This dataset contains prices of New York houses, providing valuable insights into the real estate market in the region. It includes information such as broker titles, house types, prices, number of bedrooms and bathrooms, property square footage, addresses, state, administrative and local areas, street names, and geographical coordinates.
- BROKERTITLE: Title of the broker
- TYPE: Type of the house
- PRICE: Price of the house
- BEDS: Number of bedrooms
- BATH: Number of bathrooms
- PROPERTYSQFT: Square footage of the property
- ADDRESS: Full address of the house
- STATE: State of the house
- MAIN_ADDRESS: Main address information
- ADMINISTRATIVE_AREA_LEVEL_2: Administrative area level 2 information
- LOCALITY: Locality information
- SUBLOCALITY: Sublocality information
- STREET_NAME: Street name
- LONG_NAME: Long name
- FORMATTED_ADDRESS: Formatted address
- LATITUDE: Latitude coordinate of the house
- LONGITUDE: Longitude coordinate of the house
- Price analysis: Analyze the distribution of house prices to understand market trends and identify potential investment opportunities.
- Property size analysis: Explore the relationship between property square footage and prices to assess the value of different-sized houses.
- Location-based analysis: Investigate geographical patterns to identify areas with higher or lower property prices.
- Bedroom and bathroom trends: Analyze the impact of the number of bedrooms and bathrooms on house prices.
- Broker performance analysis: Evaluate the influence of different brokers on the pricing of houses.
If you find this dataset useful, your support through an upvote would be greatly appreciated ❤️🙂 Thank you
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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:
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.
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Residential Real Estate Market Size 2025-2029
The residential real estate market size is valued to increase USD 485.2 billion, at a CAGR of 4.5% from 2024 to 2029. Growing residential sector globally will drive the residential real estate market.
Major Market Trends & Insights
APAC dominated the market and accounted for a 55% growth during the forecast period.
By Mode Of Booking - Sales segment was valued at USD 926.50 billion in 2023
By Type - Apartments and condominiums segment accounted for the largest market revenue share in 2023
Market Size & Forecast
Market Opportunities: USD 41.01 billion
Market Future Opportunities: USD 485.20 billion
CAGR : 4.5%
APAC: Largest market in 2023
Market Summary
The market is a dynamic and ever-evolving sector that continues to shape the global economy. With increasing marketing initiatives and the growing residential sector globally, the market presents significant opportunities for growth. However, regulatory uncertainty looms large, posing challenges for stakeholders. According to recent reports, technology adoption in residential real estate has surged, with virtual tours and digital listings becoming increasingly popular. In fact, over 40% of homebuyers in the US prefer virtual property viewings. Core technologies such as artificial intelligence and blockchain are revolutionizing the industry, offering enhanced customer experiences and streamlined processes.
Despite these advancements, regulatory compliance remains a major concern, with varying regulations across regions adding complexity to market operations. The market is a complex and intriguing space, with ongoing activities and evolving patterns shaping its future trajectory.
What will be the Size of the Residential Real Estate Market during the forecast period?
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How is the Residential Real Estate Market Segmented and what are the key trends of market segmentation?
The residential real estate industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.
Mode Of Booking
Sales
Rental or lease
Type
Apartments and condominiums
Landed houses and villas
Location
Urban
Suburban
Rural
End-user
Mid-range housing
Affordable housing
Luxury housing
Geography
North America
US
Canada
Mexico
Europe
France
Germany
UK
APAC
Australia
Japan
South Korea
South America
Brazil
Rest of World (ROW)
By Mode Of Booking Insights
The sales segment is estimated to witness significant growth during the forecast period.
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The Sales segment was valued at USD 926.50 billion in 2019 and showed a gradual increase during the forecast period.
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Regional Analysis
APAC is estimated to contribute 55% to the growth of the global market during the forecast period.Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.
See How Residential Real Estate Market Demand is Rising in APAC Request Free Sample
The market in the Asia Pacific (APAC) region holds a significant share and is projected to lead the global market growth. Factors fueling this expansion include the region's rapid urbanization and increasing consumer spending power. Notably, residential and commercial projects in countries like India and China are experiencing robust development. The residential real estate sector in China plays a pivotal role in the economy and serves as a major growth driver for the market.
With these trends continuing, the APAC the market is poised for continued expansion during the forecast period.
Market Dynamics
Our researchers analyzed the data with 2024 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.
In the Residential Real Estate Market, understanding the impact property tax rates home values and effect interest rates mortgage affordability is essential for buyers and investors. Key factors affecting home price appreciation and factors influencing housing affordability shape market trends, while the importance property due diligence process and requirements environmental site assessment ensure informed decisions. Investors benefit from methods calculating rental property roi, process home equity loan application, and benefits real estate portfolio diversification. Tools like property management software efficiency and techniques effective property marketing help tackle challenges managing rental properties. Additionally, strategies successf
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Explore the Redfin USA Properties Dataset, available in CSV format. This extensive dataset provides valuable insights into the U.S. real estate market, including detailed property listings, prices, property types, and more across various states and cities. Perfect for those looking to conduct in-depth market analysis, real estate investment research, or financial forecasting.
Key Features:
Who Can Benefit From This Dataset:
Download the Redfin USA Properties Dataset to access essential information on the U.S. housing market, ideal for professionals in real estate, finance, and data analytics. Unlock key insights to make informed decisions in a dynamic market environment.
Looking for deeper insights or a custom data pull from Redfin?
Send a request with just one click and explore detailed property listings, price trends, and housing data.
🔗 Request Redfin Real Estate Data
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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.
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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.
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The United States Residential Real Estate Market is Segmented by Property Type (Apartments and Condominiums, and Villas and Landed Houses), by Price Band (Affordable, Mid-Market and Luxury), by Business Model (Sales and Rental), by Mode of Sale (Primary and Secondary), and by Region (Northeast, Midwest, Southeast, West and Southwest). The Market Forecasts are Provided in Terms of Value (USD)
In late 2016, the URA, in conjunction with Reinvestment Fund, completed the 2016 Market Value Analysis (MVA) for the City of Pittsburgh. 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 neighborhood 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. Pittsburgh’s 2016 MVA utilized data that helps to define the local real estate market between July, 2013 and June, 2016: • Median Sales Price • Variance of Sales Price • Percent Households Owner Occupied • Density of Residential Housing Units • Percent Rental with Subsidy • Foreclosures as a Percent of Sales • Permits as a Percent of Housing Units • Percent of Housing Units Built Before 1940 • Percent of Properties with Assessed Condition “Poor” or worse • Vacant Housing Units as a Percentage of Habitable 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 URA 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.
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Housing Index in the United States decreased to 433.40 points in July from 433.90 points in June of 2025. This dataset provides the latest reported value for - United States House Price Index MoM Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
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This dataset provides a comprehensive overview of new housing price indexes in Canada. The data is sourced from a reliable statistical survey, offering a detailed breakdown of housing prices across different components such as total house and land, house only, and land only. The dataset is structured to include key metrics such as geographical location, price index classification, and specific price values, providing a robust foundation for analyzing housing price dynamics within the country.
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This dataset contains detailed information on current real estate listings in Houston, Texas, sourced from Zillow, and provides a comprehensive snapshot of the Houston housing market as of 5th June 2024.
The data was extracted from Zillow using a combination of two scraping tools from Apify: Zillow ZIP Code Scraper 🔗 https://apify.com/maxcopell/zillow-zip-search and Zillow Details Scraper 🔗 https://apify.com/maxcopell/zillow-detail-scraper.
The data includes key details for each listing for sale, such as:
With 25,900 current listings, this dataset is ideal for in-depth analysis of the Houston housing market and the Houston real estate market. Potential use cases include:
Whether you're a real estate professional, market researcher, data scientist, or just curious about the Houston housing market, this dataset provides a wealth of information to explore. You can start investigating Houston real estate today.
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Graph and download economic data for All-Transactions House Price Index for Michigan (MISTHPI) from Q1 1975 to Q2 2025 about MI, appraisers, HPI, housing, price index, indexes, price, and USA.
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License information was derived automatically
Key information about House Prices Growth
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Residential Real Estate Market is Segmented by Property Type (Apartments & Condominiums, and Landed Houses & Villas), by Price Band (Affordable, Mid-Market, and Luxury/Super-prime), by Business Model (Sales and Rental), by Mode of Sale (Primary and Secondary), and by Region (North America, South America, Europe, Asia-Pacific, and Middle East & Africa). The Market Forecasts are Provided in Terms of Value (USD).
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Our dataset features comprehensive housing market data, extracted from 250,000 records sourced directly from Redfin USA. Our Crawl Feeds team utilized proprietary in-house tools to meticulously scrape and compile this valuable data.
Key Benefits of Our Housing Market Data:
Unlock the Power of Redfin Data for Real Estate Professionals
Leveraging our Redfin properties dataset allows real estate professionals to make data-driven decisions. With detailed insights into property listings, sales history, and pricing trends, agents and investors can identify opportunities in the market more effectively. The data is particularly useful for comparing neighborhood trends, understanding market demand, and making informed investment decisions.
Enhance Your Real Estate Research with Custom Filters and Analysis
Our Redfin dataset is not only extensive but also customizable, allowing users to apply filters based on specific criteria such as property type, listing status, and geographic location. This flexibility enables researchers and analysts to drill down into the data, uncovering patterns and insights that can guide strategic planning and market entry decisions. Whether you're tracking the performance of single-family homes or exploring multi-family property trends, this dataset offers the depth and accuracy needed for thorough analysis.
Looking for deeper insights or a custom data pull from Redfin?
Send a request with just one click and explore detailed property listings, price trends, and housing data.
🔗 Request Redfin Real Estate Data
Global house prices experienced a significant shift in 2022, with advanced economies seeing a notable decline after a prolonged period of growth. The real house price index (adjusted for inflation) for advanced economies peaked at nearly *** index points in early 2022 before falling to around ****** points by the fourth quarter of 2024. This represents a reversal of the upward trend that had characterized the housing market for roughly a decade. Conversely, real house prices in emerging economies resumed growing, after a brief correction in the second half of 2022. What is behind the slowdown? Inflation and slow economic growth have been the primary drivers for the cooling of the housing market. Secondly, the growing gap between incomes and house prices since 2012 has decreased the affordability of homeownership. Last but not least, homebuyers in 2024 faced dramatically higher mortgage interest rates, further contributing to worsening sentiment and declining transactions. Some markets continue to grow While many countries witnessed a deceleration in house price growth in 2022, some markets continued to see substantial increases. Turkey, in particular, stood out with a nominal increase in house prices of over ** percent in the first quarter of 2024. Other countries that recorded a two-digit growth include Russia and the United Arab Emirates. When accounting for inflation, the three countries with the fastest growing residential prices in early 2024 were the United Arab Emirates, Poland, and Bulgaria.
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US Real Estate Market Size & Growth 2025-2032: Valued at USD 3T in 2025, the market is projected to reach nearly USD 3.9T by 2032, growing at a CAGR of 4.12%. Get the latest industry forecast and analysis.
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The North America Prefabricated Housing Market Report is Segmented by Material Type (Concrete, Glass, Metal, Timber, Other Materials), by Type (Single Family, Multi Family), by Product Type (Modular Homes, Panelized & Componentized Systems, Manufactured Homes, Other Prefab Types), and by Country (United States, Canada, Mexico). The Market Forecasts are Provided in Terms of Value (USD).
The house price index (HPI) shows changes in the value of residential properties in England, Scotland, Wales, and Northern Ireland. With the HPI set at a base of 100 in January 2023, a value of over 100 would mark an increase in the average dwelling price. A value of under 100 points, on the other hand, would indicate that the average price has dropped. In April 2025, the index measured 101.7 index points, showing an increase of 1.7 percent since January 2023. UK house prices grew rapidly during the COVID-19 pandemic House prices in the UK grew steadily between 2015 and 2020, fueled by stable economic growth and low borrowing costs. In the following two years, a combination of factors exacerbated this trend. These factors included a stamp duty holiday, low interest rates, a shortage of new homes supplied, and a high housing demand. As a result, house price growth soared, hitting a record 13.6 percent in July 2022. This trend in the index, and therefore the value of UK residential properties, has also been observed by the Halifax house price index. What is the average house price in the UK? Average house prices are affected by several factors. Economic growth, unemployment, interest rates and mortgage availability can all drive them up or down. A shortage of supply means that the need for housing and the competitive market created will push house prices up. An excess of housing, on the other hand, means prices fall to stimulate buyers.
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House Price Index YoY in the United States decreased to 2.30 percent in July from 2.70 percent in June of 2025. This dataset includes a chart with historical data for the United States FHFA House Price Index YoY.
This dataset contains prices of New York houses, providing valuable insights into the real estate market in the region. It includes information such as broker titles, house types, prices, number of bedrooms and bathrooms, property square footage, addresses, state, administrative and local areas, street names, and geographical coordinates.
- BROKERTITLE: Title of the broker
- TYPE: Type of the house
- PRICE: Price of the house
- BEDS: Number of bedrooms
- BATH: Number of bathrooms
- PROPERTYSQFT: Square footage of the property
- ADDRESS: Full address of the house
- STATE: State of the house
- MAIN_ADDRESS: Main address information
- ADMINISTRATIVE_AREA_LEVEL_2: Administrative area level 2 information
- LOCALITY: Locality information
- SUBLOCALITY: Sublocality information
- STREET_NAME: Street name
- LONG_NAME: Long name
- FORMATTED_ADDRESS: Formatted address
- LATITUDE: Latitude coordinate of the house
- LONGITUDE: Longitude coordinate of the house
- Price analysis: Analyze the distribution of house prices to understand market trends and identify potential investment opportunities.
- Property size analysis: Explore the relationship between property square footage and prices to assess the value of different-sized houses.
- Location-based analysis: Investigate geographical patterns to identify areas with higher or lower property prices.
- Bedroom and bathroom trends: Analyze the impact of the number of bedrooms and bathrooms on house prices.
- Broker performance analysis: Evaluate the influence of different brokers on the pricing of houses.
If you find this dataset useful, your support through an upvote would be greatly appreciated ❤️🙂 Thank you