The travel time data on this map is modeled from a 2005 transit network. The home values are as of 2000 and are expressed in year 2000 dollars. The home value estimates were created by the Association of Bay Area Governements by combining ParcelQuest real estate transaction data and real estate tax assessment data. This information can be generated for any address in the region using an interactive mapping tool available under Maps at onebayarea.org/maps.htm (Note - this tool is no longer available).

This dataset includes the listing prices for the sale of properties (mostly houses) in Ontario. They are obtained for a short period of time in July 2016 and include the following fields: - Price in dollars - Address of the property - Latitude and Longitude of the address obtained by using Google Geocoding service - Area Name of the property obtained by using Google Geocoding service

This dataset will provide a good starting point for analyzing the inflated housing market in Canada although it does not include time related information. Initially, it is intended to draw an enhanced interactive heatmap of the house prices for different neighborhoods (areas)

However, if there is enough interest, there will be more information added as newer versions to this dataset. Some of those information will include more details on the property as well as time related information on the price (changes).

This is a somehow related articles about the real estate prices in Ontario: http://www.canadianbusiness.com/blogs-and-comment/check-out-this-heat-map-of-toronto-real-estate-prices/

I am also inspired by this dataset which was provided for King County https://www.kaggle.com/harlfoxem/housesalesprediction

House prices grew year-on-year in most states in the U.S. in the first quarter of 2025. Hawaii was the only exception, with a decline of **** percent. The annual appreciation for single-family housing in the U.S. was **** percent, while in Rhode Island—the state where homes appreciated the most—the increase was ******percent. How have home prices developed in recent years? House price growth in the U.S. has been going strong for years. In 2025, the median sales price of a single-family home exceeded ******* U.S. dollars, up from ******* U.S. dollars five years ago. One of the factors driving house prices was the cost of credit. The record-low federal funds effective rate allowed mortgage lenders to set mortgage interest rates as low as *** percent. With interest rates on the rise, home buying has also slowed, causing fluctuations in house prices. Why are house prices growing? Many markets in the U.S. are overheated because supply has not been able to keep up with demand. How many homes enter the housing market depends on the construction output, whereas the availability of existing homes for purchase depends on many other factors, such as the willingness of owners to sell. Furthermore, growing investor appetite in the housing sector means that prospective homebuyers have some extra competition to worry about. In certain metros, for example, the share of homes bought by investors exceeded ** percent in 2025.

Mapping spatial processes at a small scale is a challenge when observed data are not abundant. The article examines the residential housing market in Fort Worth, Texas, and builds price indices at the inter- and intra-neighborhood levels. To accomplish our objectives, we initially model price variability in the joint space–time continuum. We then use geostatistics to predict and map monthly housing prices across the area of interest over a period of 4 years. For this analysis, we introduce the Bayesian maximum entropy (BME) method into real estate research. We use BME because it rigorously integrates uncertain or secondary soft data, which are needed to build the price indices. The soft data in our analysis are property tax values, which are plentiful, publicly available, and highly correlated with transaction prices. The results demonstrate how the use of the soft data provides the ability to map house prices within a small areal unit such as a subdivision or neighborhood.

The median home sales price is the middle value of the prices for which homes are sold (both market and private transactions) within a calendar year. The median value is used as opposed to the average so that both extremely high and extremely low prices do not distort the prices for which homes are sold. This measure does not take into account the assessed value of a property.Source: First American Real Estate Solutions (FARES) and RBIntel (2022-forward)Years Available: 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2022, 2023

The average transaction price of new housing in Europe was the highest in Norway, whereas existing homes were the most expensive in Austria. Since there is no central body that collects and tracks transaction activity or house prices across the whole continent or the European Union, not all countries are included. To compile the ranking, the source weighed the transaction prices of residential properties in the most important cities in each country based on data from their national offices. For example, in Germany, the cities included were Munich, Hamburg, Frankfurt, and Berlin. House prices have been soaring, with Sweden topping the ranking Considering the RHPI of houses in Europe (the price index in real terms, which measures price changes of single-family properties adjusted for the impact of inflation), however, the picture changes. Sweden, Luxembourg and Norway top this ranking, meaning residential property prices have surged the most in these countries. Real values were calculated using the so-called Personal Consumption Expenditure Deflator (PCE), This PCE uses both consumer prices as well as consumer expenditures, like medical and health care expenses paid by employers. It is meant to show how expensive housing is compared to the way of living in a country. Home ownership highest in Eastern Europe The home ownership rate in Europe varied from country to country. In 2020, roughly half of all homes in Germany were owner-occupied whereas home ownership was at nearly ** percent in Romania or around ** percent in Slovakia and Lithuania. These numbers were considerably higher than in France or Italy, where homeowners made up ** percent and ** percent of their respective populations.For more information on the topic of property in Europe, visit the following pages as a starting point for your research: real estate investments in Europe and residential real estate in Europe.

Portugal, Canada, and the United States were the countries with the highest house price to income ratio in 2024. In all three countries, the index exceeded 130 index points, while the average for all OECD countries stood at 116.2 index points. The index measures the development of housing affordability and is calculated by dividing nominal house price by nominal disposable income per head, with 2015 set as a base year when the index amounted to 100. An index value of 120, for example, would mean that house price growth has outpaced income growth by 20 percent since 2015. How have house prices worldwide changed since the COVID-19 pandemic? House prices started to rise gradually after the global financial crisis (2007–2008), but this trend accelerated with the pandemic. The countries with advanced economies, which usually have mature housing markets, experienced stronger growth than countries with emerging economies. Real house price growth (accounting for inflation) peaked in 2022 and has since lost some of the gain. Although, many countries experienced a decline in house prices, the global house price index shows that property prices in 2023 were still substantially higher than before COVID-19. Renting vs. buying In the past, house prices have grown faster than rents. However, the home affordability has been declining notably, with a direct impact on rental prices. As people struggle to buy a property of their own, they often turn to rental accommodation. This has resulted in a growing demand for rental apartments and soaring rental prices.

This table shows the average House Price/Earnings ratio, which is an important indicator of housing affordability. Ratios are calculated by dividing house price by the median earnings of a borough.

The Annual Survey of Hours and Earnings (ASHE) is based on a 1 per cent sample of employee jobs. Information on earnings and hours is obtained in confidence from employers. It does not cover the self-employed nor does it cover employees not paid during the reference period. Information is as at April each year. The statistics used are workplace based full-time individual earnings.

Pre-2013 Land Registry housing data are for the first half of the year only, so that they are comparable to the ASHE data which are as at April. This is no longer the case from 2013 onwards as this data uses house price data from the ONS House Price Statistics for Small Areas statistical release. Prior to 2006 data are not available for Inner and Outer London.

The lowest 25 per cent of prices are below the lower quartile; the highest 75 per cent are above the lower quartile.
The "lower quartile" property price/income is determined by ranking all property prices/incomes in ascending order.
The 'median' property price/income is determined by ranking all property prices/incomes in ascending order. The point at which one half of the values are above and one half are below is the median.

Regional data has not been published by DCLG since 2012. Data for regions has been calculated by the GLA. Data since 2014 has been calculated by the GLA using Land Registry house prices and ONS Earnings data.

Link to DCLG Live Tables

An interactive map showing the affordability ratios by local authority for 2013, 2014 and 2015 is also available.

The average square meter price of new residential real estate in Spain was the highest in Catalonia and the Community of Madrid in 2024. In the second quarter of the year, both regions boasted home prices of over 4,000 euros per square meter. That was substantially higher than the average for the country, which amounted to 2,930 euros per square meter. Overall, house prices in Spain have been on the rise since 2016.

The average price of detached and duplex houses in the biggest cities in Germany varied between approximately ***** euros and 10,000 euros per square meter in 2024. Housing was most expensive in Munich, where the square meter price of houses amounted to ***** euros. Conversely, Berlin was most affordable, with the square meter price at ***** euros. How have German house prices evolved? House prices maintained an upward trend for more than a decade, with 2020 and 2021 experiencing exceptionally high growth rates. In 2021, the nominal year-on-year change exceeded 10 percent. Nevertheless, the second half of 2022 saw the market slowing, with the annual percentage change turning negative for the first time in 12 years. Another way to examine the price growth is through the house price index, which uses 2015 as a base. At its peak in 2022, the German house price index measured about *** percent, which means that a house bought in 2015 would have appreciated by ** percent. Is housing affordable in Germany? Housing affordability depends greatly on income: High-income areas often tend to have more expensive housing, which does not necessarily make them unaffordable. The house price to income index measures the development of the cost of housing relative to income. In the first quarter of 2024, the index value stood at ***, meaning that since 2015, house price growth has outpaced income growth by about ** percent. Compared with the average for the euro area, this value was lower.

This web map shows a comparison of owner occupied housing and the median home value for counties, tracts, and block groups in the US in 2018. Yellow areas have over 50% of households occupied by the home owner. A large symbol denotes a larger median home value. The popup is configured to show the following:% Owner occupied housingCount of owner occupied housesCount of renter occupied housesTotal householdsMedian home valueHousehold income by rangeThe source of the data is Esri's 2018 demographic estimates. For more information about Esri's demographic data, visit the Updated Demographics documentation.

Graph and download economic data for Real Residential Property Prices for Mexico (QMXR628BIS) from Q1 2005 to Q4 2024 about Mexico, residential, HPI, housing, real, price index, indexes, and price.

This dataset includes the listing prices for the sale of properties (mostly houses) in Ontario. They are obtained for a short period of time in July 2016 and include the following fields: Price in dollars Address of the property Latitude and Longitude of the address obtained by using Google Geocoding service Area Name of the property obtained by using Google Geocoding service This dataset will provide a good starting point for analyzing the inflated housing market in Canada although it does not include time related information. Initially, it is intended to draw an enhanced interactive heatmap of the house prices for different neighborhoods (areas) However, if there is enough interest, there will be more information added as newer versions to this dataset. Some of those information will include more details on the property as well as time related information on the price (changes). This is a somehow related articles about the real estate prices in Ontario: http://www.canadianbusiness.com/blogs-and-comment/check-out-this-heat-map-of-toronto-real-estate-prices/ I am also inspired by this dataset which was provided for King County https://www.kaggle.com/harlfoxem/housesalesprediction

The price of residential property in New Zealand was the highest in the Auckland region in June 2025, with an average sale price of around ******* New Zealand dollars. The most populated city in the country, Auckland, has consistently reported higher house prices compared to most other regions. Buying property in New Zealand, particularly in its major cities, is expensive. The nation has one of the highest house-price-to-income ratios in the world. Auckland residential market The residential housing market in Auckland is competitive. Prices have been slowly decreasing; the Auckland region experienced an annual decrease in the average residential house price in March 2025 compared to the same month in the previous year. The price of residential property in Auckland was the highest in the North Shore City district, with an average sale price of around **** million New Zealand dollars. Home financing Due to the rising cost of real estate, an increasing number of New Zealanders who want to own their own property are taking on mortgages. Most residential mortgage lending in New Zealand went to owner-occupier borrowers, followed by first home buyers. In addition to mortgage lending, previously under the KiwiSaver HomeStart initiative, first-home buyers in New Zealand were able to apply to withdraw all or part of their KiwiSaver retirement savings to assist with purchasing a first home. Nonetheless, the scheme was discontinued in May 2024. Furthermore, even with a large initial deposit, it may take decades for many borrowers to pay off their mortgage.

Abstract Purpose: The aim of this study is to quantify the effect of location on rental housing prices in the city of Athens. Theoretical framework: The right to adequate housing is a fundamental human right defended by democratic societies. Therefore, it is of interest to examine housing tenures for both owned and rented accommodation. Design/methodology/approach: Geostatistical methods (regression-kriging) were used to obtain the results, which are represented on an isovalue map of rental housing prices displaying the minor and major effects of location by zone. Findings: This study highlights the impact of location on rental housing prices by showing how the rent of a standard dwelling in the city of Athens varies depending on its location. Research Practical & Social implications: The main social implications of this work is it helps investors determine where to direct investments and it assists public authorities in deciding where to focus urban management policies, in order to control the undesirable effects of an excessive rise in rents caused by tourism. Originality/value: The main originality of this paper lies in its isovalue map of rental housing prices for standard dwellings, which can also be interpreted as a locational isovalue map.

House prices decreased in all Swedish counties in 2023. The highest average purchase price for one- and two-residential property buildings in Sweden was in Stockholm, where the average price amounted to 6.7 million Swedish kroner in 2023, approximately twice the nation average house price. The lowest average purchase price that year was in Västernorrland, which was around 1.7 million Swedish kroner.

Only a small fraction of vacant housing units are actually considered available. Only vacant units for rent or for sale make up the available housing stock. Vacant housing that is not on the market, such as homes for seasonal, recreational, or occasional use & housing for migrant workers, are not part of the available housing stock.The housing availability rate is an indicator that economists and housing policy analysts often track. A low housing availability rate indicates a "tight" housing market (a seller's market or landlord's market) whereas a high housing availability rate indicates a buyer's or renter's market.This map shows the housing availability rate depicted by the color: pink indicates a low housing availability rate, and green indicates a high housing availability rate. The count of available housing units is depicted by the size of the symbol.This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.

This project combines data extraction, predictive modeling, and geospatial mapping to analyze housing trends in Mercer County, New Jersey. It consists of three core components: Census Data Extraction: Gathers U.S. Census data (2012–2022) on median house value, household income, and racial demographics for all census tracts in the county. It accounts for changes in census tract boundaries between 2010 and 2020 by approximating values for newly defined tracts. House Value Prediction: Uses an LSTM model with k-fold cross-validation to forecast median house values through 2025. Multiple feature combinations and sequence lengths are tested to optimize prediction accuracy, with the final model selected based on MSE and MAE scores. Data Mapping: Visualizes historical and predicted housing data using GeoJSON files from the TIGERWeb API. It generates interactive maps showing raw values, changes over time, and percent differences, with customization options to handle outliers and improve interpretability. This modular workflow can be adapted to other regions by changing the input FIPS codes and feature selections.

In 2024, Milan boasted some of the most expensive residential real estate properties in the country. A ranking of the priciest districts of the city for residential properties showed that home buyers could expect to pay on average close to ****** euros per square meter in the district Centro (historical city center). In Milan, renting a dwelling also comes at a cost. The rental price in the same area amounted to nearly ** euros per square meter in 2024. Milan, an attractive destination Milan is one of the most dynamic Italian cities. In recent years, the city was able to create jobs and expand investments in many sectors, attracting capital and talent both from Italy and from foreign countries. This growth was reflected also in the real estate market, which has proved to be the most dynamic in the country in recent years. Transactions in residential real estate in Milan increased steadily since 2012. Moreover, Milan was one of the most popular cities in Italy for residential property purchase as an investment. More tourists after Expo 2015 Hosting the Expo 2015 was a brave bet for the city. Thanks to public and private investments, Milan could carry out much-needed projects in terms of infrastructure and regeneration of some central areas of the city. In this sense, Expo 2015 also allowed the city to place itself on the map of the most popular tourist destinations in Europe and left a positive effect on the city’s tourism fluxes. International visitors have increased steadily since it was announced that the city would be the host of the global event, and continued to do so also in the years following the Expo.

This data set provides the calculated annual average price of residential homes sold, by home type, within Peel and the area municipalities since 2005. Data is compiled from monthly data released by the Toronto Real Estate Board’s Market Watch reports.NoteAverage annual home price by type for Peel and each of the area municipalities has been calculated using monthly sales and dollar volume. For years 2005 to 2011, data was first aggregated based on TREB districts.