100+ datasets found
  1. Homeowners with current or overdue mortgage payments in the U.S. in 2024, by...

    • statista.com
    Updated Jul 29, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Homeowners with current or overdue mortgage payments in the U.S. in 2024, by race [Dataset]. https://www.statista.com/statistics/1251602/mortgage-borrowers-by-mortgage-payment-status-and-race-usa/
    Explore at:
    Dataset updated
    Jul 29, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Aug 20, 2024 - Sep 16, 2024
    Area covered
    United States
    Description

    Over ********* black households had overdue mortgage payments in the period between the 20th of August and the 16th of September 2024, while **** million reported they were caught up on mortgage payments. In comparison, approximately *** million white households were behind with their payments, whereas **** million were on track. This makes White homeowners least affected by late mortgage payments.

  2. F

    Consumer Unit Characteristics: Percent Homeowner without Mortgage by Housing...

    • fred.stlouisfed.org
    json
    Updated Sep 25, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2024). Consumer Unit Characteristics: Percent Homeowner without Mortgage by Housing Tenure: Home Owner [Dataset]. https://fred.stlouisfed.org/series/CXU980240LB1702M
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 25, 2024
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Consumer Unit Characteristics: Percent Homeowner without Mortgage by Housing Tenure: Home Owner (CXU980240LB1702M) from 1984 to 2023 about consumer unit, homeownership, mortgage, percent, housing, and USA.

  3. English Housing Survey data on owner occupiers, recent first time buyers and...

    • gov.uk
    Updated Jul 17, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ministry of Housing, Communities and Local Government (2025). English Housing Survey data on owner occupiers, recent first time buyers and second homes [Dataset]. https://www.gov.uk/government/statistical-data-sets/owner-occupiers-recent-first-time-buyers-and-second-homes
    Explore at:
    Dataset updated
    Jul 17, 2025
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Ministry of Housing, Communities and Local Government
    Description

    Tables on:

    • trends in ownership
    • types of purchase
    • recent first-time buyers
    • types of mortgage
    • mortgage payments
    • leaseholders
    • moves out of owner occupation
    • second homes

    The previous Survey of English Housing live table number is given in brackets below. Please note from July 2024 amendments have been made to the following tables:

    Table FA2211 and FA2221 have been combined into table FA4222.

    Table FA2501 and FA2511 and FA2531 have been combined into table FA2555.

    For data prior to 2022-23 for the above tables, see discontinued tables.

    Live tables

    https://assets.publishing.service.gov.uk/media/687830bff5eb08157f36385f/FA2222_type_of_purchase_by_age_of_HRP_and_household_type.ods">FA2222 (FA2211 and FA2221): type of purchase by age of household reference person

     <p class="gem-c-attachment_metadata"><span class="gem-c-attachment_attribute"><abbr title="OpenDocument Spreadsheet" class="gem-c-attachment_abbr">ODS</abbr></span>, <span class="gem-c-attachment_attribute">12.5 KB</span></p>
    
    
    
      <p class="gem-c-attachment_metadata">
       This file is in an <a href="https://www.gov.uk/guidance/using-open-document-formats-odf-in-your-organisation" target="_self" class="govuk-link">OpenDocument</a> format
    

    https://assets.publishing.service.gov.uk/media/687830e3760bf6cedaf5bd7e/FA2321_sources_of_finance_besides_mortgage_for_purchase_ofcurrentproperty.ods">FA2321 (S311): sources of finance, other than a mortgage, for purchase of current property

     <p class="gem-c-attachment_metadata"><span class="gem-c-attachment_attribute"><abbr title="OpenDocument Spreadsheet" class="gem-c-attachment_abbr">ODS</abbr></span>, <span class="gem-c-attachment_attribute">17.9 KB</span></p>
    
    
    
      <p class="gem-c-attachment_metadata">
       This file is in an <a href="https://www.gov.uk/guidance/using-open-document-formats-odf-in-your-organisation" target="_self" class="govuk-link">OpenDocument</a> format
    

    <a class="govuk-link" target="_self" tabindex="-1" aria-hidden="true" data-ga4-link='{"event_name":"file_download","type":"attachment"}' href="https://assets.pub

  4. d

    Mortgage Data, Property Data, Title Data, Ownership Data | Over 150 MM...

    • datarade.ai
    Updated Nov 7, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    McGRAW (2024). Mortgage Data, Property Data, Title Data, Ownership Data | Over 150 MM Records and 200 Attributes [Dataset]. https://datarade.ai/data-products/mcgraw-mortgage-data-property-data-title-data-ownership-da-mcgraw
    Explore at:
    .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Nov 7, 2024
    Dataset authored and provided by
    McGRAW
    Area covered
    United States of America
    Description

    Discover the power of McGRAW’s comprehensive data solutions, the industry's largest and most complete property and ownership database in the nation. Additionally, the mortgage industry's most sought-after analytics solutions for loan quality, risk management, compliance, and collateral valuation. These data sets are built to empower businesses with reliable, accurate, and actionable insights across the mortgage, real estate, and title sectors. With access to over 150 million records and 200 attributes, our expansive data repository enables you to streamline decision-making, optimize marketing, and enhance customer targeting across industries. Take a look at the comprehensive data sets below:

    Mortgage Data Our mortgage data encompasses loan origination, borrower profiles, mortgage terms, and payment statuses, providing a complete view of borrowers and mortgage landscapes. We deliver details on active and historical mortgages, including lender information, loan types, interest rates, and mortgage maturity. This empowers financial institutions and analysts to predict market trends, assess creditworthiness, and personalize customer outreach with accuracy.

    Property Data McGRAW’s property data includes detailed attributes on residential and commercial properties, spanning property characteristics, square footage, zoning information, construction dates, and much more. Our data empowers real estate professionals, property appraisers, and investors to make well-informed decisions based on current and historical property details.

    Title Data Our title data service provides a clear view of ownership history and title status, ensuring comprehensive information on property chain-of-title, lien positions, encumbrances, and transaction history. This invaluable data assists title companies, legal professionals, and financial institutions in validating title claims, mitigating risks, and reducing time-to-close.

    Ownership Data McGRAW ownership data supplies in-depth insights into individual and corporate property ownership, offering information on property owners, purchase prices, and ownership duration. This dataset is crucial for due diligence, investment planning, and market analysis, giving businesses the competitive edge to identify opportunities and assess ownership patterns in the marketplace.

    Unmatched Data Quality & Coverage Our data covers the full spectrum of residential and commercial properties in the United States, with attributes verified for accuracy and updated regularly. From state-of-the-art technology to rigorous data validation practices, McGRAW’s data quality stands out, providing the confidence that businesses need to make strategic decisions.

    Why Choose McGRAW Data?

    Extensive Reach: Over 150 million records provide unparalleled depth and breadth of data coverage across all 50 states.

    Diverse Attributes: With 200 attributes across mortgage, property, title, and ownership data, businesses can customize data views for specific needs.

    Actionable Insights: Our data analytics tools and customizable reports translate raw data into valuable insights, helping you stay ahead in the competitive landscape.

    Leverage McGRAW’s data solutions to unlock a holistic view of the mortgage, property, title, and ownership landscapes. For real estate professionals, lenders, and investors seeking data-driven growth, McGRAW provides the tools to elevate decision-making, enhance operational efficiency, and drive business success in today’s data-centric market.

  5. Number of existing homes sold in the U.S. 1995-2024, with a forecast until...

    • statista.com
    Updated Apr 28, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Number of existing homes sold in the U.S. 1995-2024, with a forecast until 2026 [Dataset]. https://www.statista.com/statistics/226144/us-existing-home-sales/
    Explore at:
    Dataset updated
    Apr 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The number of U.S. home sales in the United States declined in 2024, after soaring in 2021. A total of four million transactions of existing homes, including single-family, condo, and co-ops, were completed in 2024, down from 6.12 million in 2021. According to the forecast, the housing market is forecast to head for recovery in 2025, despite transaction volumes expected to remain below the long-term average. Why have home sales declined? The housing boom during the coronavirus pandemic has demonstrated that being a homeowner is still an integral part of the American dream. Nevertheless, sentiment declined in the second half of 2022 and Americans across all generations agreed that the time was not right to buy a home. A combination of factors has led to house prices rocketing and making homeownership unaffordable for the average buyer. A survey among owners and renters found that the high home prices and unfavorable economic conditions were the two main barriers to making a home purchase. People who would like to purchase their own home need to save up a deposit, have a good credit score, and a steady and sufficient income to be approved for a mortgage. In 2022, mortgage rates experienced the most aggressive increase in history, making the total cost of homeownership substantially higher. Are U.S. home prices expected to fall? The median sales price of existing homes stood at 413,000 U.S. dollars in 2024 and was forecast to increase slightly until 2026. The development of the S&P/Case Shiller U.S. National Home Price Index shows that home prices experienced seven consecutive months of decline between June 2022 and January 2023, but this trend reversed in the following months. Despite mild fluctuations throughout the year, home prices in many metros are forecast to continue to grow, albeit at a much slower rate.

  6. F

    Homeownership Rate in the United States

    • fred.stlouisfed.org
    json
    Updated Jul 28, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2025). Homeownership Rate in the United States [Dataset]. https://fred.stlouisfed.org/series/RHORUSQ156N
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 28, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    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.

  7. Average years in current home in England 2011-2024, by tenure

    • statista.com
    Updated Jul 11, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Average years in current home in England 2011-2024, by tenure [Dataset]. https://www.statista.com/statistics/755763/number-of-years-in-current-home-england/
    Explore at:
    Dataset updated
    Jul 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 2023 - Mar 2024
    Area covered
    United Kingdom, England
    Description

    The average number of years individuals spent in their current home in England between 2010 and 2024 varied by tenure. Outright homeowners, on average, stay in the same home far longer than any other tenure type. Private renters, spend on average *** years in their current residence in 2024, up from *** years on average in 2011. In 2024, there were around four million of such private rented households in England.

  8. Homeowners behind on mortgage payments in the U.S. 2022-2023, by age

    • statista.com
    Updated Jul 8, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Homeowners behind on mortgage payments in the U.S. 2022-2023, by age [Dataset]. https://www.statista.com/statistics/1251586/mortgage-borrowers-behind-on-mortgage-payments-by-age-usa/
    Explore at:
    Dataset updated
    Jul 8, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jun 7, 2023 - Jun 19, 2023
    Area covered
    United States
    Description

    About ************ U.S. households were estimated to be behind on their last month's mortgage repayment in *********. Homeowners between 40 and 54 years made up over *********** households late on their payment. Second in rank were roughly *********** homeowners between 25 and 39 years. The smallest number of mortgage borrowers who struggled repaying their mortgage loan was for those between 18 and 24 years.

  9. F

    Delinquency Rate on Single-Family Residential Mortgages, Booked in Domestic...

    • fred.stlouisfed.org
    json
    Updated May 21, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2025). Delinquency Rate on Single-Family Residential Mortgages, Booked in Domestic Offices, All Commercial Banks [Dataset]. https://fred.stlouisfed.org/series/DRSFRMACBS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    May 21, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Delinquency Rate on Single-Family Residential Mortgages, Booked in Domestic Offices, All Commercial Banks (DRSFRMACBS) from Q1 1991 to Q1 2025 about domestic offices, delinquencies, 1-unit structures, mortgage, family, residential, commercial, domestic, banks, depository institutions, rate, and USA.

  10. s

    Home ownership

    • ethnicity-facts-figures.service.gov.uk
    csv
    Updated Apr 7, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Race Disparity Unit (2025). Home ownership [Dataset]. https://www.ethnicity-facts-figures.service.gov.uk/housing/owning-and-renting/home-ownership/latest
    Explore at:
    csv(58 KB)Available download formats
    Dataset updated
    Apr 7, 2025
    Dataset authored and provided by
    Race Disparity Unit
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    England
    Description

    70% of White British households owned their own homes – the highest percentage out of all ethnic groups.

  11. CoreLogic Smart Data Platform: Owner Transfer and Mortgage

    • redivis.com
    application/jsonl +7
    Updated Aug 1, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Stanford University Libraries (2024). CoreLogic Smart Data Platform: Owner Transfer and Mortgage [Dataset]. http://doi.org/10.57761/8twx-xz17
    Explore at:
    parquet, application/jsonl, sas, avro, csv, spss, arrow, stataAvailable download formats
    Dataset updated
    Aug 1, 2024
    Dataset provided by
    Redivis Inc.
    Authors
    Stanford University Libraries
    Description

    Abstract

    The Owner Transfer and Mortgage data covers over 450 million properties, and includes over 50 years of sales history. The tables were generated in June 2024, and cover all U.S. states, the U.S. Virgin Islands, Guam, and Washington, D.C.

    The Owner Transfer data provides historical information about property sales and ownership-related transactions, including full, nominal, and quitclaim transactions (involving a change in title/ownership). It contains comprehensive property and transaction information, such as property characteristics, current ownership, transaction history, title company, cash purchase/foreclosure/resale/short sale indicators, and buyer information.

    The Mortgage data provides historical information at the mortgage level, including purchase, refinance, equity, as well as details associated with each transaction, such as lender, loan amount, loan date, interest rate, etc. Mortgage details include mortgage amount, type of loan (conventional, FHA, VHA), mortgage rate type, mortgage purpose (cash out first, consolidation, standalone subordinate), mortgage ARM features, and mortgage indicators such as fixed-rate, conforming loan, construction loan, and private party. The Mortgage data also includes subordinate mortgage types, rate details, and lender details (NMLS ID, Loan Company, Loan Officers).

    The CoreLogic Smart Data Platform (SDP) Owner Transfer and Mortgage data was formerly known as the CoreLogic Deed data. The CoreLogic Deed data contained both owner transfer and mortgage information. In the CoreLogic Smart Data Platform (SDP), this data was separated into two tables: Owner Transfer and Mortgage. Between the two tables, the CoreLogic Smart Data Platform (SDP) Owner Transfer and Mortgage data contains almost all of the variables that were included in the CoreLogic Deed data. Further, each CoreLogic Smart Data Platform (SDP) table is augmented with additional owner transfer and mortgage characteristics.

    Methodology

    In the United States, parcel data is public record information that describes a division of land (also referred to as "property" or "real estate"). Each parcel is given a unique identifier called an Assessor’s Parcel Number or APN. The two principal types of records maintained by county government agencies for each parcel of land are deed and property tax records. When a real estate transaction takes place (e.g. a change in ownership), a property deed must be signed by both the buyer and seller. The deed will then be filed with the County Recorder’s offices, sometimes called the County Clerk-Recorder or other similar title. Property tax records are maintained by County Tax Assessor’s offices; they show the amount of taxes assessed on a parcel and include a detailed description of any structures or buildings on the parcel, including year built, square footages, building type, amenities like a pool, etc. There is not a uniform format for storing parcel data across the thousands of counties and county equivalents in the U.S.; laws and regulations governing real estate/property sales vary by state. Counties and county equivalents also have inconsistent approaches to archiving historical parcel data.

    To fill researchers’ needs for uniform parcel data, CoreLogic collects, cleans, and normalizes public records that they collect from U.S. County Assessor and Recorder offices. CoreLogic augments this data with information gathered from other public and non-public sources (e.g., loan issuers, real estate agents, landlords, etc.). The Stanford Libraries has purchased bulk extracts from CoreLogic’s parcel data, including mortgage, owner transfer, pre-foreclosure, and historical and contemporary tax assessment data. Data is bundled into pipe-delimited text files, which are uploaded to Data Farm (Redivis) for preview, extraction and analysis.

    For more information about how the data was prepared for Redivis, please see CoreLogic 2024 GitLab.

    Usage

    The Property, Mortgage, Owner Transfer, Historical Property and Pre-Foreclosure data can be linked on the CLIP, a unique identification number assigned to each property.

    Mortgage records can be linked to a transaction using the MORTGAGE_COMPOSITE_TRANSACTION_ID.

    For more information about included variables, please see:

    • core_logic_sdp_owner_transfer_data_dictionary_2024.txt
    • core_logic_sdp_mortgage_data_dictionary_2024.txt
    • Mortgage_v3.xlsx
    • Owner Transfer_v3.xlsx

    %3C!-- --%3E

    For a count of records per FIPS code, please see core_logic_sdp_owner_transfer_counts_2024.txt and core_logic_sdp_mortgage_counts_2024.txt.

    For more information about how the CoreLogic Smart Data Platform: Owner Transfer and Mortgage data compares to legacy data, please see core_logic_legacy_content_mapping.pdf.

    Bulk Data Access

    Data access is required to view this section.

  12. U

    US Mortgage Lending Market Report

    • marketreportanalytics.com
    doc, pdf, ppt
    Updated Apr 30, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Market Report Analytics (2025). US Mortgage Lending Market Report [Dataset]. https://www.marketreportanalytics.com/reports/us-mortgage-lending-market-99565
    Explore at:
    pdf, doc, pptAvailable download formats
    Dataset updated
    Apr 30, 2025
    Dataset authored and provided by
    Market Report Analytics
    License

    https://www.marketreportanalytics.com/privacy-policyhttps://www.marketreportanalytics.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The US mortgage lending market, a cornerstone of the American economy, is experiencing robust growth, projected to maintain a Compound Annual Growth Rate (CAGR) exceeding 5% from 2025 to 2033. This expansion is fueled by several key factors. Firstly, a consistently increasing population and household formations drive demand for housing, consequently boosting mortgage loan originations. Secondly, historically low interest rates in recent years have stimulated borrowing, making homeownership more accessible. Furthermore, government initiatives aimed at supporting homeownership, along with increasing disposable incomes in certain segments of the population, contribute to the market's positive trajectory. The market is segmented by loan type (fixed-rate mortgages and home equity lines of credit), service providers (commercial banks, financial institutions, credit unions, and other lenders), and application mode (online and offline). Competition is intense among major players like Bank of America, Chase Bank, and US Bank, with smaller institutions and credit unions vying for market share. While the overall trend is positive, potential headwinds include fluctuations in interest rates, economic downturns impacting consumer confidence, and stringent regulatory environments which can impact lending practices. The geographical distribution of the US mortgage lending market reflects regional economic variations. While the United States dominates North America's market share, growth potential exists across various international markets. European and Asian markets, though characterized by distinct regulatory landscapes and consumer behaviors, present opportunities for expansion. The market's future trajectory will depend on several interconnected factors, including macroeconomic conditions, demographic shifts, and technological advancements influencing the mortgage lending process. The continued adoption of digital technologies is expected to streamline lending processes and expand access, impacting the future of the market significantly. Strategic partnerships and acquisitions are also anticipated, further consolidating the market landscape and driving innovation. Recent developments include: August 2023: Spring EQ, a provider of home equity financing solutions, has entered into a definitive agreement to be acquired by an affiliate of Cerberus Capital Management, L.P., a global leader in alternative investing. The main aim of the partnership is to support Spring EQ's mission to deliver offerings and expand its leadership in the home equity financing market., June 2023: VIU by HUB, a digital insurance brokerage platform subsidiary of Hub International Limited, has entered into a new partnership with Unison, a home equity-sharing company. The collaboration will allow homeowners to compare insurance coverage quotes from various carriers and receive expert advice throughout the process.. Key drivers for this market are: Home Renovation Trends are Driving the Market. Potential restraints include: Home Renovation Trends are Driving the Market. Notable trends are: Home Equity Lending Market is Being Stimulated By Rising Home Prices.

  13. T

    Lithuania - Overcrowding rate: Owner, with mortgage or loan

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jun 22, 2021
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    TRADING ECONOMICS (2021). Lithuania - Overcrowding rate: Owner, with mortgage or loan [Dataset]. https://tradingeconomics.com/lithuania/overcrowding-rate-owner-with-mortgage-or-loan-eurostat-data.html
    Explore at:
    excel, xml, json, csvAvailable download formats
    Dataset updated
    Jun 22, 2021
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Lithuania
    Description

    Lithuania - Overcrowding rate: Owner, with mortgage or loan was 24.50% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Lithuania - Overcrowding rate: Owner, with mortgage or loan - last updated from the EUROSTAT on August of 2025. Historically, Lithuania - Overcrowding rate: Owner, with mortgage or loan reached a record high of 45.70% in December of 2010 and a record low of 11.00% in December of 2012.

  14. Number of owner-occupied homes in the U.S. 1975-2023

    • statista.com
    Updated Apr 12, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2024). Number of owner-occupied homes in the U.S. 1975-2023 [Dataset]. https://www.statista.com/statistics/187576/housing-units-occupied-by-owner-in-the-us-since-1975/
    Explore at:
    Dataset updated
    Apr 12, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Following a period of stagnation over most of the 2010s, the number of owner occupied housing units in the United States started to grow in 2017. In 2023, there were over 86 million owner-occupied homes. Owner-occupied housing is where the person who owns a property – either outright or through a mortgage – also resides in the property. Excluded are therefore rental properties, employer-provided housing and social housing. Homeownership sentiment in the U.S. Though homeownership is still a cornerstone of the American dream, an increasing share of people see themselves as lifelong renters. Millennials have been notoriously late to enter the housing market, with one in four reporting that they would probably continue to always rent in the future, a 2022 survey found. In 2017, just five years before that, this share stood at about 13 percent. How many renter households are there? Renter households are roughly half as few as owner-occupied households in the U.S. In 2023, the number of renter occupied housing units amounted to almost 45 million. Climbing on the property ladder for renters is not always easy, as it requires prospective homebuyers to save up for a down payment and qualify for a mortgage. In many metros, the median household income is insufficient to qualify for the median-priced home.

  15. T

    Spain - Housing cost overburden rate: Owner, no outstanding mortgage or...

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jul 27, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    TRADING ECONOMICS (2020). Spain - Housing cost overburden rate: Owner, no outstanding mortgage or housing loan [Dataset]. https://tradingeconomics.com/spain/housing-cost-overburden-rate-owner-no-outsting-mortgage-or-housing-loan-eurostat-data.html
    Explore at:
    json, csv, xml, excelAvailable download formats
    Dataset updated
    Jul 27, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Spain
    Description

    Spain - Housing cost overburden rate: Owner, no outstanding mortgage or housing loan was 2.20% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Spain - Housing cost overburden rate: Owner, no outstanding mortgage or housing loan - last updated from the EUROSTAT on July of 2025. Historically, Spain - Housing cost overburden rate: Owner, no outstanding mortgage or housing loan reached a record high of 3.10% in December of 2021 and a record low of 1.60% in December of 2009.

  16. c

    Survey of Consumer Finances, 1962

    • archive.ciser.cornell.edu
    • icpsr.umich.edu
    Updated Feb 23, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Economic Behavior Program (2020). Survey of Consumer Finances, 1962 [Dataset]. http://doi.org/10.6077/atzj-2r27
    Explore at:
    Dataset updated
    Feb 23, 2020
    Dataset authored and provided by
    Economic Behavior Program
    Variables measured
    Other
    Description

    This data collection is one in a series of financial surveys of consumers conducted annually since 1946. In a nationally representative sample, the head of each spending unit (usually the husband, the main earner, or the owner of the home) was interviewed. The basic unit of reference in the study was the spending unit, but some family data are also available. The questions in the 1962 survey covered the respondent's attitudes toward national economic conditions and price activity, as well as the respondent's own financial situation. Other questions examined the spending unit head's occupation, and the nature and amount of the spending unit's income, debts, liquid assets, changes in liquid assets, savings, investment preferences, and actual and expected purchases of cars and other major durables. In addition, the survey explored in detail the subject of housing, e.g., previous and present home ownership, value of respondent's dwelling, and mortgage information. The survey paid particular attention to assets and net worth. Personal data include number of people in the spending unit, age, sex, and education of the head, and the race and sex of the respondent. (Source: downloaded from ICPSR 7/13/10)

    Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR07442.v2. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

  17. T

    Czech Republic - Overcrowding rate: Owner, no outstanding mortgage or...

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 11, 2021
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    TRADING ECONOMICS (2021). Czech Republic - Overcrowding rate: Owner, no outstanding mortgage or housing loan [Dataset]. https://tradingeconomics.com/czech-republic/overcrowding-rate-owner-no-outsting-mortgage-or-housing-loan-eurostat-data.html
    Explore at:
    csv, xml, excel, jsonAvailable download formats
    Dataset updated
    May 11, 2021
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Czech Republic
    Description

    Czech Republic - Overcrowding rate: Owner, no outstanding mortgage or housing loan was 10.20% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Czech Republic - Overcrowding rate: Owner, no outstanding mortgage or housing loan - last updated from the EUROSTAT on July of 2025. Historically, Czech Republic - Overcrowding rate: Owner, no outstanding mortgage or housing loan reached a record high of 17.60% in December of 2010 and a record low of 10.20% in December of 2024.

  18. T

    Greece - Overcrowding rate: Owner, with mortgage or loan

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 24, 2021
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    TRADING ECONOMICS (2021). Greece - Overcrowding rate: Owner, with mortgage or loan [Dataset]. https://tradingeconomics.com/greece/overcrowding-rate-owner-with-mortgage-or-loan-eurostat-data.html
    Explore at:
    csv, json, xml, excelAvailable download formats
    Dataset updated
    Mar 24, 2021
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Greece
    Description

    Greece - Overcrowding rate: Owner, with mortgage or loan was 26.80% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Greece - Overcrowding rate: Owner, with mortgage or loan - last updated from the EUROSTAT on July of 2025. Historically, Greece - Overcrowding rate: Owner, with mortgage or loan reached a record high of 35.60% in December of 2016 and a record low of 21.10% in December of 2011.

  19. T

    Hungary - Overcrowding rate: Owner, no outstanding mortgage or housing loan

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jun 18, 2021
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    TRADING ECONOMICS (2021). Hungary - Overcrowding rate: Owner, no outstanding mortgage or housing loan [Dataset]. https://tradingeconomics.com/hungary/overcrowding-rate-owner-no-outsting-mortgage-or-housing-loan-eurostat-data.html
    Explore at:
    csv, xml, excel, jsonAvailable download formats
    Dataset updated
    Jun 18, 2021
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Hungary
    Description

    Hungary - Overcrowding rate: Owner, no outstanding mortgage or housing loan was 13.70% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Hungary - Overcrowding rate: Owner, no outstanding mortgage or housing loan - last updated from the EUROSTAT on July of 2025. Historically, Hungary - Overcrowding rate: Owner, no outstanding mortgage or housing loan reached a record high of 43.10% in December of 2010 and a record low of 13.70% in December of 2024.

  20. a

    How many housing units are owned with a mortgage?

    • hub.arcgis.com
    Updated Apr 10, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    ArcGIS Living Atlas Team (2020). How many housing units are owned with a mortgage? [Dataset]. https://hub.arcgis.com/datasets/fe4802a9abf349a497bd5d3932b66b2a
    Explore at:
    Dataset updated
    Apr 10, 2020
    Dataset authored and provided by
    ArcGIS Living Atlas Team
    Area covered
    Description

    This map shows how many housing units are owner-occupied with a mortgage in the United States. The maps shows this as a percentage of all owner-occupied housing units, and also shows it as a count of how many housing units are owned with a mortgage. The areas in bright yellow have the highest percentage of mortgage-owned homes. The pop-up provides additional information about owner-occupied units in each area. Search for any area within the US or Puerto Rico to see local or regional patterns. The data comes from the most current American Community Survey (ACS) data, and gets updated annually when the US Census Bureau releases their newest ACS estimates. To see the full documentation for the layer used in this map, click here. To find detailed ACS data for other topics, find them here in ArcGIS Living Atlas of the World.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Statista (2025). Homeowners with current or overdue mortgage payments in the U.S. in 2024, by race [Dataset]. https://www.statista.com/statistics/1251602/mortgage-borrowers-by-mortgage-payment-status-and-race-usa/
Organization logo

Homeowners with current or overdue mortgage payments in the U.S. in 2024, by race

Explore at:
Dataset updated
Jul 29, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Aug 20, 2024 - Sep 16, 2024
Area covered
United States
Description

Over ********* black households had overdue mortgage payments in the period between the 20th of August and the 16th of September 2024, while **** million reported they were caught up on mortgage payments. In comparison, approximately *** million white households were behind with their payments, whereas **** million were on track. This makes White homeowners least affected by late mortgage payments.

Search
Clear search
Close search
Google apps
Main menu