100+ datasets found
  1. Gini index: inequality of income distribution in China 2005-2023

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Gini index: inequality of income distribution in China 2005-2023 [Dataset]. https://www.statista.com/statistics/250400/inequality-of-income-distribution-in-china-based-on-the-gini-index/
    Explore at:
    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    This statistic shows the inequality of income distribution in China from 2005 to 2023 based on the Gini Index. In 2023, China reached a score of ************ 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 **** 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 **** 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.

  2. F

    Income Inequality in New York County, NY

    • fred.stlouisfed.org
    json
    Updated Dec 12, 2024
    + more versions
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    (2024). Income Inequality in New York County, NY [Dataset]. https://fred.stlouisfed.org/series/2020RATIO036061
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Dec 12, 2024
    License

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

    Area covered
    Manhattan, New York County, New York, New York
    Description

    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.

  3. Gini coefficient income distribution inequality in Latin America 2023, by...

    • statista.com
    • ai-chatbox.pro
    Updated May 6, 2025
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    Statista (2025). Gini coefficient income distribution inequality in Latin America 2023, by country [Dataset]. https://www.statista.com/statistics/980285/income-distribution-gini-coefficient-latin-america-caribbean-country/
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    Dataset updated
    May 6, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Latin America, LAC
    Description

    Based on the degree of inequality in income distribution measured by the Gini coefficient, 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.

  4. U

    USA Gini inequality index - data, chart | TheGlobalEconomy.com

    • theglobaleconomy.com
    csv, excel, xml
    Updated Aug 8, 2019
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    Globalen LLC (2019). USA Gini inequality index - data, chart | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/USA/gini_inequality_index/
    Explore at:
    csv, excel, xmlAvailable download formats
    Dataset updated
    Aug 8, 2019
    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, 2022
    Area covered
    United States
    Description

    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.

  5. 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
    Explore at:
    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.

  6. N

    United States annual median income by work experience and sex dataset: Aged...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). United States annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/a53c92b0-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    United States
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents 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 United States. 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 United States, the median income for all workers aged 15 years and older, regardless of work hours, was $48,138 for males and $32,546 for females.

    These income figures highlight a substantial gender-based income gap in United States. Women, regardless of work hours, earn 68 cents for each dollar earned by men. This significant gender pay gap, approximately 32%, underscores concerning gender-based income inequality in the country of United States.

    - Full-time workers, aged 15 years and older: In United States, among full-time, year-round workers aged 15 years and older, males earned a median income of $67,966, while females earned $54,999, leading to a 19% gender pay gap among full-time workers. This illustrates that women earn 81 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 United States.

    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 United States median household income by race. You can refer the same here

  7. T

    Income Inequality in Broward County, FL

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Aug 24, 2018
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    TRADING ECONOMICS (2018). Income Inequality in Broward County, FL [Dataset]. https://tradingeconomics.com/united-states/income-inequality-in-broward-county-fl-fed-data.html
    Explore at:
    csv, xml, excel, jsonAvailable download formats
    Dataset updated
    Aug 24, 2018
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Broward County, Florida
    Description

    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 June of 2025.

  8. 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).

  9. T

    Income Inequality in Denver County, CO

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Sep 1, 2018
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    TRADING ECONOMICS (2018). Income Inequality in Denver County, CO [Dataset]. https://tradingeconomics.com/united-states/income-inequality-in-denver-county-co-fed-data.html
    Explore at:
    csv, excel, xml, jsonAvailable download formats
    Dataset updated
    Sep 1, 2018
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Denver, Colorado
    Description

    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 July of 2025.

  10. N

    Forest View, IL annual median income by work experience and sex dataset:...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Forest View, IL annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/a5157bf7-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Forest View, Illinois
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents 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 Forest View. 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 Forest View, the median income for all workers aged 15 years and older, regardless of work hours, was $58,688 for males and $38,500 for females.

    These income figures highlight a substantial gender-based income gap in Forest View. Women, regardless of work hours, earn 66 cents for each dollar earned by men. This significant gender pay gap, approximately 34%, underscores concerning gender-based income inequality in the village of Forest View.

    - Full-time workers, aged 15 years and older: In Forest View, for all full-time workers aged 15 years and older, the median income was equal at, $59,957 for both males and females. This indicates a gender income balance in Forest View, where both men and women, in full-time year-round roles, earn an equal income.

    Curiously, across all roles (full-time and others), there was a notable income disparity between the median incomes for women and men. This hints at a considerable reduction in the income gap within full-time roles, potentially indicating progress towards income equality for women in these roles within Forest View.

    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 Forest View median household income by race. You can refer the same here

  11. T

    Income Inequality in Bronx County, NY

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jul 15, 2019
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    TRADING ECONOMICS (2019). Income Inequality in Bronx County, NY [Dataset]. https://tradingeconomics.com/united-states/income-inequality-in-bronx-county-ny-fed-data.html
    Explore at:
    excel, json, csv, xmlAvailable download formats
    Dataset updated
    Jul 15, 2019
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    New York, New York, The Bronx
    Description

    Income Inequality in Bronx County, NY was 25.92554 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in Bronx County, NY reached a record high of 25.92554 in January of 2023 and a record low of 17.84934 in January of 2010. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in Bronx County, NY - last updated from the United States Federal Reserve on July of 2025.

  12. Gini coefficient income distribution inequality in Brazil 2010-2023

    • statista.com
    • ai-chatbox.pro
    Updated May 6, 2025
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    Statista (2025). Gini coefficient income distribution inequality in Brazil 2010-2023 [Dataset]. https://www.statista.com/statistics/981226/income-distribution-gini-coefficient-brazil/
    Explore at:
    Dataset updated
    May 6, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Brazil
    Description

    Between 2010 and 2023, Brazil's data on the degree of inequality in wealth distribution based on the Gini coefficient reached 52. That year, Brazil was deemed one of the most unequal country in Latin America. Prior to 2010, wealth distribution in Brazil had shown signs of improvement, with the Gini coefficient decreasing in the previous 3 reporting periods. The Gini coefficient measures the deviation of the distribution of income (or consumption) among individuals or households in a given country from a perfectly equal distribution. A value of 0 represents absolute equality, whereas 100 would be the highest possible degree of inequality.

  13. T

    Income Inequality in Clackamas County, OR

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jul 12, 2019
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    TRADING ECONOMICS (2019). Income Inequality in Clackamas County, OR [Dataset]. https://tradingeconomics.com/united-states/income-inequality-in-clackamas-county-or-fed-data.html
    Explore at:
    excel, xml, json, csvAvailable download formats
    Dataset updated
    Jul 12, 2019
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Clackamas County
    Description

    Income Inequality in Clackamas County, OR was 13.11469 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in Clackamas County, OR reached a record high of 13.24556 in January of 2022 and a record low of 12.25643 in January of 2011. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in Clackamas County, OR - last updated from the United States Federal Reserve on June of 2025.

  14. N

    Scipio, New York annual median income by work experience and sex dataset:...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
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    Cite
    Neilsberg Research (2025). Scipio, New York annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/a535bdcb-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Scipio, New York
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents 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 Scipio town. 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 Scipio town, the median income for all workers aged 15 years and older, regardless of work hours, was $49,958 for males and $22,946 for females.

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

    - Full-time workers, aged 15 years and older: In Scipio town, for all full-time workers aged 15 years and older, the median income was equal at, $67,750 for both males and females. This indicates a gender income balance in Scipio town, where both men and women, in full-time year-round roles, earn an equal income.

    Curiously, across all roles (full-time and others), there was a notable income disparity between the median incomes for women and men. This hints at a considerable reduction in the income gap within full-time roles, potentially indicating progress towards income equality for women in these roles within Scipio town.

    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 Scipio town median household income by race. You can refer the same here

  15. T

    Income Inequality in Sawyer County, WI

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 12, 2020
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    TRADING ECONOMICS (2020). Income Inequality in Sawyer County, WI [Dataset]. https://tradingeconomics.com/united-states/income-inequality-in-sawyer-county-wi-fed-data.html
    Explore at:
    xml, csv, json, excelAvailable download formats
    Dataset updated
    Mar 12, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Sawyer County, Wisconsin
    Description

    Income Inequality in Sawyer County, WI was 15.05201 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in Sawyer County, WI reached a record high of 16.46913 in January of 2017 and a record low of 12.08829 in January of 2014. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in Sawyer County, WI - last updated from the United States Federal Reserve on June of 2025.

  16. T

    Income Inequality in Douglas County, NV

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 12, 2020
    + more versions
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    TRADING ECONOMICS (2020). Income Inequality in Douglas County, NV [Dataset]. https://tradingeconomics.com/united-states/income-inequality-in-douglas-county-nv-fed-data.html
    Explore at:
    xml, json, excel, csvAvailable download formats
    Dataset updated
    Mar 12, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Douglas County, Nevada
    Description

    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 June of 2025.

  17. T

    Income Inequality in Dade County, GA

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jul 13, 2019
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    TRADING ECONOMICS (2019). Income Inequality in Dade County, GA [Dataset]. https://tradingeconomics.com/united-states/income-inequality-in-dade-county-ga-fed-data.html
    Explore at:
    csv, json, xml, excelAvailable download formats
    Dataset updated
    Jul 13, 2019
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Dade County, Georgia
    Description

    Income Inequality in Dade County, GA was 10.76186 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in Dade County, GA reached a record high of 13.78123 in January of 2017 and a record low of 9.20450 in January of 2022. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in Dade County, GA - last updated from the United States Federal Reserve on July of 2025.

  18. T

    Income Inequality in Washtenaw County, MI

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 12, 2020
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    TRADING ECONOMICS (2020). Income Inequality in Washtenaw County, MI [Dataset]. https://tradingeconomics.com/united-states/income-inequality-in-washtenaw-county-mi-fed-data.html
    Explore at:
    excel, csv, json, xmlAvailable download formats
    Dataset updated
    Mar 12, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Michigan, Washtenaw County
    Description

    Income Inequality in Washtenaw County, MI was 18.38661 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in Washtenaw County, MI reached a record high of 19.08646 in January of 2022 and a record low of 16.19600 in January of 2010. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in Washtenaw County, MI - last updated from the United States Federal Reserve on July of 2025.

  19. T

    Income Inequality in Allegany County, MD

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 12, 2020
    + more versions
    Share
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    TRADING ECONOMICS (2020). Income Inequality in Allegany County, MD [Dataset]. https://tradingeconomics.com/united-states/income-inequality-in-allegany-county-md-fed-data.html
    Explore at:
    excel, xml, csv, jsonAvailable download formats
    Dataset updated
    Mar 12, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Allegany County, Maryland
    Description

    Income Inequality in Allegany County, MD was 14.60969 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in Allegany County, MD reached a record high of 15.25891 in January of 2022 and a record low of 12.88879 in January of 2011. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in Allegany County, MD - last updated from the United States Federal Reserve on June of 2025.

  20. T

    Income Inequality in White County, GA

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 11, 2020
    Share
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    TRADING ECONOMICS (2020). Income Inequality in White County, GA [Dataset]. https://tradingeconomics.com/united-states/income-inequality-in-white-county-ga-fed-data.html
    Explore at:
    json, excel, xml, csvAvailable download formats
    Dataset updated
    Mar 11, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    White County, Georgia
    Description

    Income Inequality in White County, GA was 12.84707 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in White County, GA reached a record high of 16.02604 in January of 2010 and a record low of 9.59673 in January of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in White County, GA - last updated from the United States Federal Reserve on June of 2025.

Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Statista (2025). Gini index: inequality of income distribution in China 2005-2023 [Dataset]. https://www.statista.com/statistics/250400/inequality-of-income-distribution-in-china-based-on-the-gini-index/
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Gini index: inequality of income distribution in China 2005-2023

Explore at:
39 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 23, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
China
Description

This statistic shows the inequality of income distribution in China from 2005 to 2023 based on the Gini Index. In 2023, China reached a score of ************ 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 **** 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 **** 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.

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