Graph and download economic data for Homeownership Rates by Race and Ethnicity: Hispanic (of Any Race) in the United States (HOLHORUSQ156N) from Q1 1994 to Q2 2025 about homeownership, latino, hispanic, rate, and USA.

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.

In 2018, ** percent of Hispanic or Latino Americans living in Wyoming owned their home. However, their homeownership rate in New York was only ** 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). 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.

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.

Homeownership Rates by Race and Ethnicity: Hispanic (of Any Race) in the United States was 48.80% in April of 2025, according to the United States Federal Reserve. Historically, Homeownership Rates by Race and Ethnicity: Hispanic (of Any Race) in the United States reached a record high of 51.40 in April of 2020 and a record low of 40.30 in January of 1994. Trading Economics provides the current actual value, an historical data chart and related indicators for Homeownership Rates by Race and Ethnicity: Hispanic (of Any Race) in the United States - last updated from the United States Federal Reserve on August of 2025.

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.

This statistic shows the Generation Z homeownership rate in the United States in 2016 and 2025, by ethnicity. In 2016, almost ** percent of Hispanic Americans between 15 and 24 years were homeowners, but this is set to rise to **** percent by 2025 when they will be 25 to 34 years.

Homeownership Rates by Race and Ethnicity: Non-Hispanic White Alone in the United States was 74.00% in April of 2025, according to the United States Federal Reserve. Historically, Homeownership Rates by Race and Ethnicity: Non-Hispanic White Alone in the United States reached a record high of 76.20 in April of 2004 and a record low of 69.80 in January of 1994. Trading Economics provides the current actual value, an historical data chart and related indicators for Homeownership Rates by Race and Ethnicity: Non-Hispanic White Alone in the United States - last updated from the United States Federal Reserve on August of 2025.

U.S. Homeownership Rates - Non-Hispanic White - Historical chart and current data through 2025.

This statistic shows the homeownership rate among LGBT community in the United States in 2018, by race. In 2018, only ** percent of Latino members of the LGBT community owned their home or primary living space, whereas ** percent of white/non-Hispanic members said the same. The homeownership rate of the general population was ** percent in 2018.

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 statistic shows the Millennial homeownership rate in the United States in 2016 and 2025, by ethnicity. In 2016, ** percent of Hispanic Americans between 25 and 34 years were homeowners, but this is set to rise to 45.9 percent by 2025 when they will be 35 to 44 years.

Graph and download economic data for Consumer Unit Characteristics: Percent Homeowner without Mortgage by Hispanic or Latino Origin: Hispanic or Latino (CXU980240LB1002M) from 1994 to 2023 about consumer unit, homeownership, mortgage, latino, hispanic, percent, 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.

In a September 2020 survey among adults in the United States, over half of respondents said that their interest in buying a home had not changed due to the COVID-19 pandemic (** percent). However, Hispanic respondents were more likely to have changed their plans (** percent) compared to white respondents (** percent). In the United States, the 2020 homeownership rate reached **** percent.

Graph and download economic data for Consumer Unit Characteristics: Percent Homeowner with Mortgage by Hispanic or Latino Origin: Hispanic or Latino (CXU980230LB1002M) from 1994 to 2023 about consumer unit, homeownership, latino, hispanic, mortgage, percent, and USA.

In a ************** survey among adults in the United States, there were more people of color (POC)Millennials that were currently saving up to buy a house (** percent) than that there were White Non-Hispanic Millennials (** percent).In the United States, the 2020 homeownership rate reached **** percent.

In a September 2020 survey among adults in the United States, one in three Millennials who was a person of color (POC) said that they were more interested in buying a home due to the COVID-19 pandemic (** percent). On the other hand, the share of White Non-Hispanic Millennials who were more likely to purchase a house was ** percent. In the United States, the 2020 homeownership rate reached **** percent.

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 for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..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..Source: U.S. Census Bureau, 2019-2023 American Community Survey 5-Year Estimates.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..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..The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..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..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.