Graph and download economic data for Homeownership Rate in the United States (RHORUSQ156N) from Q1 1965 to Q2 2025 about homeownership, housing, rate, and USA.

The homeownership rate in the United States declined slightly in 2023 and remained stable in 2024. The U.S. homeownership rate was the highest in 2004 before the 2007-2009 recession hit and decimated the housing market. In 2024, the proportion of households occupied by owners stood at **** percent in 2024, *** percentage points below 2004 levels. Homeownership since the recession The rate of homeownership in the U.S. fell in the lead up to the recession and continued to do so until 2016. Despite this trend, the share of Americans who perceived homeownership as part of their personal American dream remained relatively stable. This suggests that the financial hardship caused by the recession led to the fall in homeownership, rather than a change in opinion about the importance of homeownership itself. What the future holds for homeownership Homeownership trends vary from generation to generation. Homeownership among Americans over 65 years old is declining, whereas most Millennial renters plan to buy a home in the near future. This suggests that homeownership will remain important in the future, as Millennials are forecast to head most households over the next two decades.

Home Ownership Rate in the United States decreased to 65.10 percent in the first quarter of 2025 from 65.70 percent in the fourth quarter of 2024. This dataset provides the latest reported value for - United States Home Ownership Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Graph and download economic data for Homeownership Rate for the United States (USHOWN) from 1984 to 2024 about homeownership, housing, 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.

Graph and download economic data for Consumer Unit Characteristics: Percent Homeowner by Age: Age 65 or over (CXUHOMEOWNLB0407M) from 1990 to 2023 about 65-years +, consumer unit, age, homeownership, percent, and USA.

United States Homeownership Rate: Annual data was reported at 63.900 % in 2017. This records an increase from the previous number of 63.400 % for 2016. United States Homeownership Rate: Annual data is updated yearly, averaging 64.700 % from Dec 1965 (Median) to 2017, with 53 observations. The data reached an all-time high of 69.000 % in 2004 and a record low of 63.000 % in 1965. United States Homeownership Rate: Annual data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.EB008: Housing Vacancy and Home Ownership Rate.

The homeownership rate was the highest among Americans in their early 70s and the lowest among people in their early 20s in 2023. In that year, approximately ** percent of individuals aged 70 to 75 resided in a residence they owned, compared to approximately **** percent among individuals under the age of 25. On average, **** percent of Americans lived in an owner-occupied home. The homeownership rate was the highest in 2004 but has since declined.

Our US Home Ownership Data is gathered and aggregated via surveys, digital services, and public data sources. We use powerful profiling algorithms to collect and ingest only fresh and reliable data points.

Our comprehensive data enrichment solution includes various data sets that can help you address gaps in your customer data, gain a deeper understanding of your customers, and power superior client experiences. 1. Geography - City, State, ZIP, County, CBSA, Census Tract, etc. 2. Demographics - Gender, Age Group, Marital Status, Language etc. 3. Financial - Income Range, Credit Rating Range, Credit Type, Net worth Range, etc 4. Persona - Consumer type, Communication preferences, Family type, etc 5. Interests - Content, Brands, Shopping, Hobbies, Lifestyle etc. 6. Household - Number of Children, Number of Adults, IP Address, etc. 7. Behaviours - Brand Affinity, App Usage, Web Browsing etc. 8. Firmographics - Industry, Company, Occupation, Revenue, etc 9. Retail Purchase - Store, Category, Brand, SKU, Quantity, Price etc. 10. Auto - Car Make, Model, Type, Year, etc. 11. Housing - Home type, Home value, Renter/Owner, Year Built etc.

Consumer Graph Schema & Reach: Our data reach represents the total number of counts available within various categories and comprises attributes such as country location, MAU, DAU & Monthly Location Pings:

Data Export Methodology: Since we collect data dynamically, we provide the most updated data and insights via a best-suited method on a suitable interval (daily/weekly/monthly).

Consumer Graph Use Cases: 360-Degree Customer View: Get a comprehensive image of customers by the means of internal and external data aggregation. Data Enrichment: Leverage Online to offline consumer profiles to build holistic audience segments to improve campaign targeting using user data enrichment Fraud Detection: Use multiple digital (web and mobile) identities to verify real users and detect anomalies or fraudulent activity. Advertising & Marketing: Understand audience demographics, interests, lifestyle, hobbies, and behaviors to build targeted marketing campaigns.

Multiple advantages with Home Owner Data Set: Increase campaign ROI with personalized and targeted engagements. Utilize predictive real estate data attributes such as home value, purchase date, property descriptors, and mortgage information. Focus resources on high-value prospects and their preferences Maximize conversions with personalized marketing campaigns featuring relevant real estate intelligence. Engage your target audience with messaging tailored to their interests and needs.

BatchData provides comprehensive home ownership data for 87 million owners of residential homes in the US. We specialize in providing accurate contact information for owners of specific properties, trusted by some of the largest real estate companies for our superior capabilities in accurately unmasking owners of properties that may be hidden behind LLCs and corporate veils.

Our home ownership data is commonly used to fuel targeted marketing campaigns, generating real estate insights, powering websites/applications with real estate intelligence, and enriching sales and marketing databases with accurate homeowner contact information and surrounding intelligence to improve segmentation and targeting.

Home ownership data that is linked to a given property includes: - Homeowner Name(s) - Homeowner Cell Phone Number - Homeowner Email Address - Homeowner Mailing Address - Addresses of Properties Owned - Homeowner Portfolio Equity - Total Number of Properties Owned - Property Characteristics of Properties Owned - Homeowner sales, loan, and mortgage information - Property Occupancy Status of Properties Owned - Property Valuation & ARV information of Properties Owned - Ownership Length - Ownership History - Homeowner Age - Homeowner Marital Status - Homeowner Income - and more!

BatchService is both a data and technology company helping companies in and around the real estate ecosystem achieve faster growth. BatchService specializes in providing accurate B2B and B2C contact data for US property owners, including in-depth intelligence and actionable insights related to their property. Our portfolio of products, services, and go-to-market expertise help companies identify their target market, reach the right prospects, enrich their data, consolidate their data providers, and power their products and services.

United States Housing Vacancy Rate: Homeowner: Central City Areas data was reported at 1.700 % in Sep 2018. This records an increase from the previous number of 1.600 % for Jun 2018. United States Housing Vacancy Rate: Homeowner: Central City Areas data is updated quarterly, averaging 1.900 % from Mar 1965 (Median) to Sep 2018, with 210 observations. The data reached an all-time high of 4.300 % in Mar 2008 and a record low of 0.900 % in Jun 1973. United States Housing Vacancy Rate: Homeowner: Central City Areas data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s United States – Table US.EB008: Housing Vacancy and Home Ownership Rate.

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.

United States Homeownership Rate: Less than 25 Years data was reported at 22.600 % in 2017. This records an increase from the previous number of 21.900 % for 2016. United States Homeownership Rate: Less than 25 Years data is updated yearly, averaging 20.800 % from Dec 1982 (Median) to 2017, with 36 observations. The data reached an all-time high of 25.700 % in 2005 and a record low of 14.800 % in 1993. United States Homeownership Rate: Less than 25 Years data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.EB008: Housing Vacancy and Home Ownership Rate.

The homeownership rate in the United States amounted to nearly ** percent in the third quarter of 2024. While there are many factors that affect people’s decision to buy a house, the recent decrease can be attributed to the higher mortgage interest rates, which make taking out a mortgage less affordable for potential buyers, especially considering the surge in house prices in recent years. Which factors affect homeownership? Age and ethnicity have a strong correlation with homeownership. Baby boomers, for example, are twice as likely to own their home than Millennials. Also, the homeownership rate among white Americans is substantially higher than among any other ethnicity. How does the U.S. homeownership rate compare with other countries? Having a home is an integral part of the “American Dream”. Compared with selected European countries, the U.S. ranks alongside the United Kingdom, Cyprus, and Ireland. Many countries in Europe, however, exceed ** percent homeownership rate.

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, 2023 American Community Survey 1-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..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.

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.

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 homeownership, African-American, rate, and USA.

United States Homeownership Rate: 30 to 34 Years data was reported at 45.700 % in 2017. This records an increase from the previous number of 45.400 % for 2016. United States Homeownership Rate: 30 to 34 Years data is updated yearly, averaging 53.200 % from Dec 1982 (Median) to 2017, with 36 observations. The data reached an all-time high of 57.400 % in 2004 and a record low of 45.400 % in 2016. United States Homeownership Rate: 30 to 34 Years data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s United States – Table US.EB008: Housing Vacancy and Home Ownership Rate.

Product Overview

Homeowner Association (HOA) Data is notoriously difficult to obtain from a single source – until now. With HOA Contact Data, you can start identifying properties that are part of an association and may have restrictions for improvements. Knowing whether your prospects are a part of an HOA mitigates risk and streamlines your decision-making. You can avoid the homes that are unlikely to respond or confidently adjust your approach to be more appealing and directed toward the correct audience.

What is HOA Data?

As of 2019, more than 351,000 HOA communities exist across the United State. To be sure you’re connecting with those homeowners in a way they will respond to, it’s important to know the demographics and to have accurate, current, data powering your outreach. Our robust database covers all 50 states (encompassing 2,748 counties) and accounts for more than 49 million unique properties, providing an in-depth snapshot of HOAs across the country.

HOA Data Details

• Property Location
• HOA Name
• HOA Fee Type and Value
• HOA Fee Frequency
• HOA Contact
• HOA Contact Type
• Contact Information (Name, Address, Photo, and Email)