Graph and download economic data for Homeownership Rates by Race and Ethnicity: Black Alone in the United States (BOAAAHORUSQ156N) from Q1 1994 to Q2 2025 about African-American, homeownership, rate, and USA.

In 2023, the rate of homeownership among White people living in the United States was 74.3 percent. Comparatively, 45.7 percent of Black people owned a home in the same year.

In 2018, ** percent of African Americans living in Mississippi owned their home, which was the state with the highest Black homeownership rate. Mississippi also had the highest White homeownership rate, but it was considerably higher at ** percent. The homeownership rate among African Americans in Montana and North Dakota was only ***** percent.

Graph and download economic data for Homeownership Rates by Race and Ethnicity: Non-Hispanic White Alone in the United States (NHWAHORUSQ156N) from Q1 1994 to Q2 2025 about white, homeownership, non-hispanic, rate, and USA.

View quarterly updates and historical trends for US Black Home Ownership Rate. from United States. Source: Census Bureau. Track economic data with YCharts…

ACS 1-year estimates are based on data collected over one calendar year, offering more current information but with a higher margin of error. ACS 5-year estimates combine five years of data, providing more reliable information but less current. Both are based on probability samples. Some racial and ethnic categories are suppressed to avoid misleading estimates when the relative standard error exceeds 30%.

Data Source: American Community Survey (ACS) 1- & 5-Year Estimates

Why This Matters

Homeownership has historically been an important source of intergenerational wealth. For many, homeownership can provide financial and housing security.Rising home prices over the past two decades have outpaced wage growth, perpetuating significant racial disparities in homeownership rates and contributing to the displacement of Black residents and other people of color from the District.

A history of redlining and racist real estate practices, like racial covenants, barred Black and other people of color from homeownership.

The District's Response

Convening of the Black Homeownership Strikeforce to address past harms and increase equitable homeownership rates through targeted, evidence-based recommendations, and setting the goal of creating 20,000 new Black homeowners by 2030.

Programs to enable homeowning families and individuals to remain in their homes, including the Homestead Deduction and Senior Citizen or Disabled Property Owner Tax Relief and the Heir Property Assistance Program.

Inclusionary Zoning (IZ) Affordable Housing Program and financial assistance programs like the Home Purchase Assistance Program (HPAP), Employer Assisted Housing Program (EAHP), and Negotiated Employee Assistance Home Purchase Program (NEAHP) to support homeownership among District residents.

Home ownership persists as the primary way that families build wealth. Housing researchers and advocates often discuss the racial home ownership gap, particularly for Black and Hispanic households (Urban Institute, Pew Hispanic Center). Historical policies such as redlining, steering, and municipal underbounding have effects that stay with us today.This map shows the overall home ownership rate and the home ownership rate by race/ethnicity of householder in a chart in the pop-up. Map is multi-scale showing data for state, county, and tract.This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.

Graph and download economic data for Homeownership Rate (5-year estimate) for Black Hawk County, IA (HOWNRATEACS019013) from 2009 to 2023 about Black Hawk County, IA; Waterloo; homeownership; IA; 5-year; housing; rate; and USA.

The homeownership among White people in the United States was **** percent, the highest out of all ethnicities, in 2023. American Dream Part of the “American Dream” is the idea of owning a home. It is seen as a status symbol and an indicator of wealth. People take a lot of pride in owning a home, and hope to do so at the earliest age possible. It is the idea of having a white picket fence with a nuclear family, a dog, and a car or two which is seen as the stereotypical “end goal”. However, in the aftermath of the 2008 recession, the rate of homeownership in the United States fell steadily until 2016. The recession hindered people’s chances of owning a home, due to less credit being available and their own fears about being stuck with a home in negative equity if another recession were to occur. As a result, the homeownership rate in the United States has barely increased in the past few years. Factors affecting homeownership Homeownership varies based on different factors. Married-couple families have the highest homeownership rates among different family statuses. Unsurprisingly, households with high incomes have the highest homeownership rates.

Home ownership persists as the primary way that families build wealth. Housing researchers and advocates often discuss the racial home ownership gap, particularly for Black and Hispanic households (Urban Institute, Pew Hispanic Center). Historical policies such as redlining, steering, and municipal underbounding have effects that stay with us today.This map shows the overall home ownership rate and the home ownership rate by race/ethnicity of householder in a chart in the pop-up. Map is multi-scale showing data for state, county, and tract.This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.

This map compares homeownership rates between households with a non-Hispanic White householder and households with a Black or African American householder. This map shows us where there is a disparity in home ownership based on race/ethnicity. The pattern is shown at the state, county, and tract levels. Zoom or pan around the map to explore the map. You can also search for your city and explore the pattern in your local area. If you zoom out, you can see the nationwide pattern. The data comes from the most current release of American Community Survey (ACS) estimates from the U.S. Census Bureau. The layer being used in this map can be found here, and also within ArcGIS Living Atlas of the World. Click here to find more ACS layers within Living Atlas. Note: areas where there are no Black or White householders, no symbol is shown. This map compares areas where there are both White and Black householders.

Graph and download economic data for Consumer Unit Characteristics: Percent Black or African American by Housing Tenure: Homeowner without Mortgage (CXU980270LB1704M) from 2003 to 2023 about consumer unit, African-American, homeownership, mortgage, percent, housing, and USA.

In a September 2020 survey among adults in the United States, around ** percent of Hispanic respondents said that they were currently saving up to buy a house, while just ** percent of white respondents said that they were doing so. Similarly, just ** percent of Hispanics said that they never plan or expect to own a home, while ** percent of White respondents said so.In the United States, the 2020 homeownership rate reached **** percent.

Home ownership persists as the primary way that families build wealth. Housing researchers and advocates often discuss the racial home ownership gap, particularly for Black and Hispanic households (Urban Institute, Pew Hispanic Center). The Urban Institute projects that most new homeowners in the next two decades will be Hispanic, but yet the housing industry is ill-equipped for this shift. This map opens in Yuma, AZ and has nationwide coverage for states, counties, and tracts.This map uses the Compare A to B mapping style since we are comparing homeownership rates between two groups. Areas in red have higher homeownership rates among non-Hispanic White households, whereas purple areas have higher homeownership rates among Hispanic and Latino households.The pop-up contains information about whether the difference is statistically significant, which has been calculated through an Arcade expression based on this statistical testing tool from the US Census Bureau. When a difference is significant, it means we are 90% confident that the difference is real, and not just due to getting a lucky (or unlucky) sample.This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.

Comprehensive demographic dataset for Black, MO, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

Graph and download economic data for Consumer Unit Characteristics: Percent White, Asian, and All Other Races, Not Including African American by Housing Tenure: Homeowner without Mortgage (CXUWHTNDOTHLB1704M) from 2003 to 2023 about asian, consumer unit, white, homeownership, mortgage, percent, housing, and USA.

Graph and download economic data for Consumer Unit Characteristics: Percent White, Asian, and All Other Races, Not Including African American by Housing Tenure: Home Owner (CXUWHTNDOTHLB1702M) from 1984 to 2023 about asian, consumer unit, white, homeownership, percent, housing, and USA.

Key Table Information.Table Title.Total Population in Occupied Housing Units by Tenure (Black or African American Alone Householder).Table ID.ACSDT1Y2024.B25008B.Survey/Program.American Community Survey.Year.2024.Dataset.ACS 1-Year Estimates Detailed Tables.Source.U.S. Census Bureau, 2024 American Community Survey, 1-Year Estimates.Dataset Universe.The dataset universe of the American Community Survey (ACS) is the U.S. resident population and housing. For more information about ACS residence rules, see the ACS Design and Methodology Report. Note that each table describes the specific universe of interest for that set of estimates..Methodology.Unit(s) of Observation.American Community Survey (ACS) data are collected from individuals living in housing units and group quarters, and about housing units whether occupied or vacant. For more information about ACS sampling and data collection, see the ACS Design and Methodology Report..Geography Coverage.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year.Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Sampling.The ACS consists of two separate samples: housing unit addresses and group quarters facilities. Independent housing unit address samples are selected for each county or county-equivalent in the U.S. and Puerto Rico, with sampling rates depending on a measure of size for the area. For more information on sampling in the ACS, see the Accuracy of the Data document..Confidentiality.The Census Bureau has modified or suppressed some estimates in ACS data products to protect respondents' confidentiality. Title 13 United States Code, Section 9, prohibits the Census Bureau from publishing results in which an individual's data can be identified. For more information on confidentiality protection in the ACS, see the Accuracy of the Data document..Technical Documentation/Methodology.Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables.Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Weights.ACS estimates are obtained from a raking ratio estimation procedure that results in the assignment of two sets of weights: a weight to each sample person record and a weight to each sample housing unit record. Estimates of person characteristics are based on the person weight. Estimates of family, household, and housing unit characteristics are based on the housing unit weight. For any given geographic area, a characteristic total is estimated by summing the weights assigned to the persons, households, families or housing units possessing the characteristic in the geographic area. For more information on weighting and estimation in the ACS, see the Accuracy of the Data document.Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the populatio...

The majority of public housing households in the U.S. were of a racial minority in 2023. In about ** percent of the households, the head of the family belonged to a racial minority. That percentage was the lowest in Vermont, at ***** percent, and the highest in Puerto Rico, where a hundred percent of the households were considered a racial minority by the source.

Key Table Information.Table Title.Housing Costs as a Percentage of Household Income in the Past 12 Months (Black Alone Householder).Table ID.ACSDT1Y2024.B25140B.Survey/Program.American Community Survey.Year.2024.Dataset.ACS 1-Year Estimates Detailed Tables.Source.U.S. Census Bureau, 2024 American Community Survey, 1-Year Estimates.Dataset Universe.The dataset universe of the American Community Survey (ACS) is the U.S. resident population and housing. For more information about ACS residence rules, see the ACS Design and Methodology Report. Note that each table describes the specific universe of interest for that set of estimates..Methodology.Unit(s) of Observation.American Community Survey (ACS) data are collected from individuals living in housing units and group quarters, and about housing units whether occupied or vacant. For more information about ACS sampling and data collection, see the ACS Design and Methodology Report..Geography Coverage.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year.Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Sampling.The ACS consists of two separate samples: housing unit addresses and group quarters facilities. Independent housing unit address samples are selected for each county or county-equivalent in the U.S. and Puerto Rico, with sampling rates depending on a measure of size for the area. For more information on sampling in the ACS, see the Accuracy of the Data document..Confidentiality.The Census Bureau has modified or suppressed some estimates in ACS data products to protect respondents' confidentiality. Title 13 United States Code, Section 9, prohibits the Census Bureau from publishing results in which an individual's data can be identified. For more information on confidentiality protection in the ACS, see the Accuracy of the Data document..Technical Documentation/Methodology.Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables.Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Weights.ACS estimates are obtained from a raking ratio estimation procedure that results in the assignment of two sets of weights: a weight to each sample person record and a weight to each sample housing unit record. Estimates of person characteristics are based on the person weight. Estimates of family, household, and housing unit characteristics are based on the housing unit weight. For any given geographic area, a characteristic total is estimated by summing the weights assigned to the persons, households, families or housing units possessing the characteristic in the geographic area. For more information on weighting and estimation in the ACS, see the Accuracy of the Data document.Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population...