The average sales price of new homes in the United States experienced a slight decrease in 2024, dropping to 512,2000 U.S. dollars from the peak of 521,500 U.S. dollars in 2022. This decline came after years of substantial price increases, with the average price surpassing 400,000 U.S. dollars for the first time in 2021. The recent cooling in the housing market reflects broader economic trends and changing consumer sentiment towards homeownership. Factors influencing home prices and affordability The rapid rise in home prices over the past few years has been driven by several factors, including historically low mortgage rates and increased demand during the COVID-19 pandemic. However, the market has since slowed down, with the number of home sales declining by over two million between 2021 and 2023. This decline can be attributed to rising mortgage rates and decreased affordability. The Housing Affordability Index hit a record low of 98.1 in 2023, indicating that the median-income family could no longer afford a median-priced home. Future outlook for the housing market Despite the recent cooling, experts forecast a potential recovery in the coming years. The Freddie Mac House Price Index showed a growth of 6.5 percent in 2023, which is still above the long-term average of 4.4 percent since 1990. However, homebuyer sentiment remains low across all age groups, with people aged 45 to 64 expressing the most pessimistic outlook. The median sales price of existing homes is expected to increase slightly until 2025, suggesting that affordability challenges may persist in the near future.

The majority of the U.S. housing stock was between 42 and 51 years old as of 2021. According to the source, the median year was 1979, meaning that the median house age was 42 years. Housing construction in the U.S. plummeted between 2005 and 2010 and has since been slow to recover.

Graph and download economic data for Housing Inventory: Median Days on Market in the United States (MEDDAYONMARUS) from Jul 2016 to Jun 2025 about median and USA.

Context

Zillow provides data on sold homes, including sales counts (for which there’s detailed methodology), median sale price for various housing types, and foreclosures provided as a share of all sales in which the home was previously foreclosed upon. There are current and historical listings data, ranging from median list prices and inventory counts to share of listings with a price cut, median price cut size, age of inventory, and the days a listing spent on Zillow before the sale was final. See below for full list with definitions.

Acknowledgements

Data courtesy of Zillow

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.

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

About this file add_comment Add Suggestion The California housing dataset contains information on various socio-economic features of block groups in California. Each row in the dataset represents a single block group, and there are 20,640 observations, each with 10 attributes.The Features are as follows: 1.Longitude: The longitude of the center of each block group in California. 2.Latitude: The latitude of the center of each block group in California. 3.Housing Median Age: The median age of the housing units in each block group. 4.Total Rooms: The total number of rooms in the housing units in each block group. 5.Total Bedrooms: The total number of bedrooms in the housing units in each block group. 6.Population: The total population of the block group. 7.Households: The total number of households in the block group. 8.Median Income: The median income of the block group. 9.Median House Value: The median value of the housing units in the block group. 10.Ocean Proximity: The proximity of the block group to the ocean or other bodies of water. Table

In 2024, the average age of recent first-time buyers in London was slightly higher than the England average. Across the UK, first-time buyers accounted for approximately ******* home sales. First-time buyer prices and mortgages In London, the average value of a mortgage for first-time buyers was far higher than all other regions in the UK. Apart from the initial cost of a down payment, those that can afford to, see monthly payment savings against those renting. In certain parts of the country, annual savings of buying against renting saw first time buyers amounted to over ************ British pounds. Help to buy To encourage first-time buyers, the UK government started the "Help to buy" scheme. The scheme sees people saving for a first-time home receive a ***********bonus to their savings when purchasing a house valued at ******* British pounds (******* British pounds in London). Between December 2015 and March 2018, the North West of England saw the highest number of Help to buy ISA bonuses paid.

Average age and remaining useful service life ratio of Canadian residential housing assets. Annual estimates are available by province and territory, type of asset, and type of dwelling.

The majority of home buyers in the United States in 2021 purchased homes that cost *** thousand U.S. dollars or more. Homes over *** thousand U.S. dollars were purchased by ** percent of buyers from the ** to ** age group who made up the largest share of buyers in that category.

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in New Home. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in New Home. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2023

In terms of income distribution across age cohorts, in New Home, the median household income stands at $98,125 for householders within the 45 to 64 years age group, followed by $55,313 for the 25 to 44 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $38,000.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New Home median household income by age. You can refer the same here

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).

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.

Update 29-04-2020: The data is now split into two files based on the variable collection frequency (monthly and yearly). Additional variables added: area size in hectares, number of jobs in the area, number of people living in the area.

Context

I have been inspired by Xavier and his work on Barcelona to explore the city of London! 🇬🇧 💂

Content

The datasets is primarily centered around the housing market of London. However, it contains a lot of additional relevant data: - Monthly average house prices - Yearly number of houses - Yearly number of houses sold - Yearly percentage of households that recycle - Yearly life satisfaction - Yearly median salary of the residents of the area - Yearly mean salary of the residents of the area - Monthly number of crimes committed - Yearly number of jobs - Yearly number of people living in the area - Area size in hectares

The data is split by areas of London called boroughs (a flag exists to identify these), but some of the variables have other geographical UK regions for reference (like England, North East, etc.). There have been no changes made to the data except for melting it into a long format from the original tables.

Acknowledgements

The data has been extracted from London Datastore. It is released under UK Open Government License v2 and v3. The underlining datasets can be found here: https://data.london.gov.uk/dataset/uk-house-price-index https://data.london.gov.uk/dataset/number-and-density-of-dwellings-by-borough https://data.london.gov.uk/dataset/subjective-personal-well-being-borough https://data.london.gov.uk/dataset/household-waste-recycling-rates-borough https://data.london.gov.uk/dataset/earnings-place-residence-borough https://data.london.gov.uk/dataset/recorded_crime_summary https://data.london.gov.uk/dataset/jobs-and-job-density-borough https://data.london.gov.uk/dataset/ons-mid-year-population-estimates-custom-age-tables

Cover photo by Frans Ruiter from Unsplash

Inspiration

The dataset lends itself for extensive exploratory data analysis. It could also be a great supervised learning regression problem to predict house price changes of different boroughs over time.

Median age

Average age for older people in ordinary housing with home care, years. Persons who have only security alarms, food distribution or less than two hours of home care per month have been excluded. Up to 2020, an average of the months of the year, from 2021 a municipality-individual median. Data is available according to gender breakdown.

About this dataset

Context

The dataset tabulates the population of Red House town by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Red House town. The dataset can be utilized to understand the population distribution of Red House town by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Red House town. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Red House town.

Key observations

Largest age group (population): Male # 40-44 years (5) | Female # 40-44 years (5). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Red House town population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Red House town is shown in the following column.
• Population (Female): The female population in the Red House town is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Red House town for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Red House town Population by Gender. You can refer the same here

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.

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in New Home. Based on the latest 2017-2021 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in New Home. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2021

In terms of income distribution across age cohorts, in New Home, the median household income stands at $113,496 for householders within the 25 to 44 years age group, followed by $67,557 for the 45 to 64 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $35,901.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific age group

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New Home median household income by age. You can refer the same here

Between 86 percent and 91 percent of homebuyers in the United States purchased their homes through a real estate agent or broker, depending on their age group, in 2024. Homebuyers in the age group of 79 to 99 were most likely to buy a house through an agent or broker. On the other hand, the oldest homebuyers were most likely to buy their new home from the previous owner directly.