As of the end of the fiscal year 2022, the average age of licensed individual real estate brokers who operated their own business was **** years. This reflected the large share of individual real estate brokers aged between 70 and 79 years.

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.

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.

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Concerns housing values in suburbs of Boston.

1. Number of Instances: 506

2. Number of Attributes: 13 continuous attributes (including "class" attribute "MEDV"), 1 binary-valued attribute.

3. Attribute Information:

   1. CRIM per capita crime rate by town
   2. ZN proportion of residential land zoned for lots over 25,000 sq.ft.
   3. INDUS proportion of non-retail business acres per town
   4. CHAS Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)
   5. NOX nitric oxides concentration (parts per 10 million)
   6. RM average number of rooms per dwelling
   7. AGE proportion of owner-occupied units built prior to 1940
   8. DIS weighted distances to five Boston employment centres
   9. RAD index of accessibility to radial highways
   10. TAX full-value property-tax rate per $10,000
   11. PTRATIO pupil-teacher ratio by town
   12. B 1000(Bk - 0.63)^2 where Bk is the proportion of blacks by town
   13. LSTAT % lower status of the population
   14. MEDV Median value of owner-occupied homes in $1000's

4. Missing Attribute Values: None.

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 Median Sales Price of Existing Homes (HOSMEDUSM052N) from May 2024 to May 2025 about sales, median, housing, and USA.

Graph and download economic data for Average Sales Price of Houses Sold for the United States (ASPUS) from Q1 1963 to Q1 2025 about sales, housing, and USA.

The average market value of homes of new mortgage borrowers in Sweden in 2022 was highest among debtors in the age group between 30 and 50 years. The average value amounted to over 4.35 million Swedish kronor for this age group, whereas borrowers in the age group of 18 to 30 years owned homes valued at on average 2.61 million Swedish kronor. The market value also varied in different areas, with Stockholm recording the highest figure.

The majority of home buyers in the United States in 2024 across all age groups purchased a home between ***** and ***** square feet in size. ** percent of the young millennials (26 to 34 years old) and ** percent of the silent generation (79 to 99 years old) purchased a home about the same feet in size.

The mean and median age of long stay residents, as well as at the time of admission and discharge, by main client group.

This map uses a two-color thematic shading to emphasize where areas experience the least to the most affordable housing across the US. This web map is part of the How Affordable is the American Dream story map.

Esri’s Housing Affordability Index (HAI) is a powerful tool to analyze local real estate markets. Esri’s housing affordability index measures the financial ability of a typical household to purchase an existing home in an area. A HAI of 100 represents an area that on average has sufficient household income to qualify for a loan on a home valued at the median home price. An index greater than 100 suggests homes are easily afforded by the average area resident. A HAI less than 100 suggests that homes are less affordable. The housing affordability index is not applicable in areas with no households or in predominantly rental markets . Esri’s home value estimates cover owner-occupied homes only. For a full demographic analysis of US growth refer to Esri's Trending in 2017: The Selectivity of Growth.

The pop-up is configured to show the following 2017 demographics for each County and ZIP Code:

Total Households 2010-17 Annual Pop Change Median Age Percent Owner-Occupied Housing Units Median Household Income Median Home Value Housing Affordability Index Share of Income to Mortgage

The average number of years care home residents aged 65 years and over are expected to live beyond their current age in England and Wales. Classified as Experimental Statistics.

Graph and download economic data for Households; Owners' Equity in Real Estate, Level (OEHRENWBSHNO) from Q4 1945 to Q1 2025 about net worth, balance sheet, nonprofit organizations, equity, real estate, Net, households, and USA.

The average monthly stock per estate agent in the United Kingdom (UK) peaked in the end of 2020. As home buyer sentiment strengthened and the demand for housing rose, the available inventory decreased steadily and reached ** properties per agent in January 2022.

Existing Home Sales in the United States increased to 4030 Thousand in May from 4000 Thousand in April of 2025. This dataset provides the latest reported value for - United States Existing Home Sales - 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 Housing Inventory: Active Listing Count in the United States (ACTLISCOUUS) from Jul 2016 to Jun 2025 about active listing, listing, and USA.

US Census Bureau American Community Survey 2013-2017 Estimates in the Keys the Valley Region for Population, Households, Tenure, Cost Burden, Poverty, and Age of Housing Stock.

The American Community Survey (ACS) is a nationwide survey designed to provide communities with reliable and timely social, economic, housing, and demographic data every year. Because the ACS is based on a sample, rather than all housing units and people, ACS estimates have a degree of uncertainty associated with them, called sampling error. In general, the larger the sample, the smaller the level of sampling error. Data associated with a small town will have a greater degree of error than data associated with an entire county. To help users understand the impact of sampling error on data reliability, the Census Bureau provides a “margin of error” for each published ACS estimate. The margin of error, combined with the ACS estimate, give users a range of values within which the actual “real-world” value is likely to fall.

Single-year and multiyear estimates from the ACS are all “period” estimates derived from a sample collected over a period of time, as opposed to “point-in-time” estimates such as those from past decennial censuses. For example, the 2000 Census “long form” sampled the resident U.S. population as of April 1, 2000. The estimates here were derived from a sample collected over time from 2013-2017.

Data Dictionary - Population, Households, Tenure, Cost Burden, Poverty, Age of Housing Stock

·
Population: Total Population (B01003)

·
Households: Total number of households (B25003)

·
OwnHH: Total number of owner-occupied households (B25003)

·
RentHH: Total number of renter-occupied households (B25003)

·
TotalU: Total number of housing units (B25001)

·
VacantU: Total number of vacant units (B25004)

·
SeasRecOcU: Total number of Seasonal/Recreational/Occasionally Occupied Units (B25004)

·
ForSale: Total number of units currently for sale (B25004)

·
ForRent: Total number of units currently for rent (B25004)

·
MedianHI: Median Household Income (B25119)

·
OwnHH3049: Total number of owner-occupied households spending 30-49% of their income on housing costs. (B25095)

·
POwnHH3049: Percentage of owner-occupied households spending 30-49% of their income on housing costs. (B25095)

·
OwnHH50: Total number of severely cost-burdened owner-occupied households – those spending 50% or more of their income on housing costs. (B25095)

·
POwnHH50: Percentage of severely cost-burdened owner-occupied households – those spending 50% or more of their income on housing costs. (B25095)

·
OwnHH_CB: Total number of owner-occupied, cost-burdened households - those who spend 30% or more of their income on housing costs. (B25095)

·
POwnHH_CB: Percentage of owner-occupied, cost-burdened households - those who spend 30% or more of their income on housing costs. (B25095)

·
RenHH3049: Total number of renter-occupied households spending 30-49% of their income on housing costs. (B25070)

·
PRenHH3049: Percentage of renter-occupied households spending 30-49% of their income on housing costs. (B25070)

·
RenHH50: Total number of severely cost-burdened renter-occupied households – those spending 50% or more of their income on housing costs. (B25070)

·
PRenHH50: Percentage of severely cost-burdened renter-occupied households – those spending 50% or more of their income on housing costs. (B25070)

·
RenHH_CB: Total number of renter-occupied, cost-burdened households - those who spend 30% or more of their income on housing costs. (B25070)

·
PRenHH_CB: Percentage of renter-occupied, cost-burdened households - those who spend 30% or more of their income on housing costs. (B25070)

·
Poverty: Population below poverty level. (B17001)

·
PPoverty: Percentage of population below poverty level. Note poverty status (above or below) is not determined for the entire population. (B17001)

·
MYearBuilt: Median structure year of construction. (B25035)

Homes for the elderly and disabled are an essential part of the healthcare system. Due to increasing life expectancy and the growing proportion of senior citizens in the population, the demand for such facilities is also increasing. In the last five years, turnover in the sector has risen by an average of 4% per year. However, the dynamic cost trend has recently placed a heavy burden on the industry's earnings situation and caused financial difficulties for many industry players, increasing the risk of insolvency. Operators were faced with rising costs for energy, accommodation and catering, which were not sufficiently refinanced by the cost bearers.Additional economic challenges are posed by rising personnel costs. These will continue to rise in the current year. The parties to the collective agreement have agreed on further salary increases in 2024 in addition to an inflation adjustment. In addition, the switch to the new staff assessment procedure means that specialised and auxiliary staff will be included in the care rates. All of this is compounded by a worsening staff shortage, which is leading to lower capacity utilisation. In order to avoid getting into financial difficulties, the additional costs are largely passed on to the residents, while the care insurance companies' fees are barely adjusted. A decline in turnover of 0.2% compared to the previous year is expected for 2024, meaning that total turnover will amount to 8.6 billion euros. One growth driver in the sector is the provision of alternative forms of living. Assisted living facilities have become increasingly popular in recent years. The high demand for this form of living means that flats designed for this purpose are being built as part of almost all new construction projects in the sector.For the next five years, IBISWorld expects an average annual growth rate of 2.6%, which means that turnover is likely to reach 9.8 billion euros in 2029. There is growth potential for the industry in the areas of sustainability, energy, digitalisation, innovation and connected living. The positive development is likely to attract numerous new operators to the sector, meaning that the number of companies active on the market is expected to increase by an average of 1.5% per year until 2029. As competition intensifies, there will be an even greater focus on maximising profits and cutting costs, which may have a negative impact on the quality of care.