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.

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

The income distribution Gini-coefficient of individual earnings for full-time, year-round workers was 0.42 in 2023, indicating no change from the year prior. A Gini coefficient of zero expresses perfect equality, where all would have the same income, and a Gini coefficient of one expresses maximal inequality among values. In 2021, the Gini coefficient for individual income was 0.43.

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.

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.

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.

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

In 2023, the Gini index for Black households in the United States stood at 0.5, which was higher than the national index that year. The Census Bureau defines the Gini index as “a statistical measure of income inequality ranging from zero to one. A measure of one indicates perfect inequality, i.e., one household having all the income and the rest having none. A measure of zero indicates perfect equality, i.e., all households having an equal share of income.”

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.

In 2023, the Gini Index for all U.S. households was 0.49. The U.S. Census Bureau defines the Gini index as “a statistical measure of income inequality ranging from zero to one. A measure of one indicates perfect inequality, i.e., one household having all the income and the rest having none. A measure of zero indicates perfect equality, i.e., all households having an equal share of income.”

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

United States - Income Gini for Households by Race of Householder, White Alone Not Hispanic was 0.47300 Ratio in January of 2023, according to the United States Federal Reserve. Historically, United States - Income Gini for Households by Race of Householder, White Alone Not Hispanic reached a record high of 0.48400 in January of 2021 and a record low of 0.45200 in January of 2002. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Income Gini for Households by Race of Householder, White Alone Not Hispanic - last updated from the United States Federal Reserve on March of 2025.

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.

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).

Estimated Gini index by US census tract in 2018.

The table Gini Index by Census Tract is part of the dataset US Gini Coefficient Data, available at https://redivis.com/datasets/mvy6-47eywr6qf. It contains 74016 rows across 4 variables.

Graph and download economic data for Income Gini Ratio of Families by Race of Householder, White Alone Not Hispanic (GINIWANHF) from 2002 to 2023 about gini, white, hispanic, households, income, and USA.

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.

Graph and download economic data for Income Gini Ratio for Households by Race of Householder, Black Alone from 2002 to 2023 about gini, African-American, households, income, and USA.

The table Population by County is part of the dataset US Gini Coefficient Data, available at https://redivis.com/datasets/mvy6-47eywr6qf. It contains 838 rows across 3 variables.

Graph and download economic data for Income Gini Ratio of Families by Race of Householder, Asian Alone (GINIAAF) from 2002 to 2023 about gini, asian, households, income, and USA.