About ** percent of home buyers in the United States in 2021 purchased homes that cost ******* U.S. dollars or more. The share of home buyers generally reduced as the house prices decreased. The largest share of purchases fell in the ******* to ******* and ******* to ******* price classes, which was below the national average sales price for existing homes.

Key information about House Prices Growth

• US house prices grew 3.3% YoY in Sep 2025, following an increase of 4.1% YoY in the previous quarter.
• YoY growth data is updated quarterly, available from Mar 1992 to Sep 2025, with an average growth rate of -12.4%.
• House price data reached an all-time high of 17.7% in Sep 2021 and a record low of -12.4% in Dec 2008.

CEIC calculates House Prices Growth from quarterly House Price Index. Federal Housing Finance Agency provides House Price Index with base January 1991=100.

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.

In 2022, house price growth in the UK slowed, after a period of decade-long increase. Nevertheless, in June 2025, prices reached a new peak, with the average home costing ******* British pounds. This figure refers to all property types, including detached, semi-detached, terraced houses, and flats and maisonettes. Compared to other European countries, the UK had some of the highest house prices. How have UK house prices increased over the last 10 years? Property prices have risen dramatically over the past decade. According to the UK house price index, the average house price has grown by over ** percent since 2015. This price development has led to the gap between the cost of buying and renting a property to close. In 2023, buying a three-bedroom house in the UK was no longer more affordable than renting one. Consequently, Brits have become more likely to rent longer and push off making a house purchase until they have saved up enough for a down payment and achieved the financial stability required to make the step. What caused the recent fluctuations in house prices? House prices are affected by multiple factors, such as mortgage rates, supply, and demand on the market. For nearly a decade, the UK experienced uninterrupted house price growth as a result of strong demand and a chronic undersupply. Homebuyers who purchased a property at the peak of the housing boom in July 2022 paid ** percent more compared to what they would have paid a year before. Additionally, 2022 saw the most dramatic increase in mortgage rates in recent history. Between December 2021 and December 2022, the **-year fixed mortgage rate doubled, adding further strain to prospective homebuyers. As a result, the market cooled, leading to a correction in pricing.

Data description

The House Price Index (HPI) measures inflation in the residential property market. The HPI captures price changes of all types of dwellings purchased by households (flats, detached houses, terraced houses, etc.). Only transacted dwellings are considered, self-build dwellings are excluded. The land component of the dwelling is included.

The HPI is available for all European Union Member States (except Greece), the United Kingdom (only until the third quarter of 2020), Iceland, Norway, Switzerland and Turkey. In addition to the individual country series, Eurostat produces indices for the euro area and for the European Union (EU). As from the first quarter of 2020 onwards, the EU HPI aggregate no longer includes the HPI from the United Kingdom.

The national HPIs are produced by National Statistical Offices (NSIs) and the European aggregates by Eurostat, by combining the national indices. The data released quarterly on Eurostat's website include the national and European price indices, weights and their rates of change.

In order to provide a more comprehensive picture of the housing market, house sales indicators are also provided. Available house sales indicators refer to the total number and value of dwellings transactions at national level where the purchaser is a household. Eurostat publishes in its database a quarterly and annual house sales index as well as quarterly and annual rates of change.

Statistical concepts and definitions

The HPI is based on market prices of dwellings. Non-marketed prices are ruled out from the scope of this indicator. Self-build dwellings, dwellings purchased by sitting tenants at discount prices or dwellings transacted between family members are out of the scope of the indicator. It covers all monetary dwelling transactions regardless of its type (e.g., carried out through a cash purchase or financed through a mortgage loan).

The HPI measures the price developments of all dwellings purchased by households, regardless of which institutional sector they were bought from and the purpose of the purchase. As such, a dwelling bought by a household for a purpose other than owner-occupancy (e.g., for being rented out) is within the scope of the indicator. The HPI includes all purchases of new and existing dwellings, including those of dwellings transacted between households.

The number and value of house sales cover the total annual value of dwellings transactions at national level where the purchaser is a household. Transactions between households are included. Transfers in dwellings due to donations and inheritances are excluded.

The house sales value reflect the prices paid by household buyers and include both the price of land and the price of the structure of the dwelling. The prices for new dwellings include VAT. Other costs related to the acquisition of the dwelling (e.g., notary fees, registration fees, real estate agency commission, bank fees) are excluded.

Statistical unit

Each published index or rate of change refers to transacted dwellings purchased at market prices by the household sector in the corresponding geographical entity. All transacted dwellings are covered, regardless of which institutional sector they were bought from and of the purchase purpose.

more: https://ec.europa.eu/eurostat/cache/metadata/en/prc_hpi_inx_esms.htm

House Price Index YoY in the United States decreased to 1.70 percent in September from 2.40 percent in August of 2025. This dataset includes a chart with historical data for the United States FHFA House Price Index YoY.

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Description:

A simple yet challenging project, to predict the housing price based on certain factors like house area, bedrooms, furnished, nearness to mainroad, etc. The dataset is small yet, it's complexity arises due to the fact that it has strong multicollinearity. Can you overcome these obstacles & build a decent predictive model?

Acknowledgement:

Harrison, D. and Rubinfeld, D.L. (1978) Hedonic prices and the demand for clean air. J. Environ. Economics and Management 5, 81–102. Belsley D.A., Kuh, E. and Welsch, R.E. (1980) Regression Diagnostics. Identifying Influential Data and Sources of Collinearity. New York: Wiley.

Objective:

• Understand the Dataset & cleanup (if required).
• Build Regression models to predict the sales w.r.t a single & multiple feature.
• Also evaluate the models & compare thier respective scores like R2, RMSE, etc.

The U.S. housing market has slowed, after ** consecutive years of rising home prices. In 2021, house prices surged by an unprecedented ** percent, marking the highest increase on record. However, the market has since cooled, with the Freddie Mac House Price Index showing more modest growth between 2022 and 2024. In 2024, home prices increased by *** percent. That was lower than the long-term average of *** percent since 1990. Impact of mortgage rates on homebuying The recent cooling in the housing market can be partly attributed to rising mortgage rates. After reaching a record low of **** percent in 2021, the average annual rate on a 30-year fixed-rate mortgage more than doubled in 2023. This significant increase has made homeownership less affordable for many potential buyers, contributing to a substantial decline in home sales. Despite these challenges, forecasts suggest a potential recovery in the coming years. How much does it cost to buy a house in the U.S.? In 2023, the median sales price of an existing single-family home reached a record high of over ******* U.S. dollars. Newly built homes were even pricier, despite a slight decline in the median sales price in 2023. Naturally, home prices continue to vary significantly across the country, with West Virginia being the most affordable state for homebuyers.

Housing Index in Hong Kong increased to 143.46 points in November 23 from 142.49 points in the previous week. This dataset provides - Hong Kong House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

View monthly updates and historical trends for US House Price Index. from United States. Source: Federal Housing Finance Agency. Track economic data with …

Key information about House Prices Growth

• Belarus house prices dropped 2.5% YoY in Dec 2021, following a decrease of 0.5% YoY in the previous quarter.
• YoY growth data is updated quarterly, available from Mar 2010 to Dec 2021, with an average growth rate of 14.6%.
• House price data reached an all-time high of 169.0% in Dec 2011 and a record low of -12.1% in Mar 2017.

CEIC calculates House Prices Growth from quarterly House Price Index. The National Statistical Committee of the Republic of Belarus provides House Price Index with base Same Quarter Previous Year=100.

House Price Index YoY in Ireland increased to 7.60 percent in September from 7.50 percent in August of 2025. This dataset includes a chart with historical data for Ireland Residential Property Prices YoY.

This is the median house price for residential property sales (all dwellings sold and registered) in a given period of four consecutive quarters, in the area. They are calculated using open data from the HM Land Registry (LR), a source of comprehensive record-level administrative data on property transactions.

They are updated twice a year, in spring and autumn. The LR Price Paid data are comprehensive in that they capture changes of ownership for individual residential properties which have sold for full market value and cover both cash sales and those involving a mortgage.

The median is the value determined by putting all the house sales for a given year, area and type in order of price and then selecting the price of the house sale which falls in the middle.

Note that a transaction occurs when a change of freeholder or leaseholder takes place regardless of the amount of money involved, and a property can transact more than once in the time period. The LR records the actual price for which the property changed hands. This will usually be an accurate reflection of the market value for the individual property, but it is not always the case.

In order to generate statistics that more accurately reflect market values, the LR has excluded records of houses that were not sold at market value from the dataset. The remaining data are considered a good reflection of market values at the time of the transaction.

The LR Price Paid data are not adjusted to reflect the mix of houses in a given area. Fluctuations in the types of house that are sold in that area can cause differences between the median transactional value of houses and the overall market value of houses.

Therefore these statistics differ from the new UK House Price Index (HPI) which reports mix-adjusted average house prices and house price indices.

If, for a given year, house type and area there were fewer than 5 sales records in the LR Price Paid data, the house price statistics are not reported.

Data is Powered by LG Inform Plus and automatically checked for new data on the 4th of each month and shows MSOAs (Middle Layer Super Output Areas) at the 2021 Census Geography.

Residential house prices across the capital cities in Australia increased by 23.7 percent through the year to December 2021. Housing affordability in Australia remains a highly political topic with many prospective home buyers feeling priced out of the market.

Median price paid for residential property in England and Wales, for all property types by lower layer super output area. Annual data..

Key information about House Prices Growth

• Czech Republic house prices grew 10.5% YoY in Jun 2025, following an increase of 9.9% YoY in the previous quarter.
• YoY growth data is updated quarterly, available from Mar 2006 to Jun 2025, with an average growth rate of 4.1%.
• House price data reached an all-time high of 25.8% in Dec 2021 and a record low of -6.8% in Dec 2009.

CEIC calculates quarterly House Prices Growth from quarterly House Price Index. Eurostat provides House Price Index with base 2015=100. House Prices Growth prior to Q1 2009 is calculated from Real Estate Price Index with base 2005=100, provided by Czech Statistical Office.

In 2021, Allegheny County Economic Development (ACED), in partnership with Urban Redevelopment Authority of Pittsburgh(URA), completed the a Market Value Analysis (MVA) for Allegheny County. This analysis services as both an update to previous MVA’s commissioned separately by ACED and the URA and combines the MVA for the whole of Allegheny County (inclusive of the City of Pittsburgh). The MVA is a unique tool for characterizing markets because it creates an internally referenced index of a municipality’s residential real estate market. It identifies areas that are the highest demand markets as well as areas of greatest distress, and the various markets types between. The MVA offers insight into the variation in market strength and weakness within and between traditional community boundaries because it uses Census block groups as the unit of analysis. Where market types abut each other on the map becomes instructive about the potential direction of market change, and ultimately, the appropriateness of types of investment or intervention strategies. This MVA utilized data that helps to define the local real estate market. The data used covers the 2017-2019 period, and data used in the analysis includes: Residential Real Estate Sales Mortgage Foreclosures Residential Vacancy Parcel Year Built Parcel Condition Building Violations Owner Occupancy Subsidized Housing Units The MVA uses a statistical technique known as cluster analysis, forming groups of areas (i.e., block groups) that are similar along the MVA descriptors, noted above. The goal is to form groups within which there is a similarity of characteristics within each group, but each group itself different from the others. Using this technique, the MVA condenses vast amounts of data for the universe of all properties to a manageable, meaningful typology of market types that can inform area-appropriate programs and decisions regarding the allocation of resources. Please refer to the presentation and executive summary for more information about the data, methodology, and findings.

Graph and download economic data for Median Sales Price of Houses Sold for the United States (MSPUS) from Q1 1963 to Q2 2025 about sales, median, housing, and USA.