In December 2024, the average house price in England was pricier than in any other country. This considerable disparity in average house prices is in no small part down to the country's capital city, where the average asking price was more than double that of the UK’s average. Even in London, for those who can afford a mortgage, the savings made through buying over renting can be beneficial. What drives house prices? Average house prices are affected by several factors, including economic growth, unemployment, and interest rates. Housing supply also plays a considerable role, with a shortage of supply leading to increased competition and an upward push in prices. Conversely, an excess of housing means prices fall to stimulate buyers. House prices still set to grow The housing market in the UK is expected to continue to grow in the next years. By 2029,.the annual number of housing transactions is set to reach *** million. With transactions on the rise, the average house price is also set to rise.

Graph and download economic data for Real Residential Property Prices for United States (QUSR628BIS) from Q1 1970 to Q1 2025 about residential, HPI, housing, real, price index, indexes, price, and USA.

House Price Index YoY in the United States decreased to 2.80 percent in May from 3.20 percent in April of 2025. This dataset includes a chart with historical data for the United States FHFA House Price Index YoY.

Key information about House Prices Growth

• Canada house prices grew 0.1% YoY in Jan 2025, following an increase of 0.1% YoY in the previous month.
• YoY growth data is updated monthly, available from Jan 1982 to Jan 2025, with an average growth rate of 1.8%.
• House price data reached an all-time high of 16.5% in Mar 1989 and a record low of -9.7% in Apr 1991.

In 2024, Turkey had the highest inflation-adjusted house price index out of the ** European countries under observation, making it the country where house prices have increased the most since 2010. In Turkey, the house price index exceeded *** index points in the fourth quarter of 2024, showing an increase in real terms of *** percent since 2010, the baseline year for the index. Iceland and Estonia completed the top three, with an index value of *** and *** index points. In the past year, however, many European countries saw house prices decline in real terms. Where can I find other metrics on different housing markets in Europe? To assess the valuation in different housing markets, one can compare the house-price-to-income ratios of different countries worldwide. These ratios are calculated by dividing nominal house prices by nominal disposable income per head. There are also ratios that look at how residential property prices relate to domestic rents, such as the house-price-to-rent ratio for the United Kingdom. Unfortunately, these numbers are not available in a European overview. An overview of the price per square meter of an apartment in the EU-28 countries is available, however. One region, different markets An important trait of the European housing market is that there is not one market, but multiple. Property policy in Europe lies with the domestic governments, not with the European Union. This leads to significant differences between European countries, which shows in, for example, the homeownership rate (the share of owner-occupied dwellings of all homes). These differences also lead to another problem: the availability of data. Non-Europeans might be surprised to see that house price statistics vary in depth, as every country has their own methodology and no European body exists that tracks this data for the whole continent.

Home prices fell by **** percent during the Great Recession of 2007 to 2009 in the United States. However, such a significant decrease in prices did not happen in the other four recessions which have occurred since 1980.

Average House Prices in Canada decreased to 688600 CAD in June from 690200 CAD in May of 2025. This dataset includes a chart with historical data for Canada Average House Prices.

Graph and download economic data for Existing Home Sales (EXHOSLUSM495S) from Jun 2024 to Jun 2025 about headline figure, sales, housing, and USA.

Graph and download economic data for Real Residential Property Prices for Canada (QCAR628BIS) from Q1 1970 to Q1 2025 about Canada, residential, HPI, housing, real, price index, indexes, and price.

The Commercial Real Estate Market in Mexico size was valued at nearly USD 260.3 Billion in 2022 and is anticipated to reach USD 348.64 Billion by 2031, expanding at a CAGR of 3.3% during the forecast period, 2023 – 2031. Growth of the market is attributed to the public–private partnerships, an improving economy, and increased government initiatives for infrastructure development. Commercial real estate is a property that is used only for commercial purposes or to offer a workspace, as opposed to residential real estate, which is utilized for living reasons.



Commercial real estate is frequently leased to tenants for the purpose of conducting income-generating operations. This vast category of real estate can range from a single storefront to a massive retail mall. Retailers of various types, office space, hotels & resorts, strip malls, restaurants, and healthcare facilities are all examples of commercial real estate.

Due to the immensely strong domestic market, notably the expanding middle class and growing performance of its industrial sector, the prognosis for commercial real estate remains optimistic. Because of the expansion in financial sources and real estate asset, the market offers fertile ground for development, investment, and diversification. Due to low oil prices and the strong US currency, American and Canadian customers are returning to Mexico after a several-year exile.



The Covid-19 pandemic affected the demand and supply of commercial real estate market in Mexico market. Lockdown across the globe, supply chain disorders, and oscillating supply of raw materials forced manufacturers to shut down production leading to unfortunate decline in market growth. Launch of vaccines to combat the Covid-19 pandemic is expected to contribute to the market growth over the forecast period.

Commercial Real Estate Market Trends, Drivers, Restraints, and Opportunities

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In 2017, the County Department of Economic Development, in conjunction with Reinvestment Fund, completed the 2016 Market Value Analysis (MVA) for Allegheny County. A similar MVA was completed with the Pittsburgh Urban Redevelopment Authority in 2016. The Market Value Analysis (MVA) offers an approach for community revitalization; it recommends applying interventions not only to where there is a need for development but also in places where public investment can stimulate private market activity and capitalize on larger public investment activities. 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.

The 2016 Allegheny County MVA does not include the City of Pittsburgh, which was characterized at the same time in the fourth update of the City of Pittsburgh’s MVA. All calculations herein therefore do not include the City of Pittsburgh. While the methodology between the City and County MVA's are very similar, the classification of communities will differ, and so the data between the two should not be used interchangeably.

Allegheny County's MVA utilized data that helps to define the local real estate market. Most data used covers the 2013-2016 period, and data used in the analysis includes:

•Residential Real Estate Sales; • Mortgage Foreclosures; • Residential Vacancy; • Parcel Year Built; • Parcel Condition; • Owner Occupancy; and • 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.

During the research process, staff from the County and Reinvestment Fund spent an extensive amount of effort ensuring the data and analysis was accurate. In addition to testing the data, staff physically examined different areas to verify the data sets being used were appropriate indicators and the resulting MVA categories accurately reflect the market.

Please refer to the report (included here as a pdf) for more information about the data, methodology, and findings.

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.

Key information about House Prices Growth

• Taiwan house prices grew 12.5% YoY in Sep 2024, following an increase of 11.9% YoY in the previous quarter.
• YoY growth data is updated quarterly, available from Mar 2002 to Sep 2024, with an average growth rate of 7.3%.
• House price data reached an all-time high of 20.9% in Mar 2010 and a record low of -6.0% in Mar 2016.

United States CSI: Home Values: Next 5 Yrs: 25th Percentile data was reported at 0.000 % in May 2018. This records a decrease from the previous number of 0.200 % for Apr 2018. United States CSI: Home Values: Next 5 Yrs: 25th Percentile data is updated monthly, averaging 0.100 % from Mar 2007 (Median) to May 2018, with 135 observations. The data reached an all-time high of 0.400 % in Jun 2017 and a record low of -0.400 % in Jul 2013. United States CSI: Home Values: Next 5 Yrs: 25th Percentile data remains active status in CEIC and is reported by University of Michigan. The data is categorized under Global Database’s USA – Table US.H036: Consumer Sentiment Index: Home Buying and Selling Conditions. The question was: What about the outlook for prices of homes like yours in your community over the next 5 years or so? Do you expect them to increase, remain about the same, or decrease?By about what percent per year do you expect prices of homes like yours in your community to go (up/down), on average, over the next 5years or so?

Key information about House Prices Growth

• Morocco house prices grew 0.8% YoY in Dec 2024, following a decrease of 0.4% YoY in the previous quarter.
• YoY growth data is updated quarterly, available from Mar 2007 to Dec 2024, with an average growth rate of 0.3%.
• House price data reached an all-time high of 7.6% in Mar 2017 and a record low of -6.0% in Dec 2021.

In 2023, the UK Real Estate Market reached a value of USD 816.7 million, and it is projected to surge to USD 919.0 million by 2030.

Housing Index in Croatia increased to 214.18 points in the first quarter of 2025 from 205.01 points in the fourth quarter of 2024. This dataset provides - Croatia Housing Index- actual values, historical data, forecast, chart, statistics, economic calendar and news.

DisclaimerBefore using this layer, please review the 2018 Rochester Citywide Housing Market Study for the full background and context that is required for interpreting and portraying this data. Please click here to access the study. Please also note that the housing market typologies were based on analysis of property data from 2008 to 2018, and is a snapshot of market conditions within that time frame. For an accurate depiction of current housing market typologies, this analysis would need to be redone with the latest available data.About the DataThis is a polygon feature layer containing the boundaries of all census blockgroups in the city of Rochester. Beyond the unique identifier fields including GEOID, the only other field is the housing market typology for that blockgroup.Information from the 2018 Housing Market Study- Housing Market TypologiesThe City of Rochester commissioned a Citywide Housing Market Study in 2018 as a technical study to inform development of the City's new Comprehensive Plan, Rochester 2034, and retained czb, LLC – a firm with national expertise based in Alexandria, VA – to perform the analysis.Any understanding of Rochester’s housing market – and any attempt to develop strategies to influence the market in ways likely to achieve community goals – must begin with recognition that market conditions in the city are highly uneven. On some blocks, competition for real estate is strong and expressed by pricing and investment levels that are above city averages. On other blocks, private demand is much lower and expressed by above average levels of disinvestment and physical distress. Still other blocks are in the middle – both in terms of condition of housing and prevailing prices. These block-by-block differences are obvious to most residents and shape their options, preferences, and actions as property owners and renters. Importantly, these differences shape the opportunities and challenges that exist in each neighborhood, the types of policy and investment tools to utilize in response to specific needs, and the level and range of available resources, both public and private, to meet those needs. The City of Rochester has long recognized that a one-size-fits-all approach to housing and neighborhood strategy is inadequate in such a diverse market environment and that is no less true today. To concisely describe distinct market conditions and trends across the city in this study, a Housing Market Typology was developed using a wide range of indicators to gauge market health and investment behaviors. This section of the Citywide Housing Market Study introduces the typology and its components. In later sections, the typology is used as a tool for describing and understanding demographic and economic patterns within the city, the implications of existing market patterns on strategy development, and how existing or potential policy and investment tools relate to market conditions.Overview of Housing Market Typology PurposeThe Housing Market Typology in this study is a tool for understanding recent market conditions and variations within Rochester and informing housing and neighborhood strategy development. As with any typology, it is meant to simplify complex information into a limited number of meaningful categories to guide action. Local context and knowledge remain critical to understanding market conditions and should always be used alongside the typology to maximize its usefulness.Geographic Unit of Analysis The Block Group – a geographic unit determined by the U.S. Census Bureau – is the unit of analysis for this typology, which utilizes parcel-level data. There are over 200 Block Groups in Rochester, most of which cover a small cluster of city blocks and are home to between 600 and 3,000 residents. For this tool, the Block Group provides geographies large enough to have sufficient data to analyze and small enough to reveal market variations within small areas.Four Components for CalculationAnalysis of multiple datasets led to the identification of four typology components that were most helpful in drawing out market variations within the city:• Terms of Sale• Market Strength• Bank Foreclosures• Property DistressThose components are described one-by-one on in the full study document (LINK), with detailed methodological descriptions provided in the Appendix.A Spectrum of Demand The four components were folded together to create the Housing Market Typology. The seven categories of the typology describe a spectrum of housing demand – with lower scores indicating higher levels of demand, and higher scores indicating weaker levels of demand. Typology 1 are areas with the highest demand and strongest market, while typology 3 are the weakest markets. For more information please visit: https://www.cityofrochester.gov/HousingMarketStudy2018/Dictionary: STATEFP10: The two-digit Federal Information Processing Standards (FIPS) code assigned to each US state in the 2010 census. New York State is 36. COUNTYFP10: The three-digit Federal Information Processing Standards (FIPS) code assigned to each US county in the 2010 census. Monroe County is 055. TRACTCE10: The six-digit number assigned to each census tract in a US county in the 2010 census. BLKGRPCE10: The single-digit number assigned to each block group within a census tract. The number does not indicate ranking or quality, simply the label used to organize the data. GEOID10: A unique geographic identifier based on 2010 Census geography, typically as a concatenation of State FIPS code, County FIPS code, Census tract code, and Block group number. NAMELSAD10: Stands for Name, Legal/Statistical Area Description 2010. A human-readable field for BLKGRPCE10 (Block Groups). MTFCC10: Stands for MAF/TIGER Feature Class Code 2010. For this dataset, G5030 represents the Census Block Group. BLKGRP: The GEOID that identifies a specific block group in each census tract. TYPOLOGYFi: The point system for Block Groups. Lower scores indicate higher levels of demand – including housing values and value appreciation that are above the Rochester average and vulnerabilities to distress that are below average. Higher scores indicate lower levels of demand – including housing values and value appreciation that are below the Rochester average and above presence of distressed or vulnerable properties. Points range from 1.0 to 3.0. For more information on how the points are calculated, view page 16 on the Rochester Citywide Housing Study 2018. Shape_Leng: The built-in geometry field that holds the length of the shape. Shape_Area: The built-in geometry field that holds the area of the shape. Shape_Length: The built-in geometry field that holds the length of the shape. Source: This data comes from the City of Rochester Department of Neighborhood and Business Development.

The average house price in England started to increase in August 2024, after falling by over three percent year-on-year in December 2023. In May 2025, the house price index amounted to 101.7 index points, suggesting an increase in house prices of 3.4 percent since the same month in 2024 and roughly 2 percent rise since January 2023 - the baseline year for the index. Among the different regions in the UK, West and East Midlands experienced the strongest growth.

The mortgage interest rate in Germany decreased notably between 2013 and 2022, falling below 1.5 percent. This was part of an overall trend of falling mortgage interest rates in Europe. The mortgage interest rate in Germany has since increased to 3.9 percent in the second quarter of 2024. The German mortgage market In Europe, Germany is the second-largest mortgage market, with a total value of mortgages outstanding amounting to over 1.8 trillion euros. Mortgage loans are one of the oldest bank products. Among the factors that influence mortgage interest rates are inflation, economic growth, monetary policies, the bond market, the stability of lenders, and the overall conditions of the housing market. Mortgage loans The higher cost of borrowing has a significant effect on the market: While the interest rates were at their lowest, mortgage lending was on the rise. In 2023, when the rates reached a 10-year-high, the quarterly gross mortgage lending fell to the lowest value since 2014. Meanwhile, house prices have also increased substantially in recent years. According to the House Price Index in Germany, between 2015 and 2022, house prices increased by over 60 percent.