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.

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.

Graph and download economic data for Income Inequality in New York County, NY (2020RATIO036061) from 2010 to 2023 about New York County, NY; inequality; New York; NY; income; and USA.

In 2023, the Gini index for the income distribution of U.S. families stood at 0.45. 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.”

The USA: Gini income inequality index: The latest value from 2022 is 41.3 index points, an increase from 39.7 index points in 2021. In comparison, the world average is 38.33 index points, based on data from 28 countries. Historically, the average for the USA from 1963 to 2022 is 38.7 index points. The minimum value, 34.7 index points, was reached in 1980 while the maximum of 41.5 index points was recorded in 2014.

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.

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.

Income Inequality in Denver County, CO was 17.97779 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in Denver County, CO reached a record high of 20.23338 in January of 2010 and a record low of 17.13318 in January of 2021. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in Denver County, CO - last updated from the United States Federal Reserve on June of 2025.

Income Inequality in Broward County, FL was 17.32913 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in Broward County, FL reached a record high of 17.32913 in January of 2023 and a record low of 14.78784 in January of 2010. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in Broward County, FL - last updated from the United States Federal Reserve on May of 2025.

This file contains data needed to replicate all time series analyses from my book The Politics of Income Inequality in the United States.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in American Falls. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In American Falls, the median income for all workers aged 15 years and older, regardless of work hours, was $37,500 for males and $22,725 for females.

These income figures highlight a substantial gender-based income gap in American Falls. Women, regardless of work hours, earn 61 cents for each dollar earned by men. This significant gender pay gap, approximately 39%, underscores concerning gender-based income inequality in the city of American Falls.

- Full-time workers, aged 15 years and older: In American Falls, among full-time, year-round workers aged 15 years and older, males earned a median income of $49,073, while females earned $33,510, leading to a 32% gender pay gap among full-time workers. This illustrates that women earn 68 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in American Falls, showcasing a consistent income pattern irrespective of employment status.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for American Falls median household income by race. You can refer the same here

Graph and download economic data for Income Inequality in Orange County, FL (2020RATIO012095) from 2010 to 2023 about Orange County, FL; Orlando; inequality; FL; income; and USA.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Rye. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Rye, the median income for all workers aged 15 years and older, regardless of work hours, was $150,179 for males and $61,020 for females.

These income figures highlight a substantial gender-based income gap in Rye. Women, regardless of work hours, earn 41 cents for each dollar earned by men. This significant gender pay gap, approximately 59%, underscores concerning gender-based income inequality in the city of Rye.

- Full-time workers, aged 15 years and older: In Rye, among full-time, year-round workers aged 15 years and older, males earned a median income of $250,001, while females earned $127,824, leading to a 49% gender pay gap among full-time workers. This illustrates that women earn 51 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Rye, showcasing a consistent income pattern irrespective of employment status.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Rye median household income by race. You can refer the same here

Graph and download economic data for Income Inequality in Jackson County, MS (2020RATIO028059) from 2010 to 2023 about Jackson County, MS; Pascagoula; inequality; MS; income; and USA.

Income Inequality in Douglas County, NV was 14.94557 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in Douglas County, NV reached a record high of 14.94557 in January of 2023 and a record low of 11.58794 in January of 2018. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in Douglas County, NV - last updated from the United States Federal Reserve on May of 2025.

Income Inequality in Jefferson County, IA was 16.60413 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in Jefferson County, IA reached a record high of 20.01233 in January of 2022 and a record low of 14.39858 in January of 2016. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in Jefferson County, IA - last updated from the United States Federal Reserve on June of 2025.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Lostine. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Lostine, the median income for all workers aged 15 years and older, regardless of work hours, was $57,500 for males and $30,956 for females.

These income figures highlight a substantial gender-based income gap in Lostine. Women, regardless of work hours, earn 54 cents for each dollar earned by men. This significant gender pay gap, approximately 46%, underscores concerning gender-based income inequality in the city of Lostine.

- Full-time workers, aged 15 years and older: In Lostine, among full-time, year-round workers aged 15 years and older, males earned a median income of $57,222, while females earned $45,000, leading to a 21% gender pay gap among full-time workers. This illustrates that women earn 79 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in Lostine.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Lostine median household income by race. You can refer the same here

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).

Income Inequality in Clay County, NE was 12.30711 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in Clay County, NE reached a record high of 12.30711 in January of 2023 and a record low of 8.99209 in January of 2010. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in Clay County, NE - last updated from the United States Federal Reserve on June of 2025.

Income Inequality in Liberty County, MT was 18.75731 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in Liberty County, MT reached a record high of 27.52868 in January of 2022 and a record low of 15.16998 in January of 2011. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in Liberty County, MT - last updated from the United States Federal Reserve on May of 2025.