100+ datasets found
  1. Gini Index - countries with the biggest inequality in income distribution...

    • statista.com
    • flwrdeptvarieties.store
    Updated Mar 25, 2025
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    Statista, Gini Index - countries with the biggest inequality in income distribution 2023 [Dataset]. https://www.statista.com/statistics/264627/ranking-of-the-20-countries-with-the-biggest-inequality-in-income-distribution/
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    Dataset updated
    Mar 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    South Africa had the highest inequality in income distribution in 2023 with a Gini score of 63. Its South African neighbor Namibia followed in second. The Gini coefficient measures the deviation of the distribution of income (or consumption) among individuals or households within a country from a perfectly equal distribution. A value of 0 represents absolute equality, a value of 100 absolute inequality. All the 20 most unequal countries in the world were either located in Africa or Latin America & The Caribbean.

  2. 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
    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.

  3. Gini index worldwide 2024, by country

    • statista.com
    Updated Mar 10, 2025
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    Statista (2025). Gini index worldwide 2024, by country [Dataset]. https://www.statista.com/forecasts/1171540/gini-index-by-country
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    Dataset updated
    Mar 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 1, 2024 - Dec 31, 2024
    Area covered
    Albania
    Description

    Comparing the 130 selected regions regarding the gini index , South Africa is leading the ranking (0.63 points) and is followed by Namibia with 0.58 points. At the other end of the spectrum is Slovakia with 0.23 points, indicating a difference of 0.4 points to South Africa. The Gini coefficient here measures the degree of income inequality on a scale from 0 (=total equality of incomes) to one (=total inequality).The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

  4. Income Inequality in U.S. Counties

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

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

  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. F

    GINI Index for the United States

    • fred.stlouisfed.org
    json
    Updated Sep 19, 2024
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    (2024). GINI Index for the United States [Dataset]. https://fred.stlouisfed.org/series/SIPOVGINIUSA
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    jsonAvailable download formats
    Dataset updated
    Sep 19, 2024
    License

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

    Area covered
    United States
    Description

    Graph and download economic data for GINI Index for the United States (SIPOVGINIUSA) from 1963 to 2022 about gini, indexes, and USA.

  7. 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.

  8. 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.

  9. w

    Global Income Inequality 1988-2002 - Aruba, Afghanistan, Angola...and 190...

    • microdata.worldbank.org
    Updated Oct 26, 2023
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    Global Income Inequality 1988-2002 - Aruba, Afghanistan, Angola...and 190 more [Dataset]. https://microdata.worldbank.org/index.php/catalog/1784
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    Dataset updated
    Oct 26, 2023
    Dataset authored and provided by
    Branko L. Milanovic
    Time period covered
    1988 - 2002
    Area covered
    Angola
    Description

    Abstract

    Is global inequality (inequality among world citizens) stable, decreasing or increasing? How high it is? Is it mostly due to inequalities within nations or between nations? Is there a global middle class? See the working papers above: "True world income distribution 1988 and 1993: first calculations based on household surveys alone" no. 2244, and "Decomposing global income distribution: Does the world have a middle class?" no. 2562

    Household survey data (1988-2002) used in these papers, and subsequent book "Worlds Apart: Measuring International and Global Inequality", Princeton University Press, 2005. The data are for three benchmark years: 1988, 1993 and 1998

    Kind of data

    Aggregate data [agg]

    Mode of data collection

    Other [oth]

  10. Gini index in OECD countries based on disposable income 2022, by country

    • statista.com
    Updated Jul 4, 2024
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    Statista (2024). Gini index in OECD countries based on disposable income 2022, by country [Dataset]. https://www.statista.com/statistics/1461858/gini-index-oecd-countries/
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    Dataset updated
    Jul 4, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    OECD, Worldwide
    Description

    Of the countries included, South Africa had the highest income inequality, with a Gini coefficient of 0.62. It was also the country with the highest inequality level worldwide. Of the OECD members, Costa Rica had the highest income inequality, whereas Slovakia had the lowest.

  11. 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
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    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.

  12. L

    Latvia LV: Gini Coefficient (GINI Index): World Bank Estimate

    • ceicdata.com
    Updated Apr 15, 2018
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    CEICdata.com (2018). Latvia LV: Gini Coefficient (GINI Index): World Bank Estimate [Dataset]. https://www.ceicdata.com/en/latvia/poverty/lv-gini-coefficient-gini-index-world-bank-estimate
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    Dataset updated
    Apr 15, 2018
    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, 2004 - Dec 1, 2015
    Area covered
    Latvia
    Description

    Latvia LV: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 34.200 % in 2015. This records a decrease from the previous number of 35.100 % for 2014. Latvia LV: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 35.500 % from Dec 1993 (Median) to 2015, with 15 observations. The data reached an all-time high of 39.000 % in 2005 and a record low of 27.000 % in 1993. Latvia LV: 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 Latvia – Table LV.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.

  13. G

    Greece GR: Gini Coefficient (GINI Index): World Bank Estimate

    • ceicdata.com
    Updated Jan 15, 2018
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    CEICdata.com (2018). Greece GR: Gini Coefficient (GINI Index): World Bank Estimate [Dataset]. https://www.ceicdata.com/en/greece/poverty/gr-gini-coefficient-gini-index-world-bank-estimate
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    Dataset updated
    Jan 15, 2018
    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, 2004 - Dec 1, 2015
    Area covered
    Greece
    Description

    Greece GR: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 36.000 % in 2015. This records an increase from the previous number of 35.800 % for 2014. Greece GR: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 34.600 % from Dec 2003 (Median) to 2015, with 13 observations. The data reached an all-time high of 36.200 % in 2012 and a record low of 32.800 % in 2003. Greece GR: 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 Greece – Table GR.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.

  14. E

    Ecuador EC: Gini Coefficient (GINI Index): World Bank Estimate

    • ceicdata.com
    Updated Mar 22, 2018
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    CEICdata.com (2018). Ecuador EC: Gini Coefficient (GINI Index): World Bank Estimate [Dataset]. https://www.ceicdata.com/en/ecuador/poverty/ec-gini-coefficient-gini-index-world-bank-estimate
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    Dataset updated
    Mar 22, 2018
    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
    Ecuador
    Description

    Ecuador EC: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 45.000 % in 2016. This records a decrease from the previous number of 46.000 % for 2015. Ecuador EC: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 49.700 % from Dec 1987 (Median) to 2016, with 19 observations. The data reached an all-time high of 58.600 % in 1999 and a record low of 45.000 % in 2016. Ecuador EC: 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 Ecuador – Table EC.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.

  15. U

    Ukraine UA: Gini Coefficient (GINI Index): World Bank Estimate

    • ceicdata.com
    Updated Dec 15, 2018
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    CEICdata.com (2018). Ukraine UA: Gini Coefficient (GINI Index): World Bank Estimate [Dataset]. https://www.ceicdata.com/en/ukraine/poverty/ua-gini-coefficient-gini-index-world-bank-estimate
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    Dataset updated
    Dec 15, 2018
    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
    Ukraine
    Description

    Ukraine UA: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 25.000 % in 2016. This records a decrease from the previous number of 25.500 % for 2015. Ukraine UA: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 27.000 % from Dec 1992 (Median) to 2016, with 19 observations. The data reached an all-time high of 39.300 % in 1995 and a record low of 24.000 % in 2014. Ukraine UA: 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 Ukraine – Table UA.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.

  16. G

    Gini inequality index in South East Asia | TheGlobalEconomy.com

    • theglobaleconomy.com
    csv, excel, xml
    Updated Feb 8, 2021
    + more versions
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    Globalen LLC (2021). Gini inequality index in South East Asia | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/rankings/gini_inequality_index/South-East-Asia/
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    csv, xml, excelAvailable download formats
    Dataset updated
    Feb 8, 2021
    Dataset authored and provided by
    Globalen LLC
    License

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

    Time period covered
    Dec 31, 1963 - Dec 31, 2023
    Area covered
    Asia, South East Asia, World
    Description

    The average for 2021 based on 5 countries was 36.92 index points. The highest value was in Malaysia: 40.7 index points and the lowest value was in India: 32.8 index points. The indicator is available from 1963 to 2023. Below is a chart for all countries where data are available.

  17. F

    Income Gini Ratio for Households by Race of Householder, All Races

    • fred.stlouisfed.org
    json
    Updated Sep 10, 2024
    + more versions
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    (2024). Income Gini Ratio for Households by Race of Householder, All Races [Dataset]. https://fred.stlouisfed.org/series/GINIALLRH
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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

    Description

    Graph and download economic data for Income Gini Ratio for Households by Race of Householder, All Races (GINIALLRH) from 1967 to 2023 about gini, households, income, and USA.

  18. Gini Index - countries with the greatest income distribution equality 2022

    • statista.com
    Updated Jan 23, 2025
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    Statista (2025). Gini Index - countries with the greatest income distribution equality 2022 [Dataset]. https://www.statista.com/statistics/270220/ranking-of-the-20-countries-with-the-greatest-income-distribution-equality/
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    Dataset updated
    Jan 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    A high number of the countries with the highest income distribution levels are located in Eastern and Central Europe, with Slovakia topping the list. On the other end of the scale, South Africa was the country with the lowest income distribution.

  19. c

    Global income inequality measures and bibliography of household surveys,...

    • datacatalogue.cessda.eu
    Updated Mar 22, 2025
    + more versions
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    Gazeley, I; Newell, A; Reynolds, K (2025). Global income inequality measures and bibliography of household surveys, 1880-1960 [Dataset]. http://doi.org/10.5255/UKDA-SN-853185
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    Dataset updated
    Mar 22, 2025
    Dataset provided by
    Sussex University
    Brighton University
    Authors
    Gazeley, I; Newell, A; Reynolds, K
    Time period covered
    Jan 15, 2014 - Jan 14, 2018
    Area covered
    World Wide
    Variables measured
    Household, Geographic Unit
    Measurement technique
    This project utilised the published reports of household expenditure surveys. These published reports are held at copyright libraries or national statistical offices and were typically part of the output of government departments (for example, the UK Board of Trade). We compiled our bibliographies through library searches and requests to various national statistical offices. Many of these reports are published in English, but a substantial number are only published in the language of the relevant nation state. The published household expenditure survey reports typically include summary tables of grouped data of income, expenditures, and household structure. All of these reports, and the data therein, are already in the public domain, and our bibliography provides details of when and where they were published. From these data we estimated a suite of inequality measures, using three different techniques. The inequality measures are: Gini coefficient, 90/10 percentile ratio, 90/50 percentile ratio, and the 50/10 percentile ratio. These inequality measures were estimated three ways: linear interpolation, the Beta-Lorenz method and a log normal density estimation. Not all published household expenditure survey reports contain sufficient data to estimate inequality measures. Our selection was based simply on whether the reports published the appropriate data. All that we required to estimate inequality were total household income or expenditure grouped by class (and the group average incomes/expenditures) and the total number of households and average household size.
    Description

    Dataset consisting of inequality measures for 46 nation states and a global bibliography of all known household expenditure surveys covering the period roughly 1880-1960. Each entry notes when and where the survey was carried out and salient characteristics of the survey such as number of households, whether income and/or expenditure data are collected etc. These bibliographies are organised by six world regions and then by 118 nation states. For a sub-set of the most useful surveys we have estimated various inequality measures from the published data for 46 nation states, organised by world region.

    This project will calculate new estimates of world inequality in the period from the end of the nineteenth century until the 1960s, based on the results of household expenditure surveys. Our investigations have located a vast cache of household expenditure surveys for the period. Thus far, we have identified around 800 household surveys from around the world, carried out between the 1880s and 1960s, of which around half are of sufficient scope as to be potentially useful for the investigation of inequality. We will extract the reported demographic and expenditure data by income group from these reports and use them to estimate parameters of the income distribution. Using these estimates, we will investigate the changing nature of inequality within a number of key nation states, and also investigate the time path and geography of global inequality 1880-1960. In addition, we would use these data to estimate other indicators of living conditions, such as nutritional attainment, which may provide further insights into the impact of industrialisation on inequality.

  20. U

    Uganda UG: Gini Coefficient (GINI Index): World Bank Estimate

    • ceicdata.com
    Updated Dec 15, 2017
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    CEICdata.com (2017). Uganda UG: Gini Coefficient (GINI Index): World Bank Estimate [Dataset]. https://www.ceicdata.com/en/uganda/poverty/ug-gini-coefficient-gini-index-world-bank-estimate
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    Dataset updated
    Dec 15, 2017
    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, 1989 - Dec 1, 2012
    Area covered
    Uganda
    Description

    Uganda UG: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 42.800 % in 2016. This records an increase from the previous number of 41.000 % for 2012. Uganda UG: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 42.900 % from Dec 1989 (Median) to 2016, with 9 observations. The data reached an all-time high of 45.200 % in 2002 and a record low of 39.000 % in 1996. Uganda UG: 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 Uganda – Table UG.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.

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Statista, Gini Index - countries with the biggest inequality in income distribution 2023 [Dataset]. https://www.statista.com/statistics/264627/ranking-of-the-20-countries-with-the-biggest-inequality-in-income-distribution/
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Gini Index - countries with the biggest inequality in income distribution 2023

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18 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Mar 25, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Worldwide
Description

South Africa had the highest inequality in income distribution in 2023 with a Gini score of 63. Its South African neighbor Namibia followed in second. The Gini coefficient measures the deviation of the distribution of income (or consumption) among individuals or households within a country from a perfectly equal distribution. A value of 0 represents absolute equality, a value of 100 absolute inequality. All the 20 most unequal countries in the world were either located in Africa or Latin America & The Caribbean.

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