100+ datasets found
  1. o

    Wealth of two nations: The U.S. racial wealth gap, 1860-2020

    • doi.org
    • openicpsr.org
    Updated May 22, 2022
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    Ellora Derenoncourt; Chi Hyun Kim; Moritz Kuhn; Moritz Schularick (2022). Wealth of two nations: The U.S. racial wealth gap, 1860-2020 [Dataset]. http://doi.org/10.3886/E170941V2
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    Dataset updated
    May 22, 2022
    Dataset provided by
    University of Mannheim
    Kiel Institute for the World Economy, Sciences Po
    Princeton University
    University of Bonn
    Authors
    Ellora Derenoncourt; Chi Hyun Kim; Moritz Kuhn; Moritz Schularick
    Area covered
    United States
    Description

    PSID data extract for computing per capita white-to-Black wealth gaps and active saving rates of Black and white Americans during 1984-2019.

  2. o

    Data and Code for: Analytic Approaches to Measuring the Black-White Wealth...

    • openicpsr.org
    Updated Apr 23, 2024
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    Jermaine Toney; Fenaba R. Addo; Darrick Hamilton (2024). Data and Code for: Analytic Approaches to Measuring the Black-White Wealth Gap [Dataset]. http://doi.org/10.3886/E201263V2
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    Dataset updated
    Apr 23, 2024
    Dataset provided by
    American Economic Association
    Authors
    Jermaine Toney; Fenaba R. Addo; Darrick Hamilton
    License

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

    Description

    Does the measurement of the racial wealth gap shift depending on the model, method, and data set used? We contrast the traditional mean Oaxaca-Blinder decomposition with the distributional Recentered Influence Function (RIF) methods. The untransformed, logarithm-transformed, and inverse hyperbolic sine-transformed versions in both Survey of Consumer Finances and Panel Study of Income Dynamics data sets exhibit similarities. The Oaxaca-Blinder (mean) decomposition highlights that receiving an inheritance explains a larger portion of the racial wealth gap than educational attainment. Conversely, the RIF method at the median suggests that educational attainment accounts for more of the wealth gap than inheritance receipt.

  3. U.S. median household income 1967-2023, by race and ethnicity

    • statista.com
    • ai-chatbox.pro
    Updated Oct 28, 2024
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    Statista (2024). U.S. median household income 1967-2023, by race and ethnicity [Dataset]. https://www.statista.com/statistics/1086359/median-household-income-race-us/
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    Dataset updated
    Oct 28, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In the U.S., median household income rose from 51,570 U.S. dollars in 1967 to 80,610 dollars in 2023. In terms of broad ethnic groups, Black Americans have consistently had the lowest median income in the given years, while Asian Americans have the highest; median income in Asian American households has typically been around double that of Black Americans.

  4. N

    Income Distribution by Quintile: Mean Household Income in Black Earth, WI //...

    • neilsberg.com
    csv, json
    Updated Mar 3, 2025
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    Neilsberg Research (2025). Income Distribution by Quintile: Mean Household Income in Black Earth, WI // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/48162ba0-f81d-11ef-a994-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Mar 3, 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
    Black Earth, Wisconsin
    Variables measured
    Income Level, Mean Household Income
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It delineates income distributions across income quintiles (mentioned above) following an initial analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). 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 the mean household income for each of the five quintiles in Black Earth, WI, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

    Key observations

    • Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 16,027, while the mean income for the highest quintile (20% of households with the highest income) is 183,651. This indicates that the top earners earn 11 times compared to the lowest earners.
    • *Top 5%: * The mean household income for the wealthiest population (top 5%) is 250,158, which is 136.21% higher compared to the highest quintile, and 1560.85% higher compared to the lowest quintile.
    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Income Levels:

    • Lowest Quintile
    • Second Quintile
    • Third Quintile
    • Fourth Quintile
    • Highest Quintile
    • Top 5 Percent

    Variables / Data Columns

    • Income Level: This column showcases the income levels (As mentioned above).
    • Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

    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 Black Earth median household income. You can refer the same here

  5. o

    Data and code for: Root Causes of the Racial Wealth Gap: A Critique of the...

    • openicpsr.org
    Updated May 20, 2025
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    William A. Darity Jr.; Stephan Lefebvre (2025). Data and code for: Root Causes of the Racial Wealth Gap: A Critique of the Fed View [Dataset]. http://doi.org/10.3886/E230541V1
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    Dataset updated
    May 20, 2025
    Dataset provided by
    American Economic Association
    Authors
    William A. Darity Jr.; Stephan Lefebvre
    License

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

    Area covered
    United States
    Description

    In this paper, we address what has been termed “the Fed view,” the Federal Reserve’s model for black-white wealth inequality, articulated in a series of mutually consistent papers making two arguments. First, the Fed view has it that the black-white wealth gap, when measured with an “expanded wealth concept,” is smaller than previously thought. Second, the Fed view has it that the black-white wealth gap is primarily explained by income differences shaped by personal decisions around human capital acquisition, family structure, risk taking, and the legacy of residential segregation.

  6. U.S. quarterly wealth distribution 1989-2024, by income percentile

    • statista.com
    • ai-chatbox.pro
    Updated Jun 27, 2025
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    Statista (2025). U.S. quarterly wealth distribution 1989-2024, by income percentile [Dataset]. https://www.statista.com/statistics/299460/distribution-of-wealth-in-the-united-states/
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    Dataset updated
    Jun 27, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In the third quarter of 2024, the top ten percent of earners in the United States held over ** percent of total wealth. This is fairly consistent with the second quarter of 2024. Comparatively, the wealth of the bottom ** percent of earners has been slowly increasing since the start of the *****, though remains low. Wealth distribution in the United States by generation can be found here.

  7. o

    Data and Code for: The Racial Wealth Gap and the Role of Firm Ownership

    • openicpsr.org
    Updated Jan 6, 2022
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    Abraham Lipton (2022). Data and Code for: The Racial Wealth Gap and the Role of Firm Ownership [Dataset]. http://doi.org/10.3886/E158821V1
    Explore at:
    Dataset updated
    Jan 6, 2022
    Dataset provided by
    American Economic Association
    Authors
    Abraham Lipton
    License

    https://opensource.org/licenses/GPL-3.0https://opensource.org/licenses/GPL-3.0

    Time period covered
    1962 - 2019
    Area covered
    United States
    Description

    Data and code accompanying "The Racial Wealth Gap and the Role of Firm Ownership"This paper develops an overlapping generations model that isolates the impact of the U.S. racial wealth gap in 1962 on the long-run dynamics of wealth. The model predicts that one component of the initial gap, firm ownership, coupled with the intergenerational transfer of that ownership, results in a permanent wealth gap independent of other dimensions of inequality. This implies that even if all discrimination against black Americans had ceased upon the end of Jim Crow, the wealth gap would have persisted without a reparations policy addressing the fact that the initial firm ownership gap arose in the first place.

  8. a

    Where are income disparities for Black households within their county?

    • gis-for-racialequity.hub.arcgis.com
    Updated Jun 19, 2020
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    ArcGIS Living Atlas Team (2020). Where are income disparities for Black households within their county? [Dataset]. https://gis-for-racialequity.hub.arcgis.com/maps/2371072bacb44645add930e33a6eecb8
    Explore at:
    Dataset updated
    Jun 19, 2020
    Dataset authored and provided by
    ArcGIS Living Atlas Team
    Area covered
    Description

    Do Black households make as much as the "typical" household in their county? This map shows that this doesn't seem to be the case. This map compares the median household income of households with Black householders compared to the median household income of that county. If the Black households in a county make as much as a "typical" household in their county, the county is shown in turquoise. If Black households in a county make less than the median income of their county, it is shown in orange. The size of the symbol highlights where there are the highest counts of black population in the US.The data comes from County Health Rankings, a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute, measure the health of nearly all counties in the nation and rank them within states. The layer used in the map comes from ArcGIS Living Atlas of the World, and the full documentation for the layer can be found here.

  9. T

    Income Inequality in Black Hawk County, IA

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Feb 11, 2020
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    TRADING ECONOMICS (2020). Income Inequality in Black Hawk County, IA [Dataset]. https://tradingeconomics.com/united-states/income-inequality-in-black-hawk-county-ia-fed-data.html
    Explore at:
    csv, json, excel, xmlAvailable download formats
    Dataset updated
    Feb 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
    Black Hawk County, Iowa
    Description

    Income Inequality in Black Hawk County, IA was 13.88365 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in Black Hawk County, IA reached a record high of 14.60760 in January of 2019 and a record low of 11.92371 in January of 2012. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in Black Hawk County, IA - last updated from the United States Federal Reserve on July of 2025.

  10. N

    Black Wolf, Wisconsin annual median income by work experience and sex...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
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    Neilsberg Research (2025). Black Wolf, Wisconsin 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/insights/black-wolf-wi-income-by-gender/
    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
    Black Wolf, Wisconsin
    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 Black Wolf 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 Black Wolf town, the median income for all workers aged 15 years and older, regardless of work hours, was $57,981 for males and $36,176 for females.

    These income figures highlight a substantial gender-based income gap in Black Wolf town. Women, regardless of work hours, earn 62 cents for each dollar earned by men. This significant gender pay gap, approximately 38%, underscores concerning gender-based income inequality in the town of Black Wolf town.

    - Full-time workers, aged 15 years and older: In Black Wolf town, among full-time, year-round workers aged 15 years and older, males earned a median income of $71,875, while females earned $58,229, 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 Black Wolf 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 Black Wolf town median household income by race. You can refer the same here

  11. o

    Data and Code for: Student Debt Relief and Racial Wealth Gaps

    • openicpsr.org
    delimited
    Updated Apr 30, 2024
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    Gerald E. Daniels Jr.; Venoo Kakar; Jeffrey Galloway (2024). Data and Code for: Student Debt Relief and Racial Wealth Gaps [Dataset]. http://doi.org/10.3886/E201783V1
    Explore at:
    delimitedAvailable download formats
    Dataset updated
    Apr 30, 2024
    Dataset provided by
    American Economic Association
    Authors
    Gerald E. Daniels Jr.; Venoo Kakar; Jeffrey Galloway
    License

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

    Description

    The Biden-Harris Administration released a plan to cancel federal student loans for 43 million borrowers on August 24, 2022. While the Supreme Court struck down the Biden-Harris' student debt relief plan on June 30, 2023, the White House is now planning to use the Higher Education Act of 1965, a federal law that governs the student loan program, to bring about relief for student borrowers. This article estimates the potential impact of broad-based student debt relief on racial and ethnic wealth gaps. On average, federal student debt potentially eligible for relief explains 3% of the White-Black wealth gaps, suggesting that broad-based student debt relief could significantly mitigate racial wealth inequities.Note: This is data and code accompanying the article.

  12. Africa wealth distribution 2021, by region

    • statista.com
    Updated Jul 11, 2025
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    Statista (2025). Africa wealth distribution 2021, by region [Dataset]. https://www.statista.com/statistics/1411174/africa-wealth-distribution-region/
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    Dataset updated
    Jul 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Africa
    Description

    In 2021, Southern Africa's richest ** percent held around ** percent of the total wealth. Furthermore, the richest one percent in the region held over ** percent. The other African regions had a slightly smaller share of wealth with the wealthiest people. For instance, in West Africa, the richest ** percent held close to ** percent of the wealth, while the richest one percent held ** percent. On the other hand. The poorest ** percent in all the regions held lower than ***** percent of the wealth.

  13. Wage gap for African American women in the U.S. 2013, by state

    • statista.com
    Updated Apr 30, 2014
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    Statista (2014). Wage gap for African American women in the U.S. 2013, by state [Dataset]. https://www.statista.com/statistics/328259/wage-gap-for-african-american-women-in-the-us/
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    Dataset updated
    Apr 30, 2014
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2013
    Area covered
    United States
    Description

    The statistic above shows African American women's average earnings as a percentage of white, non-Hispanic men's average earnings in the United States in 2013, by state. In 2013 the gender wage gap of African American women in Louisiana was at ** percent, indicating that the average female African American full-time worker only received ** percent of the pay her male white, non-Hispanic counterpart would receive for doing the same work.

  14. Intergenerational Economic Mobility and the Racial Wealth Gap

    • openicpsr.org
    Updated Jan 6, 2021
    + more versions
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    Jermaine Toney; Cassandra Robertson (2021). Intergenerational Economic Mobility and the Racial Wealth Gap [Dataset]. http://doi.org/10.3886/E130341V1
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    Dataset updated
    Jan 6, 2021
    Dataset provided by
    American Economic Associationhttp://www.aeaweb.org/
    Authors
    Jermaine Toney; Cassandra Robertson
    License

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

    Description

    A growing body of research documents the importance of wealth and the racial wealth gap in perpetuating inequality across generations. We add to this literature by examining the impact of wealth on child income by race, while also extending our analysis to three generations. Our two stage least squares regressions reveal that grandparental and parental wealth and the younger generation’s household income is strongly positively correlated. We further explore the relationship between income and wealth by decomposing the child’s income by race. We find that the disparity in income between black and white respondents is mainly attributable to differences in family background. In context, differences in family background are stronger than differences in educational attainment. When we examine different income percentiles, however, we find that the effect of grandparental and parental wealth endowment is much stronger at the top of the income distribution. These findings indicate that wealth is an important source of income inequality.

  15. U.S. mean earnings by educational attainment and ethnicity/race 2023

    • statista.com
    • ai-chatbox.pro
    Updated Jun 24, 2025
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    Statista (2025). U.S. mean earnings by educational attainment and ethnicity/race 2023 [Dataset]. https://www.statista.com/statistics/184259/mean-earnings-by-educational-attainment-and-ethnic-group/
    Explore at:
    Dataset updated
    Jun 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, the mean income of Black Bachelor's degree holders was ****** U.S. dollars, compared to ****** U.S. dollars for White Americans with a Bachelor's degree.

  16. Breakdown of U.S. millionaires by race/ethnicity 2013

    • statista.com
    Updated Mar 31, 2013
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    Statista (2013). Breakdown of U.S. millionaires by race/ethnicity 2013 [Dataset]. https://www.statista.com/statistics/300528/us-millionaires-race-ethnicity/
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    Dataset updated
    Mar 31, 2013
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2013
    Area covered
    United States
    Description

    The statistic shows the distribution of U.S. millionaires in 2013, by race and ethnicity. As of 2013, about 76 percent of U.S. millionaires were White/Caucasian.

    Additional information on racial income inequality

    The issue of racial inequality in regards to income and wealth has been a problem through the entirety of the history of the United States. The statistic above demonstrates how the percentage of millionaires that identify as Black/African Americans is disproportionate to the share of the population overall. While the disproportionate number of millionaires demonstrates an undesirable degree of income inequality it is at the bottom of the wealth ladder within American society that the issue is most pressing. The overrepresentation of African Americans in contrast to the population in unemployment statistics are cause for concern on the part of the government and society as a whole. In 2014, nearly 25 percent of surveyed families who placed themselves in the income bracket of under ten thousand dollars identified as black.

    The percentage of non-white female business owners perhaps demonstrates that barriers to wealth exist but are diminished in unison. As barriers to wealth generation are removed for women, similar barriers are also being broken to allow for greater equality in the economic opportunities offered across the population of the United States. A central issue for policy makers is the time delay associated with policies aimed at reversing these inequalities. This was reflected in the 2015 Democratic and Republican presidential primary campaigns. Despite many major candidates discussing the issue none put forward meaningful proposals to address the problem. Even Senator Bernie Sanders who made addressing income inequality the cornerstone failed to separate the issue from income inequality generally. However, the global attention gained by movements such as ‘Black Lives Matter’ shows issues of racial inequality are prominent in the discourse of sections of the wider population if not forming a cornerstone of the political discourse in the United States.

  17. N

    Black Rock, AR 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). Black Rock, AR 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/insights/black-rock-ar-income-by-gender/
    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
    Black Rock, Arkansas
    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 Black Rock. 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 Black Rock, the median income for all workers aged 15 years and older, regardless of work hours, was $35,595 for males and $19,333 for females.

    These income figures highlight a substantial gender-based income gap in Black Rock. 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 Black Rock.

    - Full-time workers, aged 15 years and older: In Black Rock, among full-time, year-round workers aged 15 years and older, males earned a median income of $67,656, while females earned $29,375, leading to a 57% gender pay gap among full-time workers. This illustrates that women earn 43 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 Black Rock, 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 Black Rock median household income by race. You can refer the same here

  18. N

    Black Township, Pennsylvania annual median income by work experience and sex...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
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    Cite
    Neilsberg Research (2025). Black Township, Pennsylvania 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/a503db5a-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
    Black Township, Pennsylvania
    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 Black township. 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 Black township, the median income for all workers aged 15 years and older, regardless of work hours, was $38,281 for males and $25,500 for females.

    These income figures highlight a substantial gender-based income gap in Black township. Women, regardless of work hours, earn 67 cents for each dollar earned by men. This significant gender pay gap, approximately 33%, underscores concerning gender-based income inequality in the township of Black township.

    - Full-time workers, aged 15 years and older: In Black township, among full-time, year-round workers aged 15 years and older, males earned a median income of $57,188, while females earned $53,333, resulting in a 7% gender pay gap among full-time workers. This illustrates that women earn 93 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the township of Black township.

    Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Black township.

    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 Black township median household income by race. You can refer the same here

  19. N

    Black River Falls, WI annual median income by work experience and sex...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
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    Email
    Click to copy link
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    Close
    Cite
    Neilsberg Research (2025). Black River Falls, WI 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/insights/black-river-falls-wi-income-by-gender/
    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
    Black River Falls, Wisconsin
    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 Black River 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 Black River Falls, the median income for all workers aged 15 years and older, regardless of work hours, was $37,211 for males and $22,051 for females.

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

    - Full-time workers, aged 15 years and older: In Black River Falls, among full-time, year-round workers aged 15 years and older, males earned a median income of $67,941, while females earned $48,214, leading to a 29% gender pay gap among full-time workers. This illustrates that women earn 71 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 Black River Falls.

    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 Black River Falls median household income by race. You can refer the same here

  20. N

    Black Hawk County, IA annual median income by work experience and sex...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Neilsberg Research (2025). Black Hawk County, IA 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/a503d64c-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
    Black Hawk County
    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 Black Hawk County. 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 Black Hawk County, the median income for all workers aged 15 years and older, regardless of work hours, was $44,150 for males and $27,390 for females.

    These income figures highlight a substantial gender-based income gap in Black Hawk County. Women, regardless of work hours, earn 62 cents for each dollar earned by men. This significant gender pay gap, approximately 38%, underscores concerning gender-based income inequality in the county of Black Hawk County.

    - Full-time workers, aged 15 years and older: In Black Hawk County, among full-time, year-round workers aged 15 years and older, males earned a median income of $59,371, while females earned $48,891, leading to a 18% gender pay gap among full-time workers. This illustrates that women earn 82 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 Black Hawk County.

    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 Black Hawk County median household income by race. You can refer the same here

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Ellora Derenoncourt; Chi Hyun Kim; Moritz Kuhn; Moritz Schularick (2022). Wealth of two nations: The U.S. racial wealth gap, 1860-2020 [Dataset]. http://doi.org/10.3886/E170941V2

Wealth of two nations: The U.S. racial wealth gap, 1860-2020

Explore at:
Dataset updated
May 22, 2022
Dataset provided by
University of Mannheim
Kiel Institute for the World Economy, Sciences Po
Princeton University
University of Bonn
Authors
Ellora Derenoncourt; Chi Hyun Kim; Moritz Kuhn; Moritz Schularick
Area covered
United States
Description

PSID data extract for computing per capita white-to-Black wealth gaps and active saving rates of Black and white Americans during 1984-2019.

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