100+ datasets found
  1. U.S. Gini gap between rich and poor 2023, by state

    • statista.com
    • ai-chatbox.pro
    Updated Oct 25, 2024
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    Statista (2024). U.S. Gini gap between rich and poor 2023, by state [Dataset]. https://www.statista.com/statistics/227249/greatest-gap-between-rich-and-poor-by-us-state/
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    Dataset updated
    Oct 25, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    New York was the state with the greatest gap between rich and poor, with a Gini coefficient score of 0.52 in 2023. Although not a state, District of Columbia was among the highest Gini coefficients in the United States that year.

  2. Income Inequality in U.S. Counties

    • hub.arcgis.com
    Updated Sep 29, 2015
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    Urban Observatory by Esri (2015). Income Inequality in U.S. Counties [Dataset]. https://hub.arcgis.com/maps/b2db6f24618d4aad9885d2dd51024842
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    Dataset updated
    Sep 29, 2015
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    Description

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

  3. Mexico: Gini coefficient income distribution inequality 2022, by state

    • statista.com
    • ai-chatbox.pro
    Updated Jul 5, 2024
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    Statista (2024). Mexico: Gini coefficient income distribution inequality 2022, by state [Dataset]. https://www.statista.com/statistics/1040573/income-distribution-gini-coefficient-mexico-state/
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    Dataset updated
    Jul 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Mexico
    Description

    Chiapas, the state with the highest share of population living in poverty, had the highest wealth inequality in the country based on the Gini coefficient as well. This index measures the deviation of the income distribution situation in a given country from a perfectly equal distribution. A value of 0 represents an ideal situation of equality, whereas 1 would be the highest possible degree of inequality. As of 2022, Mexico City, the country's capital, had a Gini coefficient of 0.46, second highest recorded figure.

  4. Income Inequality

    • data.ca.gov
    • data.chhs.ca.gov
    • +2more
    pdf, xlsx, zip
    Updated Aug 28, 2024
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    California Department of Public Health (2024). Income Inequality [Dataset]. https://data.ca.gov/dataset/income-inequality
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    pdf, xlsx, zipAvailable download formats
    Dataset updated
    Aug 28, 2024
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    License

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

    Description

    This table contains data on income inequality. The primary measure is the Gini index – a measure of the extent to which the distribution of income among families/households within a community deviates from a perfectly equal distribution. The index ranges from 0.0, when all families (households) have equal shares of income (implies perfect equality), to 1.0 when one family (household) has all the income and the rest have none (implies perfect inequality). Index data is provided for California and its counties, regions, and large cities/towns. The data is from the U.S. Census Bureau, American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Income is linked to acquiring resources for healthy living. Both household income and the distribution of income across a society independently contribute to the overall health status of a community. On average Western industrialized nations with large disparities in income distribution tend to have poorer health status than similarly advanced nations with a more equitable distribution of income. Approximately 119,200 (5%) of the 2.4 million U.S. deaths in 2000 are attributable to income inequality. The pathways by which income inequality act to increase adverse health outcomes are not known with certainty, but policies that provide for a strong safety net of health and social services have been identified as potential buffers. More information about the data table and a data dictionary can be found in the About/Attachments section.

  5. U.S. wealth distribution Q2 2024

    • statista.com
    • alfareestrrf.ru
    • +1more
    Updated Oct 29, 2024
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    U.S. wealth distribution Q2 2024 [Dataset]. https://www.statista.com/statistics/203961/wealth-distribution-for-the-us/
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    Dataset updated
    Oct 29, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In the first quarter of 2024, almost two-thirds percent of the total wealth in the United States was owned by the top 10 percent of earners. In comparison, the lowest 50 percent of earners only owned 2.5 percent of the total wealth. Income inequality in the U.S. Despite the idea that the United States is a country where hard work and pulling yourself up by your bootstraps will inevitably lead to success, this is often not the case. In 2023, 7.4 percent of U.S. households had an annual income under 15,000 U.S. dollars. With such a small percentage of people in the United States owning such a vast majority of the country’s wealth, the gap between the rich and poor in America remains stark. The top one percent The United States follows closely behind China as the country with the most billionaires in the world. Elon Musk alone held around 219 billion U.S. dollars in 2022. Over the past 50 years, the CEO-to-worker compensation ratio has exploded, causing the gap between rich and poor to grow, with some economists theorizing that this gap is the largest it has been since right before the Great Depression.

  6. F

    GINI Index for the United States

    • fred.stlouisfed.org
    json
    Updated Jun 5, 2025
    + more versions
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    (2025). GINI Index for the United States [Dataset]. https://fred.stlouisfed.org/series/SIPOVGINIUSA
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    jsonAvailable download formats
    Dataset updated
    Jun 5, 2025
    License

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

    Area covered
    United States
    Description

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

  7. o

    Data from: GEOWEALTH-US: Spatial wealth inequality data for the United...

    • openicpsr.org
    delimited
    Updated Jun 23, 2023
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    Joel Suss; Dylan Connor; Tom Kemeny (2023). GEOWEALTH-US: Spatial wealth inequality data for the United States, 1960-2020 [Dataset]. http://doi.org/10.3886/E192306V4
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    delimitedAvailable download formats
    Dataset updated
    Jun 23, 2023
    Dataset provided by
    University of Toronto
    London School of Economics
    Arizona State University
    Authors
    Joel Suss; Dylan Connor; Tom Kemeny
    License

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

    Time period covered
    1960 - 2020
    Area covered
    United States
    Description

    Wealth inequality has been sharply rising in the United States and across many other high-income countries. Due to a lack of data, we know little about how this trend has unfolded across locations within countries. Investigating this subnational geography of wealth is crucial, as from one generation to the next, wealth powerfully shapes opportunity and disadvantage across individuals and communities. Using machine-learning-based imputation to link newly assembled national historical surveys conducted by the U.S. Federal Reserve to population survey microdata, the data presented in this paper addresses this gap. The Geographic Wealth Inequality Database ("GEOWEALTH-US") provides the first estimates of the level and distribution of wealth at various geographical scales within the United States from 1960 to 2020. The GEOWEALTH-US database enables new lines investigation into the contribution of inter-regional wealth patterns to major societal challenges including wealth concentration, spatial income inequality, equality of opportunity, housing unaffordability, and political polarization.

  8. 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
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    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
    New York, Manhattan, New York, New York County
    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.

  9. d

    Income Inequality and Redistributive Spending in the U.S. States

    • search.dataone.org
    Updated Nov 21, 2023
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    Moldogaziev, Tima T.; Monogan III, James E.; Witko, Christopher (2023). Income Inequality and Redistributive Spending in the U.S. States [Dataset]. http://doi.org/10.7910/DVN/PQUUEF
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    Dataset updated
    Nov 21, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Moldogaziev, Tima T.; Monogan III, James E.; Witko, Christopher
    Description

    Data on redistributive spending in the 50 American states from 1974-2012. Also includes two Gini coefficient measures, economic measures, and demographic measures.

  10. U.S. household income Gini Index 1990-2023

    • statista.com
    Updated Sep 16, 2024
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    Statista (2024). U.S. household income Gini Index 1990-2023 [Dataset]. https://www.statista.com/statistics/219643/gini-coefficient-for-us-individuals-families-and-households/
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    Dataset updated
    Sep 16, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    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.

  11. 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.

  12. d

    Replication Data for: Income inequality in authoritarian regimes: The role...

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 8, 2023
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    Panaro, Angelo Vito; Vaccaro, Andrea (2023). Replication Data for: Income inequality in authoritarian regimes: The role of political institutions and state capacity [Dataset]. http://doi.org/10.7910/DVN/XCKUIF
    Explore at:
    Dataset updated
    Nov 8, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Panaro, Angelo Vito; Vaccaro, Andrea
    Description

    In recent decades, there has been an institutional shift in the literature on authoritarian regimes, with scholars investigating the role of political institutions, such as elections and political parties, in shaping regime stability and economic performance. However, scant attention has been devoted to the effect of political institutions on policy outcomes, and more specifically, on income inequality. This paper adds to this debate and sheds light on the role of formal and informal institutions, on the one hand, and state capacity, on the other, in influencing levels of income inequality in autocracies. We argue that, while the presence of elections and multiparty competition creates more favourable conditions for the adoption of redistributive policies, state capacity increases the likelihood of successfully implemented policy decisions aimed at reducing the level of inequality. Our empirical analysis rests on a time-series cross-sectional dataset, which includes around 100 countries from 1972 to 2014. The findings indicate that both political institutions and a higher level of state capacity lead to lower levels of income inequality in authoritarian contexts.

  13. g

    Replication Data for: Understanding Public Perceptions of Growing Economic...

    • datasearch.gesis.org
    • dataverse-staging.rdmc.unc.edu
    Updated Jan 24, 2020
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    Franko, William (2020). Replication Data for: Understanding Public Perceptions of Growing Economic Inequality [Dataset]. http://doi.org/10.15139/S3/D9ZUIB
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    Dataset updated
    Jan 24, 2020
    Dataset provided by
    Odum Institute Dataverse Network
    Authors
    Franko, William
    Description

    While most Americans appear to acknowledge the large gap between the rich and the poor in the U.S., it is not clear if the public is aware of recent changes in income inequality. Even though economic inequality has grown substantially in recent decades, studies have shown that the public's perception of growing income disparities has remained mostly unchanged since the 1980s. This research offers an alternative approach to evaluating how public perceptions of inequality are developed. Centrally, it conceptualizes the public's response to growing economic disparities by applying theories of macro-political behavior and place-based contextual effects to the formation of aggregate perceptions about income inequality. It is argued that most of the public relies on basic information about the economy to form attitudes about inequality and that geographic context---in this case, the American states---plays a role in how views of income disparities are produced. A new measure of state perceptions of growing economic inequality over a 25-year period is used to examine whether the public is responsive to objective changes in economic inequality. Time-series cross-sectional analyses suggest that the public's perceptions of growing inequality are largely influenced by objective state economic indicators and state political ideology. This research has implications for how knowledgeable the public is of disparities between the rich and the poor, whether state context influences attitudes about inequality, and what role the public will have in determining how expanding income differences are addressed through government policy.

  14. T

    Income Inequality in Lorain County, OH

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jun 12, 2025
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    TRADING ECONOMICS (2025). Income Inequality in Lorain County, OH [Dataset]. https://tradingeconomics.com/united-states/income-inequality-in-lorain-county-oh-fed-data.html
    Explore at:
    json, csv, xml, excelAvailable download formats
    Dataset updated
    Jun 12, 2025
    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
    Ohio, Lorain County
    Description

    Income Inequality in Lorain County, OH was 15.72676 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in Lorain County, OH reached a record high of 15.72676 in January of 2023 and a record low of 12.08350 in January of 2010. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in Lorain County, OH - last updated from the United States Federal Reserve on June of 2025.

  15. F

    Share of Net Worth Held by the Top 0.1% (99.9th to 100th Wealth Percentiles)...

    • fred.stlouisfed.org
    json
    Updated Jun 20, 2025
    + more versions
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    (2025). Share of Net Worth Held by the Top 0.1% (99.9th to 100th Wealth Percentiles) [Dataset]. https://fred.stlouisfed.org/series/WFRBSTP1300
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 20, 2025
    License

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

    Description

    Graph and download economic data for Share of Net Worth Held by the Top 0.1% (99.9th to 100th Wealth Percentiles) (WFRBSTP1300) from Q3 1989 to Q1 2025 about shares, net worth, wealth, percentile, Net, and USA.

  16. T

    Income Inequality in Monterey County, CA

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jun 19, 2018
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    TRADING ECONOMICS (2018). Income Inequality in Monterey County, CA [Dataset]. https://tradingeconomics.com/united-states/income-inequality-in-monterey-county-ca-fed-data.html
    Explore at:
    excel, json, csv, xmlAvailable download formats
    Dataset updated
    Jun 19, 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
    California, Monterey County
    Description

    Income Inequality in Monterey County, CA was 13.93021 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in Monterey County, CA reached a record high of 13.93021 in January of 2023 and a record low of 12.47945 in January of 2012. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in Monterey County, CA - last updated from the United States Federal Reserve on July of 2025.

  17. N

    State Line City, IN annual median income by work experience and sex dataset:...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
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    Neilsberg Research (2025). State Line City, IN 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/a5392ad1-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
    State Line City
    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 State Line City. 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 State Line City, the median income for all workers aged 15 years and older, regardless of work hours, was $54,583 for males and $21,250 for females.

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

    - Full-time workers, aged 15 years and older: In State Line City, among full-time, year-round workers aged 15 years and older, males earned a median income of $61,250, while females earned $31,875, leading to a 48% gender pay gap among full-time workers. This illustrates that women earn 52 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 State Line City, 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 State Line City median household income by race. You can refer the same here

  18. g

    Replication Data for: Income Inequality and State Parties: Who Gets...

    • datasearch.gesis.org
    • dataverse-staging.rdmc.unc.edu
    Updated Feb 22, 2020
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    Wright, Gerald; Rigby, Elizabeth (2020). Replication Data for: Income Inequality and State Parties: Who Gets Represented? [Dataset]. http://doi.org/10.15139/S3/XJZONF
    Explore at:
    Dataset updated
    Feb 22, 2020
    Dataset provided by
    Odum Institute Dataverse Network
    Authors
    Wright, Gerald; Rigby, Elizabeth
    Description

    Recent studies of representation at the national and state levels have provided evidence that elected officials’ votes, political parties’ platforms, and enacted policy choices are more responsive to the preferences of the affluent, while those with average incomes and the poor have little or no impact in the political process. Yet, this research on the dominance of the affluent has overlooked key partisan differences in the electorate. In this era of hyper-partisanship, we argue that representation occurs through the party system, and we test whether taking this reality into account changes the story of policy dominance by the rich. We combine data on public preferences and state party positions to test for income bias in parties’ representation of their own co-partisans. The results show an interesting pattern in which under-representation of the poor is driven by Democratic parties pushing the more liberal social policy stances of rich Democrats and Republican parties reflecting the particularly conservative economic policy preferences of Rich Republicans. Thus, we have ample evidence that the wealthy, more often than not, do call the shots, but that the degree to which this disproportionate party responsiveness produces less representative policies depends on the party in power and the policy dimension being considered. We conclude by linking this pattern of influence and “coincidental representation” to familiar changes which define the transformation of the New Deal party system.[insert article abstract]

  19. w

    SIA47 - Income Inequality Rates by State, Year and Statistic

    • data.wu.ac.at
    json-stat, px
    Updated Mar 5, 2018
    + more versions
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    Central Statistics Office (2018). SIA47 - Income Inequality Rates by State, Year and Statistic [Dataset]. https://data.wu.ac.at/schema/data_gov_ie/ZDYwNDU1YWEtZWE1MC00MThkLWFjYTEtMGE2Mjg5ZmM1NzMw
    Explore at:
    px, json-statAvailable download formats
    Dataset updated
    Mar 5, 2018
    Dataset provided by
    Central Statistics Office
    License

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

    Description

    Income Inequality Rates by State, Year and Statistic

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  20. 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/
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    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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Statista (2024). U.S. Gini gap between rich and poor 2023, by state [Dataset]. https://www.statista.com/statistics/227249/greatest-gap-between-rich-and-poor-by-us-state/
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U.S. Gini gap between rich and poor 2023, by state

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12 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Oct 25, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2023
Area covered
United States
Description

New York was the state with the greatest gap between rich and poor, with a Gini coefficient score of 0.52 in 2023. Although not a state, District of Columbia was among the highest Gini coefficients in the United States that year.

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