Geneva stands out as Europe's most expensive city for apartment purchases in early 2025, with prices reaching a staggering 15,720 euros per square meter. This Swiss city's real estate market dwarfs even high-cost locations like Zurich and London, highlighting the extreme disparities in housing affordability across the continent. The stark contrast between Geneva and more affordable cities like Nantes, France, where the price was 3,700 euros per square meter, underscores the complex factors influencing urban property markets in Europe. Rental market dynamics and affordability challenges While purchase prices vary widely, rental markets across Europe also show significant differences. London maintained its position as the continent's priciest city for apartment rentals in 2023, with the average monthly costs for a rental apartment amounting to 36.1 euros per square meter. This figure is double the rent in Lisbon, Portugal or Madrid, Spain, and substantially higher than in other major capitals like Paris and Berlin. The disparity in rental costs reflects broader economic trends, housing policies, and the intricate balance of supply and demand in urban centers. Economic factors influencing housing costs The European housing market is influenced by various economic factors, including inflation and energy costs. As of April 2025, the European Union's inflation rate stood at 2.4 percent, with significant variations among member states. Romania experienced the highest inflation at 4.9 percent, while France and Cyprus maintained lower rates. These economic pressures, coupled with rising energy costs, contribute to the overall cost of living and housing affordability across Europe. The volatility in electricity prices, particularly in countries like Italy where rates are projected to reach 153.83 euros per megawatt hour by February 2025, further impacts housing-related expenses for both homeowners and renters.

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

Key information about House Prices Growth

• US house prices grew 5.2% YoY in Dec 2024, following an increase of 5.4% YoY in the previous quarter.
• YoY growth data is updated quarterly, available from Mar 1992 to Dec 2024, with an average growth rate of 5.4%.
• House price data reached an all-time high of 17.7% in Sep 2021 and a record low of -12.4% in Dec 2008.

Mexico's housing market demonstrates significant regional price variations, with Mexico City emerging as the most expensive area for residential property in the second quarter of 2025. The capital city's average house price of 3.87 million Mexican pesos far exceeds the national average of 1.86 million pesos, highlighting the stark contrast in property values across the country. This disparity reflects broader economic and demographic trends shaping Mexico's real estate landscape. Sustained growth in housing prices The Mexican housing market has experienced substantial growth over the past decade, with home prices more than doubling since 2010. By the second quarter of 2025, the nominal house price index reached 247 points, representing a 147 percent increase from the baseline year. Even when adjusted for inflation, the real house price index showed a notable 40 percent growth, underscoring the market's resilience and attractiveness to investors. The mortgage market is dominated by three main player types: Infonavit, Fovissste, and commercial banks including Sofomes. In 2023, Infonavit, a scheme by Mexico's National Housing Fund Institute which provides lending to workers in the formal sector, was responsible for the majority of mortgages granted to individuals. Challenges in mortgage lending Despite the overall growth in housing prices, Mexico's mortgage market has faced challenges in recent years. The number of new mortgage loans granted has declined over the past decade, falling by approximately 200,000 loans between 2008 and 2023. This decrease in lending activity may be attributed to various factors, including economic uncertainties and changing consumer preferences. The state of Mexico, which is home to 13 percent of the country's population, likely plays a significant role in shaping these trends given its large demographic influence on the national housing market.

Single Family Home Prices in the United States decreased to 422600 USD in August from 425700 USD in July of 2025. This dataset provides - United States Existing Single Family Home Prices- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Out of a total of *** million housing units in New York City in 2021, approximately ******* homes had housing costs between ** and ** percent of the household budget. New York City is notoriously known for its shortage of affordable housing: Overall, for a large percentage of New York City residents, housing costs exceeded ** percent.

Graph and download economic data for All-Transactions House Price Index for San Francisco-San Mateo-Redwood City, CA (MSAD) (ATNHPIUS41884Q) from Q3 1975 to Q2 2025 about San Francisco, appraisers, CA, HPI, housing, price index, indexes, price, and USA.

The dataset contains year-, quarter- and city-wise data on the Housing Price Index in Indian and among its various cities such as Ahmedabad, Bangalore, Chennai, Delhi, Jaipur, Kanpur, Kochi, Kolkata, Lucknow, Mumbai, etc.

Average House Prices in the United States increased to 534100 USD in August from 478200 USD in July of 2025. This dataset includes a chart with historical data for the United States New Home Average Sales Price.

Graph and download economic data for All-Transactions House Price Index for Baltimore city, MD (ATNHPIUS24510A) from 1975 to 2024 about Baltimore City, MD; Baltimore; MD; HPI; housing; price index; indexes; price; and USA.

Task Description: Real Estate Price Prediction

This task involves predicting the price of real estate properties based on various features that influence the value of a property. The dataset contains several attributes of real estate properties such as square footage, the number of bedrooms, bathrooms, floors, the year the property was built, whether the property has a garden or pool, the size of the garage, the location score, and the distance from the city center.

The goal is to build a regression model that can predict the Price of a property based on the provided features.

Dataset Columns:

ID: A unique identifier for each property.

Square_Feet: The area of the property in square meters.

Num_Bedrooms: The number of bedrooms in the property.

Num_Bathrooms: The number of bathrooms in the property.

Num_Floors: The number of floors in the property.

Year_Built: The year the property was built.

Has_Garden: Indicates whether the property has a garden (1 for yes, 0 for no).

Has_Pool: Indicates whether the property has a pool (1 for yes, 0 for no).

Garage_Size: The size of the garage in square meters.

Location_Score: A score from 0 to 10 indicating the quality of the neighborhood (higher scores indicate better neighborhoods).

Distance_to_Center: The distance from the property to the city center in kilometers.

Price: The target variable that represents the price of the property. This is the value we aim to predict.

Objective: The goal of this task is to develop a regression model that predicts the Price of a real estate property using the other features as inputs. The model should be able to learn the relationship between these features and the price, providing an accurate prediction for unseen data.

VITAL SIGNS INDICATOR Home Prices (EC7)

FULL MEASURE NAME Home Prices

LAST UPDATED August 2019

DESCRIPTION Home prices refer to the cost of purchasing one’s own house or condominium. While a significant share of residents may choose to rent, home prices represent a primary driver of housing affordability in a given region, county or city.

DATA SOURCE Zillow Median Sale Price (1997-2018) http://www.zillow.com/research/data/

Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1997-2018; specific to each metro area) http://data.bls.gov

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Median housing price estimates for the region, counties, cities, and zip code come from analysis of individual home sales by Zillow. The median sale price is the price separating the higher half of the sales from the lower half. In other words, 50 percent of home sales are below or above the median value. Zillow defines all homes as single-family residential, condominium, and co-operative homes with a county record. Single-family residences are detached, which means the home is an individual structure with its own lot. Condominiums are units that you own in a multi-unit complex, such as an apartment building. Co-operative homes are slightly different from condominiums where the homeowners own shares in the corporation that owns the building, not the actual units themselves.

For metropolitan area comparison values, the Bay Area metro area’s median home sale price is the population-weighted average of the nine counties’ median home prices. Home sales prices are not reliably available for Houston, because Texas is a non-disclosure state. For more information on non-disclosure states, see: http://www.zillow.com/blog/chronicles-of-data-collection-ii-non-disclosure-states-3783/

Inflation-adjusted data are presented to illustrate how home prices have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself.

Displacement risk indicator showing how many households within the specified groups are facing either housing cost burden (contributing more than 30% of monthly income toward housing costs) or severe housing cost burden (contributing more than 50% of monthly income toward housing costs).

Housing Index in China decreased by 2.50 percent in August from -2.80 percent in July of 2025. This dataset provides the latest reported value for - China Newly Built House Prices YoY Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Average House Price: Mexico City data was reported at 3,087,111.000 MXN in Mar 2019. This records an increase from the previous number of 1,479,381.000 MXN for Dec 2018. Average House Price: Mexico City data is updated quarterly, averaging 1,462,320.000 MXN from Dec 2014 (Median) to Mar 2019, with 18 observations. The data reached an all-time high of 3,087,111.000 MXN in Mar 2019 and a record low of 1,352,679.000 MXN in Dec 2014. Average House Price: Mexico City data remains active status in CEIC and is reported by Federal Mortgage Society. The data is categorized under Global Database’s Mexico – Table MX.EB005: Average House Price.

Poland - Median of the housing cost burden distribution: Cities was 13.50% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Poland - Median of the housing cost burden distribution: Cities - last updated from the EUROSTAT on October of 2025. Historically, Poland - Median of the housing cost burden distribution: Cities reached a record high of 20.40% in December of 2014 and a record low of 13.50% in December of 2024.

The UK housing market continued to show significant regional variations in 2025, with London maintaining its position as the most expensive city for homebuyers. The average house price in the capital stood at ******* British pounds in February, nearly double the national average. However, the market dynamics are shifting, with London experiencing only a modest *** percent annual increase, while other cities like Belfast and Liverpool saw more substantial growth of over **** percent respectively. Affordability challenges and market slowdown Despite the continued price growth in many cities, the UK housing market is facing headwinds. The affordability of mortgage repayments has become the biggest barrier to property purchases, with the majority of the respondents in a recent survey citing it as their main challenge. Moreover, a rising share of Brits have reported affordability as a challenge since 2021, reflecting the impact of rising house prices and higher mortgage rates. The market slowdown is evident in the declining housing transaction volumes, which have plummeted since 2021. European context The stark price differences are mirrored in the broader European context. While London boasts some of the highest property prices among European cities, a comparison of the average transaction price for new homes in different European countries shows a different picture. In 2023, the highest prices were found in Austria, Germany, and France.

The year-end value of the S&P Case Shiller National Home Price Index amounted to 321.45 in 2024. The index value was equal to 100 as of January 2000, so if the index value is equal to 130 in a given year, for example, it means that the house prices increased by 30 percent since 2000. S&P/Case Shiller U.S. home indices – additional informationThe S&P Case Shiller National Home Price Index is calculated on a monthly basis and is based on the prices of single-family homes in nine U.S. Census divisions: New England, Middle Atlantic, East North Central, West North Central, South Atlantic, East South Central, West South Central, Mountain and Pacific. The index is the leading indicator of the American housing market and one of the indicators of the state of the broader economy. The index illustrates the trend of home prices and can be helpful during house purchase decisions. When house prices are rising, a house buyer might want to speed up the house purchase decision as the transaction costs can be much higher in the future. The S&P Case Shiller National Home Price Index has been on the rise since 2011.The S&P Case Shiller National Home Price Index is one of the indices included in the S&P/Case-Shiller Home Price Index Series. Other indices are the S&P/Case Shiller 20-City Composite Home Price Index, the S&P/Case Shiller 10-City Composite Home Price Index and twenty city composite indices.

Avg Housing Price: Free Market: Less than 5 Years Old: Badajoz data was reported at 1,155.800 EUR/sq m in Mar 2018. This records an increase from the previous number of 1,138.600 EUR/sq m for Mar 2016. Avg Housing Price: Free Market: Less than 5 Years Old: Badajoz data is updated quarterly, averaging 1,385.700 EUR/sq m from Mar 2010 (Median) to Mar 2018, with 19 observations. The data reached an all-time high of 1,617.400 EUR/sq m in Jun 2010 and a record low of 1,097.500 EUR/sq m in Dec 2013. Avg Housing Price: Free Market: Less than 5 Years Old: Badajoz data remains active status in CEIC and is reported by Ministry of Public Works. The data is categorized under Global Database’s Spain – Table ES.P003: Housing Prices: Free Market: by Region and Major City.

Germany - Housing cost overburden rate: Cities was 13.10% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Germany - Housing cost overburden rate: Cities - last updated from the EUROSTAT on October of 2025. Historically, Germany - Housing cost overburden rate: Cities reached a record high of 19.80% in December of 2012 and a record low of 11.40% in December of 2020.