10 datasets found
  1. Intergenerational Economic Mobility and the Racial Wealth Gap

    • openicpsr.org
    Updated Jan 6, 2021
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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.

  2. 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
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    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.

  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. o

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

    • openicpsr.org
    • doi.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
    University of Bonn
    Princeton University
    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.

  5. F

    Income Gini Ratio for Households by Race of Householder, All Races

    • fred.stlouisfed.org
    json
    Updated Sep 10, 2024
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    (2024). Income Gini Ratio for Households by Race of Householder, All Races [Dataset]. https://fred.stlouisfed.org/series/GINIALLRH
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    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. d

    Neighborhood Financial Health Digital Mapping and Data Tool

    • catalog.data.gov
    • data.cityofnewyork.us
    Updated Sep 2, 2023
    + more versions
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    data.cityofnewyork.us (2023). Neighborhood Financial Health Digital Mapping and Data Tool [Dataset]. https://catalog.data.gov/dataset/neighborhood-financial-health-digital-mapping-and-data-tool
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    Dataset updated
    Sep 2, 2023
    Dataset provided by
    data.cityofnewyork.us
    Description

    "Neighborhood Financial Health (NFH) Digital Mapping and Data Tool provides neighborhood financial health indicator data for every neighborhood in New York City. DCWP's Office of Financial Empowerment (OFE) also developed NFH Indexes to present patterns in the data within and across neighborhoods. NFH Index scores describe relative differences between neighborhoods across the same indicators; they do not evaluate neighborhoods against fixed standards. OFE intends for the NFH Indexes to provide an easy reference tool for comparing neighborhoods, and to establish patterns in the relationship of NFH indicators to economic and demographic factors, such as race and income. Understanding these connections is potentially useful for uncovering systems that perpetuate the racial wealth gap, an issue with direct implications for OFE’s mission to expand asset building opportunities for New Yorkers with low and moderate incomes. This data tool was borne out of the Collaborative for Neighborhood Financial Health, a community-led initiative designed to better understand how neighborhoods influence the financial health of their residents.

  7. o

    Data and Code for: Racial Wealth Inequality and Access to Care with High...

    • openicpsr.org
    Updated May 13, 2024
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    Naomi Zewde (2024). Data and Code for: Racial Wealth Inequality and Access to Care with High Deductible Health Insurance [Dataset]. http://doi.org/10.3886/E202662V1
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    Dataset updated
    May 13, 2024
    Dataset provided by
    American Economic Association
    Authors
    Naomi Zewde
    License

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

    Time period covered
    2011 - 2017
    Area covered
    United States
    Description

    This paper evaluates racial inequalities in healthcare affordability between high-deductible and conventional insurance. Using the 2011-2017 National Health Interview Survey, the study finds that Blacks in high-deductible plans are not disproportionately higher-income nor more engaged in other savings vehicles, unlike their White counterparts, indicating they may be income constrained rather than desiring to partially self-insure. Furthermore, conditional on income, wealth explained more of the racial disparity in healthcare access among high-deductible enrollees than conventional enrollees, consistent with the hypothesis that benefit designs relying on households’ cash reserves would yield greater disparities due to the magnitude of racial inequalities in assets.

  8. a

    Goal 10: Reduce inequality within and among countries

    • senegal2-sdg.hub.arcgis.com
    • south-africa-sdg.hub.arcgis.com
    • +7more
    Updated Jul 1, 2022
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    arobby1971 (2022). Goal 10: Reduce inequality within and among countries [Dataset]. https://senegal2-sdg.hub.arcgis.com/datasets/cea6440cb3bd405d95d8d491270ca6df
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    Dataset updated
    Jul 1, 2022
    Dataset authored and provided by
    arobby1971
    Description

    Goal 10Reduce inequality within and among countriesTarget 10.1: By 2030, progressively achieve and sustain income growth of the bottom 40 per cent of the population at a rate higher than the national averageIndicator 10.1.1: Growth rates of household expenditure or income per capita among the bottom 40 per cent of the population and the total populationSI_HEI_TOTL: Growth rates of household expenditure or income per capita (%)Target 10.2: By 2030, empower and promote the social, economic and political inclusion of all, irrespective of age, sex, disability, race, ethnicity, origin, religion or economic or other statusIndicator 10.2.1: Proportion of people living below 50 per cent of median income, by sex, age and persons with disabilitiesSI_POV_50MI: Proportion of people living below 50 percent of median income (%)Target 10.3: Ensure equal opportunity and reduce inequalities of outcome, including by eliminating discriminatory laws, policies and practices and promoting appropriate legislation, policies and action in this regardIndicator 10.3.1: Proportion of population reporting having personally felt discriminated against or harassed in the previous 12 months on the basis of a ground of discrimination prohibited under international human rights lawVC_VOV_GDSD: Proportion of population reporting having felt discriminated against, by grounds of discrimination, sex and disability (%)Target 10.4: Adopt policies, especially fiscal, wage and social protection policies, and progressively achieve greater equalityIndicator 10.4.1: Labour share of GDPSL_EMP_GTOTL: Labour share of GDP (%)Indicator 10.4.2: Redistributive impact of fiscal policySI_DST_FISP: Redistributive impact of fiscal policy, Gini index (%)Target 10.5: Improve the regulation and monitoring of global financial markets and institutions and strengthen the implementation of such regulationsIndicator 10.5.1: Financial Soundness IndicatorsFI_FSI_FSANL: Non-performing loans to total gross loans (%)FI_FSI_FSERA: Return on assets (%)FI_FSI_FSKA: Regulatory capital to assets (%)FI_FSI_FSKNL: Non-performing loans net of provisions to capital (%)FI_FSI_FSKRTC: Regulatory Tier 1 capital to risk-weighted assets (%)FI_FSI_FSLS: Liquid assets to short term liabilities (%)FI_FSI_FSSNO: Net open position in foreign exchange to capital (%)Target 10.6: Ensure enhanced representation and voice for developing countries in decision-making in global international economic and financial institutions in order to deliver more effective, credible, accountable and legitimate institutionsIndicator 10.6.1: Proportion of members and voting rights of developing countries in international organizationsSG_INT_MBRDEV: Proportion of members of developing countries in international organizations, by organization (%)SG_INT_VRTDEV: Proportion of voting rights of developing countries in international organizations, by organization (%)Target 10.7: Facilitate orderly, safe, regular and responsible migration and mobility of people, including through the implementation of planned and well-managed migration policiesIndicator 10.7.1: Recruitment cost borne by employee as a proportion of monthly income earned in country of destinationIndicator 10.7.2: Number of countries with migration policies that facilitate orderly, safe, regular and responsible migration and mobility of peopleSG_CPA_MIGRP: Proportion of countries with migration policies to facilitate orderly, safe, regular and responsible migration and mobility of people, by policy domain (%)SG_CPA_MIGRS: Countries with migration policies to facilitate orderly, safe, regular and responsible migration and mobility of people, by policy domain (1 = Requires further progress; 2 = Partially meets; 3 = Meets; 4 = Fully meets)Indicator 10.7.3: Number of people who died or disappeared in the process of migration towards an international destinationiSM_DTH_MIGR: Total deaths and disappearances recorded during migration (number)Indicator 10.7.4: Proportion of the population who are refugees, by country of originSM_POP_REFG_OR: Number of refugees per 100,000 population, by country of origin (per 100,000 population)Target 10.a: Implement the principle of special and differential treatment for developing countries, in particular least developed countries, in accordance with World Trade Organization agreementsIndicator 10.a.1: Proportion of tariff lines applied to imports from least developed countries and developing countries with zero-tariffTM_TRF_ZERO: Proportion of tariff lines applied to imports with zero-tariff (%)Target 10.b: Encourage official development assistance and financial flows, including foreign direct investment, to States where the need is greatest, in particular least developed countries, African countries, small island developing States and landlocked developing countries, in accordance with their national plans and programmesIndicator 10.b.1: Total resource flows for development, by recipient and donor countries and type of flow (e.g. official development assistance, foreign direct investment and other flows)DC_TRF_TOTDL: Total assistance for development, by donor countries (millions of current United States dollars)DC_TRF_TOTL: Total assistance for development, by recipient countries (millions of current United States dollars)DC_TRF_TFDV: Total resource flows for development, by recipient and donor countries (millions of current United States dollars)Target 10.c: By 2030, reduce to less than 3 per cent the transaction costs of migrant remittances and eliminate remittance corridors with costs higher than 5 per centIndicator 10.c.1: Remittance costs as a proportion of the amount remittedSI_RMT_COST: Remittance costs as a proportion of the amount remitted (%)SI_RMT_COST_BC: Corridor remittance costs as a proportion of the amount remitted (%)SI_RMT_COST_SC: SmaRT corridor remittance costs as a proportion of the amount remitted (%)

  9. o

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

    • openicpsr.org
    Updated Apr 23, 2024
    + more versions
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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.

  10. U.S. poverty rate in the United States 2023, by race and ethnicity

    • statista.com
    Updated Jun 25, 2025
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    Statista (2025). U.S. poverty rate in the United States 2023, by race and ethnicity [Dataset]. https://www.statista.com/statistics/200476/us-poverty-rate-by-ethnic-group/
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    Dataset updated
    Jun 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, **** percent of Black people living in the United States were living below the poverty line, compared to *** percent of white people. That year, the total poverty rate in the U.S. across all races and ethnicities was **** percent. Poverty in the United States Single people in the United States making less than ****** U.S. dollars a year and families of four making less than ****** U.S. dollars a year are considered to be below the poverty line. Women and children are more likely to suffer from poverty, due to women staying home more often than men to take care of children, and women suffering from the gender wage gap. Not only are women and children more likely to be affected, racial minorities are as well due to the discrimination they face. Poverty data Despite being one of the wealthiest nations in the world, the United States had the third highest poverty rate out of all OECD countries in 2019. However, the United States' poverty rate has been fluctuating since 1990, but has been decreasing since 2014. The average median household income in the U.S. has remained somewhat consistent since 1990, but has recently increased since 2014 until a slight decrease in 2020, potentially due to the pandemic. The state that had the highest number of people living below the poverty line in 2020 was California.

  11. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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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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Intergenerational Economic Mobility and the Racial Wealth Gap

Explore at:
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.

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