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.

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.

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.

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

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 (%)

"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.

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.

Replication data and code for Ellora Derenoncourt, Chi Hyun Kim, Moritz Kuhn, Moritz Schularick, Wealth of Two Nations: The U.S. Racial Wealth Gap, 1860–2020, The Quarterly Journal of Economics, 2023;, qjad044, https://doi.org/10.1093/qje/qjad044

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.

About this dataset

Context

The dataset presents the median household income across different racial categories in Austin. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Austin population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 59.90% of the total residents in Austin. Notably, the median household income for White households is $98,608. Interestingly, despite the White population being the most populous, it is worth noting that Asian households actually reports the highest median household income, with a median income of $119,954. This reveals that, while Whites may be the most numerous in Austin, Asian households experience greater economic prosperity in terms of median household income.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Austin.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

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

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.

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.

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.

About this dataset

Context

The dataset presents the median household income across different racial categories in Nebraska City. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Nebraska City population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 80.58% of the total residents in Nebraska City. Notably, the median household income for White households is $69,916. Interestingly, despite the White population being the most populous, it is worth noting that Some Other Race households actually reports the highest median household income, with a median income of $87,870. This reveals that, while Whites may be the most numerous in Nebraska City, Some Other Race households experience greater economic prosperity in terms of median household income.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Nebraska City.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

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 Nebraska City median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the median household income across different racial categories in Clara City. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Clara City population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 88.91% of the total residents in Clara City. Notably, the median household income for White households is $58,056. Interestingly, despite the White population being the most populous, it is worth noting that Some Other Race households actually reports the highest median household income, with a median income of $72,000. This reveals that, while Whites may be the most numerous in Clara City, Some Other Race households experience greater economic prosperity in terms of median household income.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Clara City.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

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 Clara City median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the median household income across different racial categories in Union Gap. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Union Gap population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 43.46% of the total residents in Union Gap. Notably, the median household income for White households is $50,054. Interestingly, despite the White population being the most populous, it is worth noting that Some Other Race households actually reports the highest median household income, with a median income of $79,510. This reveals that, while Whites may be the most numerous in Union Gap, Some Other Race households experience greater economic prosperity in terms of median household income.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Union Gap.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

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 Union Gap median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the median household income across different racial categories in Buffalo County. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Buffalo County population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 87.76% of the total residents in Buffalo County. Notably, the median household income for White households is $76,688. Interestingly, despite the White population being the most populous, it is worth noting that Some Other Race households actually reports the highest median household income, with a median income of $77,054. This reveals that, while Whites may be the most numerous in Buffalo County, Some Other Race households experience greater economic prosperity in terms of median household income.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Buffalo County.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

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

About this dataset

Context

The dataset presents the median household income across different racial categories in Pelham town. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Pelham town population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 70.57% of the total residents in Pelham town. Notably, the median household income for White households is $227,099. Interestingly, despite the White population being the most populous, it is worth noting that Some Other Race households actually reports the highest median household income, with a median income of $250,001. This reveals that, while Whites may be the most numerous in Pelham town, Some Other Race households experience greater economic prosperity in terms of median household income.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Pelham town.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

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

About this dataset

Context

The dataset presents the median household income across different racial categories in Blooming Grove town. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Blooming Grove town population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 70.15% of the total residents in Blooming Grove town. Notably, the median household income for White households is $96,287. Interestingly, despite the White population being the most populous, it is worth noting that Some Other Race households actually reports the highest median household income, with a median income of $124,917. This reveals that, while Whites may be the most numerous in Blooming Grove town, Some Other Race households experience greater economic prosperity in terms of median household income.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Blooming Grove town.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

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

About this dataset

Context

The dataset presents the median household income across different racial categories in Greene town. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Greene town population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 92.04% of the total residents in Greene town. Notably, the median household income for White households is $67,413. Interestingly, despite the White population being the most populous, it is worth noting that Some Other Race households actually reports the highest median household income, with a median income of $173,352. This reveals that, while Whites may be the most numerous in Greene town, Some Other Race households experience greater economic prosperity in terms of median household income.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Greene town.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

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