Comparing the *** selected regions regarding the gini index , South Africa is leading the ranking (**** points) and is followed by Namibia with **** points. At the other end of the spectrum is Slovakia with **** points, indicating a difference of *** points to South Africa. The Gini coefficient here measures the degree of income inequality on a scale from * (=total equality of incomes) to *** (=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 *** 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).

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.

The Gini index measures economic inequality in a country. Specifically, it is the extent to which the distribution of income (or, in some cases, consumption expenditure) deviates from a perfectly equal distribution among individuals or households within an economy.

In 20234 Bulgaria had the highest Gini Index score in the European Union at 38.4, implying that the country had the highest level of inequality among European countries. The Gini Index is a measure of inequality within economies, a lower score indicates more equality, and a higher score less equality. Slovakia had the lowest score among EU countries for 2024 with a score of 21.7, suggesting that it is the most egalitarian society in Europe.

The Gini index quantifies the degree of inequality in the distribution of income (or sometimes consumption) among individuals or households within an economy. It compares the actual income distribution to a perfectly equal one. This is visualized through the Lorenz curve, which charts the cumulative share of total income against the cumulative share of recipients, starting from the poorest. The Gini index is derived from the area between the Lorenz curve and the line representing absolute equality, measured as a percentage of the total area beneath that line. A Gini index of 0 indicates perfect equality, while 100 signifies complete inequality.

Tunisia TN: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 35.800 % in 2010. This records a decrease from the previous number of 37.700 % for 2005. Tunisia TN: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 40.500 % from Dec 1985 (Median) to 2010, with 6 observations. The data reached an all-time high of 43.400 % in 1985 and a record low of 35.800 % in 2010. Tunisia TN: 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 Tunisia – Table TN.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.

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

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.

The average for 2021 based on 31 countries was 31.37 index points. The highest value was in Turkey: 44.4 index points and the lowest value was in Slovakia: 24.1 index points. The indicator is available from 1963 to 2023. Below is a chart for all countries where data are available.

Austria AT: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 30.700 % in 2021. This records an increase from the previous number of 29.800 % for 2020. Austria AT: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 30.350 % from Dec 1994 (Median) to 2021, with 26 observations. The data reached an all-time high of 31.500 % in 2009 and a record low of 28.700 % in 2005. Austria AT: 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 Austria – Table AT.World Bank.WDI: Social: Poverty and Inequality. 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, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Brazil BR: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 52.000 % in 2022. This records a decrease from the previous number of 52.900 % for 2021. Brazil BR: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 56.400 % from Dec 1981 (Median) to 2022, with 38 observations. The data reached an all-time high of 63.300 % in 1989 and a record low of 48.900 % in 2020. Brazil BR: 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 Brazil – Table BR.World Bank.WDI: Social: Poverty and Inequality. 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, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

GINI Index Data consists of information based on primary household survey data obtained from government statistical agencies and World Bank country departments. In economics, the GINI index (sometimes expressed as a GINI ratio, GINI coefficient or a normalized GINI index) is a measure of statistical dispersion intended to represent the income or wealth distribution of a nation's residents, and is the most commonly used measure of inequality.

Abstract

This dataset contains tables that match an estimated Gini coefficient to a specific geographic region (either census tract, county, or state) from 2010 to 2018. The 1-year estimates are produced by the American Community Survey (ACS).

Documentation

*The passage below comes from the US Census website:*

GINI INDEX OF INCOME INEQUALITYSurvey/Program: American Community SurveyUniverse: HouseholdsYear: 2018Estimates: 1-YearTable ID: B19083

Source: U.S. Census Bureau, 2018 American Community Survey 1-Year Estimates Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties. Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation ). The effect of nonsampling error is not represented in these tables. While the 2018 American Community Survey (ACS) data generally reflect the July 2015 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas, in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities. Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization. Explanation of Symbols: Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section. Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section.

Out of the G20 countries, South Africa, Brazil, and Turkey have the highest levels of income inequality, while France, Canada, and Germany have the lowest levels of inequality. Other G20 countries in the middle have Gini coefficients between 32.5 and 44.0. The Gini coefficient measures the level of income inequality worldwide, where a higher score indicates a higher level of income inequality.

Iran IR: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 38.800 % in 2014. This records an increase from the previous number of 37.400 % for 2013. Iran IR: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 43.600 % from Dec 1986 (Median) to 2014, with 9 observations. The data reached an all-time high of 47.400 % in 1986 and a record low of 37.400 % in 2013. Iran IR: 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 Iran – Table IR.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.

This dataset provides values for GINI COEFFICIENT NO ZERO INCOME WB DATA.HTML. reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Graph and download economic data for GINI Index for the United States (SIPOVGINIUSA) from 1963 to 2023 about gini, indexes, and USA.

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.

The average for 2021 based on 8 countries was 45.11 index points. The highest value was in Colombia: 55.1 index points and the lowest value was in Peru: 40.1 index points. The indicator is available from 1963 to 2023. Below is a chart for all countries where data are available.

Estimated Gini index by US county in 2018.

The table Gini Index by County is part of the dataset US Gini Coefficient Data, available at https://redivis.com/datasets/mvy6-47eywr6qf. It contains 839 rows across 4 variables.