Since 2011, the average age of British citizens buying their first home in the United Kingdom (UK) increased by two years. In 2011, the average age for the country was 29, while in 2024, it reached ** years. Nevertheless, the average age varied in different regions.

In the 2 years to March 2023, the average age of first-time buyers was 32 years old.

Data on resident buyers who are persons that purchased a residential property in a market sale and filed their T1 tax return form: number of and incomes of residential property buyers, sale price, price-to-income ratio by the number of buyers as part of a sale, age groups, first-time home buyer status, buyer characteristics (sex, family type, immigration status, period of immigration, admission category).

Approximately ** percent of Americans aged 26 to 34 who bought a home were first-home buyers, whereas ** percent of home buyers between 35 and 44 bought their first home in that year. Gen Z and Millennial first-time buyers It is no surprise that many Gen Z (18 to 24 years old) and Millennial (25 to 43 years old) home buyers are mostly first-time home buyers. These home buyers are in the early stages of their careers, or still studying in some cases, and often struggling to repay student debt, so they need to save for many years before they afford a down payment. When do they sell? These generations tend to stay in their first homes for several years, which means that the majority of home sellers are older than them. The share of income needed to afford a trade-up home is significantly lower than the money needed for a starter home. A trade-up home is a larger and more expensive home, which homeowners often buy after living in their starter home, or their first home, for several years. This progression generally happens when homeowners have climbed the career ladder and increased their incomes.

The average age of first-time buyers (FTBs) in Ireland increased by 1.4 years between 2017 and 2023. In 2017, the average age of first-time homebuyers was 33.9 years. In 2023, the average homebuyer was 35.3 years old. During the same period, the age of second and subsequent borrowers experienced slightly less variation.

Nearly one out of four European consumers who were tenants in 2019, believed they would not be able to buy a home in the future. This belief was especially shared in the Netherlands, Belgium, Germany, France, and the UK. However, those who did expect to eventually become first-home buyers believed it was more likely to happen once they passed the age of **. Indeed, in 2019, roughly ** percent of European respondents believed they had to wait until they were older than ** to be able to buy a property.

Graph and download economic data for Consumer Unit Characteristics: Percent Homeowner by Age: from Age 25 to 34 (CXUHOMEOWNLB0403M) from 1990 to 2023 about consumer unit, age, homeownership, 25 years +, percent, and USA.

In 2024, the median income range between of more than 200,000 U.S. dollars was the largest share of homebuyers in the United States that year. Among them, almost ** percent were between 26 and 59 years old. The income range between 100,000 and 124,999 U.S. dollars was the second one with the largest share of homebuyers in the United States that year. Among them, ** percent were between 18 and 34 years old.

This statistic shows the distribution of the French who made the first real estate purchase in 2016, according to the age group. We observe that more than 30% of the first-time buyers of real estate were between 25 and 28 years old.

The average age of second and subsequent buyers (SSBs) in Ireland showed an upward trend between 2017 and 2023. In 2017, the average age stood at 41 years, which then increased to **** years in 2018. There was a further rise to 42 years in 2019. However, in 2020, there was a slight dip to **** years. Over the following three years, the average age continued to climb, surpassing 42 years in 2021 and ultimately reaching its peak at the highest recorded average age of ***** years in 2022. Meanwhile, the average age of first-time buyers also increased.

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.

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

The Public Use Database (PUDB) is released annually to meet FHFA’s requirement under 12 U.S.C. 4543 and 4546(d) to publicly disclose data about the Enterprises’ single-family and multifamily mortgage acquisitions. The datasets supply mortgage lenders, planners, researchers, policymakers, and housing advocates with information concerning the flow of mortgage credit in America’s neighborhoods. Beginning with data for mortgages acquired in 2018, FHFA has ordered that the PUDB be expanded to include additional data that is the same as the data definitions used by the regulations implementing the Home Mortgage Disclosure Act, as required by 12 U.S.C. 4543(a)(2) and 4546(d)(1).The PUDB single-family datasets include loan-level records that include data elements on the income, race, and sex of each borrower as well as the census tract location of the property, loan-to-value (LTV) ratio, age of mortgage note, and affordability of the mortgage. New for 2018 are the inclusion of the borrower’s debt-to-income (DTI) ratio and detailed LTV ratio data at the census tract level. The PUDB multifamily property-level datasets include information on the unpaid principal balance and type of seller/servicer from which the Enterprise acquired the mortgage. New for 2018 is the inclusion of property size data at the census tract level. The multifamily unit-class files also include information on the number and affordability of the units in the property. Both the single-family and multifamily datasets include indicators of whether the purchases are from “underserved” census tracts, as defined in terms of median income and minority percentage of population.Prior to 2010 the single-family PUDB consisted of three files: Census Tract, National A, and National B files. With the 2010 PUDB a fourth file, National C, was added to provide information on high-cost mortgages acquired by the Enterprises. The single-family Census Tract file includes information on the location of the property based on the 2010 Census for acquisition years 2012 through 2021, and the 2020 Census beginning with the 2022 acquisition year. The National files contain other information but lack detailed geographic information in order to protect Enterprise proprietary data. The multifamily datasets also consist of a Census Tract file, and a National file without detailed geographic information.Several dashboards are available to analyze the data:Enterprise Multifamily Public Use Database DashboardThe Enterprise Multifamily Public Use Database (PUDB) Dashboard provides users an interactive way to generate and visualize Enterprise PUDB data of multifamily mortgage acquisitions by Fannie Mae and Freddie Mac. It shows characteristics about multifamily loans, properties and units at the national level, and characteristics about multifamily loans and properties at the state level. It includes key statistics, time series charts, and state maps of multifamily housing characteristics such as median loan amount, number of properties, average number of units per property, and unit affordability. The underlying aggregate statistics presented in the dashboard come from three multifamily data files in the Enterprise PUDB, updated annually since 2008, including two property-level datasets and a data file on the size and affordability of individual units.Enterprise Multifamily Public Use DashboardPress Release - FHFA Releases Data Visualization Dashboard for Enterprises’ Multifamily Mortgage AcquisitionsMortgage Loan and Natural Disaster DashboardFHFA published an interactive Mortgage Loan and Natural Disaster Dashboard that combines FHFA’s PUDB reports on single-family and multifamily acquisitions for the regulated entities, FEMA’s National Risk Index (NRI), and FHFA’s Duty to Serve 2023 High-Needs rural areas. Desired geographies can be exported to .pdf and Excel from the Public Use Database and National Risk Index Dashboard.Mortgage Loan and Natural Disaster DashboardMortgage Loan and Natural Disaster Dashboard FAQs

This data collection is part of the American Housing Metropolitan Survey (AHS-MS, or "metro") which is conducted in odd-numbered years. It cycles through a set of 21 metropolitan areas, surveying each one about once every six years. The metro survey, like the national survey, is longitudinal. This particular survey provides information on the characteristics of a New Orleans metropolitan sample of housing units, including apartments, single-family homes, mobile homes, and vacant housing units in 2009. The data are presented in eight separate parts: Part 1, Home Improvement Record, Part 2, Journey to Work Record, Part 3, Mortgages Recorded, Part 4, Housing Unit Record (Main Record), Recodes (One Record per Housing Unit), and Weights, Part 5, Manager and Owner of Rental Units Record, Part 6, Person Record, Part 7, High Burden Unit Record, and Part 8, Recent Mover Groups Record. Part 1 data include questions about upgrades and remodeling, cost of alterations and repairs, as well as the household member who performed the alteration/repair. Part 2 data include journey to work or commuting information, such as method of transportation to work, length of trip, and miles traveled to work. Additional information collected covers number of hours worked at home, number of days worked at home, average time respondent leaves for work in the morning or evening, whether respondent drives to work alone or with others, and a few other questions pertaining to self-employment and work schedule. Part 3 data include mortgage information, such as type of mortgage obtained by respondent, amount and term of mortgages, as well as years needed to pay them off. Other items asked include monthly payment amount, reason mortgage was taken out, and who provided the mortgage. Part 4 data include household-level information, including demographic information, such as age, sex, race, marital status, income, and relationship to householder. The following topics are also included: data recodes, unit characteristics, and weighting information. Part 5 data include information pertaining to owners of rental properties and whether the owner/resident manager lives on-site. Part 6 data include individual person level information, in which respondents were queried on basic demographic information (i.e. age, sex, race, marital status, income, and relationship to householder), as well as if they worked at all last week, month and year moved into residence, and their ability to perform everyday tasks and whether they have difficulty hearing, seeing, and concentrating or remembering things. Part 7 data include verification of income to cost when the ratio of income to cost is outside of certain tolerances. Respondents were asked whether they receive help or assistance with grocery bills, clothing and transportation expenses, child care payments, medical and utility bills, as well as with rent payments. Part 8 data include recent mover information, such as how many people were living in last unit before move, whether last residence was a condo or a co-op, as well as whether this residence was outside of the United States.

Description: This metric examines how affordable the average First Time Buyer (FTB) priced property would be for a couple earning the average FTB disposable income by NUTS 2 Region, NUTS 3 Region and County, for each year between 2016 and 2021, with this ratio expressed as a percentage (i.e. average monthly mortgage repayment due on the average FTB priced property as a percentage of the average monthly disposable income of an FTB couple). This percentage should be compared relative to the standard affordability mark of 30% (i.e. housing costs should be below 30% of a household’s disposable income). For example, in the attached excel file, the data shows that the Border recorded an Average Mortgage Repayment to Disposable Income Ratio for First Time Buyers of 17.1% in 2021, which was below the standard affordability mark of 30%. This implies that a FTB couple from the Border – on average disposable income levels in the Border and adjusted to reflect incomes of people aged 40 or below in the Border – would only typically have to pay 17.1% of their joint monthly disposable income on their mortgage instalments on the average priced FTB property in the Border. In contrast, the corresponding ratio for Dublin and the Mid-East is 35% and 31.5%, which are both above the standard affordability mark and show that housing for FTBs – on average – is relatively unaffordable in these areas.Basic Calculations = (Average mortgage repayment on average FTB priced property / Average disposable income of a couple under the age of 40).For full detail on the methodology for the development of this ratio please see the RDM FAQ section.This ratio has been developed by the Regional Economist at the three Regional Assemblies and is primarily based on the CSO County Income and Regional GDP as well as the CSO Regional Property Price Index.Geography available in RDM: State, Regional Assembly and Strategic Planning Area (SPA), County (26).Source: Regional AssembliesWeblink: n/aDate of last source data update: April 2023Update Schedule: Annual

About 36 percent of homeowners in England were aged 65 and above, which contrasts sharply with younger age groups, particularly those under 35. Young adults between 25 and 35, made up 15 percent of homeowners and had a dramatically lower homeownership rate. The disparity highlights the growing challenges faced by younger generations in entering the property market, a trend that has significant implications for wealth distribution and social mobility. Barriers to homeownership for young adults The path to homeownership has become increasingly difficult for young adults in the UK. A 2023 survey revealed that mortgage affordability was the greatest obstacle to property purchase. This represents a 39 percent increase from 2021, reflecting the impact of rising house prices and mortgage rates. Despite these challenges, one in three young adults still aspire to get on the property ladder as soon as possible, though many have put their plans on hold. The need for additional financial support from family, friends, and lenders has become more prevalent, with one in five young adults acknowledging this necessity. Regional disparities and housing supply The housing market in England faces regional challenges, with North West England and the West Midlands experiencing the largest mismatch between housing supply and demand in 2023. This imbalance is evident in the discrepancy between new homes added to the housing stock and the number of new households formed. London, despite showing signs of housing shortage, has seen the largest difference between homes built and households formed. The construction of new homes has been volatile, with a significant drop in 2020, a rebound in 2021 and a gradual decline until 2024.

Abstract copyright UK Data Service and data collection copyright owner. The Wealth and Assets Survey (WAS) is a longitudinal survey, which aims to address gaps identified in data about the economic well-being of households by gathering information on level of assets, savings and debt; saving for retirement; how wealth is distributed among households or individuals; and factors that affect financial planning. Private households in Great Britain were sampled for the survey (meaning that people in residential institutions, such as retirement homes, nursing homes, prisons, barracks or university halls of residence, and also homeless people were not included). The WAS commenced in July 2006, with a first wave of interviews carried out over two years, to June 2008. Interviews were achieved with 30,595 households at Wave 1. Those households were approached again for a Wave 2 interview between July 2008 and June 2010, and 20,170 households took part. Wave 3 covered July 2010 - June 2012, Wave 4 covered July 2012 - June 2014 and Wave 5 covered July 2014 - June 2016. Revisions to previous waves' data mean that small differences may occur between originally published estimates and estimates from the datasets held by the UK Data Service. Data are revised on a wave by wave basis, as a result of backwards imputation from the current wave's data. These revisions are due to improvements in the imputation methodology.Note from the WAS team - November 2023:“The Office for National Statistics has identified a very small number of outlier cases present in the seventh round of the Wealth and Assets Survey covering the period April 2018 to March 2020. Our current approach is to treat cases where we have reasonable evidence to suggest the values provided for specific variables are outliers. This approach did not occur for two individuals for several variables involved in the estimation of their pension wealth. While we estimate any impacts are very small overall and median pension wealth and median total wealth estimates are unaffected, this will affect the accuracy of the breakdowns of the pension wealth within the wealthiest decile, and data derived from them. We are urging caution in the interpretation of more detailed estimates.” Survey Periodicity - "Waves" to "Rounds" Due to the survey periodicity moving from “Waves” (July, ending in June two years later) to “Rounds” (April, ending in March two years later), interviews using the ‘Wave 6’ questionnaire started in July 2016 and were conducted for 21 months, finishing in March 2018. Data for round 6 covers the period April 2016 to March 2018. This comprises of the last three months of Wave 5 (April to June 2016) and 21 months of Wave 6 (July 2016 to March 2018). Round 5 and Round 6 datasets are based on a mixture of original wave-based datasets. Each wave of the survey has a unique questionnaire and therefore each of these round-based datasets are based on two questionnaires. While there may be some changes in the questionnaires, the derived variables for the key wealth estimates have not changed over this period. The aim is to collect the same data, though in some cases the exact questions asked may differ slightly. Detailed information on Moving the Wealth and Assets Survey onto a financial years’ basis was published on the ONS website in July 2019. A Secure Access version of the WAS, subject to more stringent access conditions, is available under SN 6709; it contains more detailed geographic variables than the EUL version. Users are advised to download the EUL version first (SN 7215) to see if it is suitable for their needs, before considering making an application for the Secure Access version.Further information and documentation may be found on the ONS Wealth and Assets Survey webpage. Users are advised to the check the page for updates before commencing analysis.Occupation data for 2021 and 2022 data files The ONS have identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. For further information on this issue, please see: https://www.ons.gov.uk/news/statementsandletters/occupationaldatainonssurveys.Latest edition informationFor the 18th edition (May 2023), the inheritance variables 'ivalb1r7' and 'ivalb1r7_i' which had been omitted in error have been added. Main Topics: The WAS questionnaire is divided into two parts with all adults aged 16 years and over (excluding those aged 16 to 18 currently in full-time education) being interviewed in each responding household. Household schedule: This is completed by one person in the household (usually the head of household or their partner) and predominantly collects household level information such as the number, demographics and relationship of individuals to each other, as well as information about the ownership, value and mortgages on the residence and other household assets. Individual schedule: This is given to each adult in the household and asks questions about economic status, education and employment, business assets, benefits and tax credits, saving attitudes and behaviour, attitudes to debt, insolvency, major items of expenditure, retirement, attitudes to saving for retirement, pensions, financial assets, non-mortgage debt, investments and other income. Multi-stage stratified random sample Telephone interview Face-to-face interview 2006 2020 ADOPTION PAY AGE AIRCRAFT ASSETS ATTITUDES TO SAVING BANK ACCOUNTS BICYCLES BOATS BONDS BUSINESS OWNERSHIP BUSINESS RECORDS BUSINESSES CARAVANS CARE OF DEPENDANTS CARERS BENEFITS CARS CHILD BENEFITS CHILD SUPPORT PAYMENTS CHILD TRUST FUNDS COHABITING COMMERCIAL BUILDINGS COST OF LIVING COSTS CREDIT CARD USE DEBILITATIVE ILLNESS DEBTS DISABILITIES EARLY RETIREMENT ECONOMIC ACTIVITY EDUCATIONAL BACKGROUND EDUCATIONAL COURSES EDUCATIONAL FEES EDUCATIONAL STATUS EMPLOYEES EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES ENDOWMENT ASSURANCE ESTATES ETHNIC GROUPS FAMILY BENEFITS FAMILY INCOME FAMILY MEMBERS FINANCIAL ADVICE FINANCIAL COMPENSATION FINANCIAL DIFFICULTIES FINANCIAL SERVICES FRINGE BENEFITS FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... GIFTS Great Britain HEALTH HEALTH STATUS HIRE PURCHASE HOME BUILDINGS INSU... HOME BUYING HOME CONTENTS INSUR... HOME OWNERSHIP HOUSE PRICES HOUSEHOLD BUDGETS HOUSEHOLD HEAD S EC... HOUSEHOLD HEAD S SO... HOUSEHOLD INCOME HOUSEHOLDERS HOUSEHOLDS HOUSING AGE HOUSING ECONOMICS HOUSING FINANCE HOUSING TENURE ILL HEALTH INCOME INCONTINENCE INFORMAL CARE INHERITANCE INSOLVENCIES INSURANCE CLAIMS INTELLECTUAL IMPAIR... INVESTMENT Income JOB HUNTING JOB SEEKER S ALLOWANCE LAND OWNERSHIP LANDLORDS LOANS Labour and employment MAIL ORDER SERVICES MARITAL STATUS MATERNITY BENEFITS MATERNITY PAY MATHEMATICS MOBILE HOMES MORTGAGE ARREARS MORTGAGE PROTECTION... MORTGAGES MOTOR VEHICLE VALUE MOTOR VEHICLES MOTORCYCLES OCCUPATIONAL PENSIONS OCCUPATIONAL QUALIF... OCCUPATIONS OLD AGE BENEFITS ONE PARENT FAMILIES OVERDRAFTS PART TIME EMPLOYMENT PARTNERSHIPS BUSINESS PATERNITY BENEFITS PATERNITY PAY PENSION BENEFITS PENSION CONTRIBUTIONS PENSIONS PERSONAL DEBT REPAY... PERSONAL FINANCE MA... PHYSICAL MOBILITY PLACE OF BIRTH PRIVATE PENSIONS PRIVATE PERSONAL PE... PROFIT SHARING PROFITS QUALIFICATIONS REDUNDANCY PAY RELIGIOUS AFFILIATION RELIGIOUS ATTENDANCE RENTED ACCOMMODATION RENTS RESIDENTIAL BUILDINGS RETIREMENT AGE SAVINGS SAVINGS ACCOUNTS AN... SECOND HOMES SELF EMPLOYED SELLING SHARED HOME OWNERSHIP SHARES SICK PAY SICKNESS AND DISABI... SOCIAL HOUSING SOCIAL SECURITY BEN... SOCIO ECONOMIC STATUS SPOUSES STAKEHOLDER PENSIONS STATE RETIREMENT PE... STATUS IN EMPLOYMENT STUDENT LOANS SUBSIDIARY EMPLOYMENT SUPERVISORY STATUS TAX RELIEF TENANTS HOME PURCHA... TIED HOUSING TOP MANAGEMENT TRANSPORT FARES TRUSTS UNEARNED INCOME UNEMPLOYED UNFURNISHED ACCOMMO... UNWAGED WORKERS WAGES WEALTH WILLS WINNINGS WORKPLACE property and invest...

The number of bonuses paid out compared to the number of total property completions by age group in the United Kingdom (UK) in the 'help to buy' scheme between December 2015 and June 2023 varied by age group. Those aged between 25 and 34 years old used the help to buy scheme and received bonuses as well as making property completions far more than any other age group; 25 to 34 year old's received over 482,231 bonuses and made approximately 370,120 property completions.

Data on the income, age, sex, employment status and marital status of residential property owners and other tax filers who do not own property, for the provinces of Nova Scotia, Ontario and British Columbia, their census metropolitan areas and associated census subdivisions.