2016
    Area covered
    United States
    Variables measured
    Monetary Aggregates/Money Supply/Money Stock
    Description

    United States US: Broad Money: % of GDP data was reported at 90.282 % in 2016. This records an increase from the previous number of 89.429 % for 2015. United States US: Broad Money: % of GDP data is updated yearly, averaging 70.078 % from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 91.060 % in 2009 and a record low of 59.483 % in 1994. United States US: Broad Money: % of GDP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Money Supply. Broad money (IFS line 35L..ZK) is the sum of currency outside banks; demand deposits other than those of the central government; the time, savings, and foreign currency deposits of resident sectors other than the central government; bank and traveler’s checks; and other securities such as certificates of deposit and commercial paper.; ; International Monetary Fund, International Financial Statistics and data files, and World Bank and OECD GDP estimates.; Weighted average; The derivation of this indicator was simplified in September 2012 to be current-year broad money divided by current-year GDP times 100.

  19. a

    Alaska Economic Key Performance Indicators Dashboard

    • egrants-hub-dcced.hub.arcgis.com
    Updated Apr 19, 2021
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    Dept. of Commerce, Community, & Economic Development (2021). Alaska Economic Key Performance Indicators Dashboard [Dataset]. https://egrants-hub-dcced.hub.arcgis.com/datasets/alaska-economic-key-performance-indicators-dashboard
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    Dataset updated
    Apr 19, 2021
    Dataset authored and provided by
    Dept. of Commerce, Community, & Economic Development
    Area covered
    Alaska
    Description

    This app contains the latest 14 months of unemployment statistics from the U.S. Bureau of Labor Statistics (BLS). The data is offered at the nationwide, state, and county geography levels. Puerto Rico is included. These are not seasonally adjusted values. The layer is updated monthly with the newest unemployment statistics available from BLS. There are attributes in the layer that specify which month is associated to each statistic. Most current month: March 2021 (preliminary values at the state and county level)The attributes included for each month are:Unemployment rate (%)Count of unemployed populationCount of employed population in the labor forceCount of people in the labor forceData obtained from the U.S. Bureau of Labor Statistics. Local Area Unemployment Statistics table download: https://www.bls.gov/lau/#tablesLocal Area Unemployment FTP downloads:State and CountyNationData Notes:This layer is updated automatically when the BLS releases their most current monthly statistics. The layer always contains the most recent estimates. It is updated within days of the BLS's county release schedule. BLS releases their county statistics roughly 2 months after-the-fact. The data is joined to 2019 TIGER boundaries from the U.S. Census Bureau.Monthly values are subject to revision over time.For national values, employed plus unemployed may not sum to total labor force due to rounding.To better understand the different labor force statistics included in this map, see the diagram below from BLS:Esri's U.S. Updated Demographic Data - Population, age, income, sex, race, home value, and marital status are among the variables included in the database. Each year, Esri's Data Development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of U.S. geographies.Data Note: The median household income value divides the distribution of household income into two equal parts. Pareto interpolation is used if the median falls in an income interval other than the first or last. For the lowest interval, <$10,000, linear interpolation is used. If the median falls in the upper income interval of $500,000+, it is represented by the value of $500,001. Additional Esri Resources:Esri DemographicsU.S. 2020/2025 Esri Updated DemographicsEssential demographic vocabularyPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

  20. T

    United States Corporate Profits

    • tradingeconomics.com
    • jp.tradingeconomics.com
    • +17more
    csv, excel, json, xml
    Updated Mar 27, 2025
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    TRADING ECONOMICS (2025). United States Corporate Profits [Dataset]. https://tradingeconomics.com/united-states/corporate-profits
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    excel, xml, json, csvAvailable download formats
    Dataset updated
    Mar 27, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Mar 31, 1947 - Sep 30, 2024
    Area covered
    United States
    Description

    Corporate Profits in the United States decreased to 3128.50 USD Billion in the third quarter of 2024 from 3141.56 USD Billion in the second quarter of 2024. This dataset provides the latest reported value for - United States Corporate Profits - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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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

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

WFRBSTP1300

Explore at:
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.

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