100+ datasets found
  1. T

    United States House Price Index YoY

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Sep 30, 2025
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    TRADING ECONOMICS (2025). United States House Price Index YoY [Dataset]. https://tradingeconomics.com/united-states/house-price-index-yoy
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    json, excel, xml, csvAvailable download formats
    Dataset updated
    Sep 30, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1992 - Jul 31, 2025
    Area covered
    United States
    Description

    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.

  2. F

    Median Sales Price of Houses Sold for the United States

    • fred.stlouisfed.org
    json
    Updated Jul 24, 2025
    + more versions
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    (2025). Median Sales Price of Houses Sold for the United States [Dataset]. https://fred.stlouisfed.org/series/MSPUS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 24, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    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.

  3. M

    Mexico House Prices Growth

    • ceicdata.com
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    CEICdata.com, Mexico House Prices Growth [Dataset]. https://www.ceicdata.com/en/indicator/mexico/house-prices-growth
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    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 1, 2022 - Dec 1, 2024
    Area covered
    Mexico
    Description

    Key information about House Prices Growth

    • Mexico house prices grew 8.8% YoY in Dec 2024, following an increase of 9.2% YoY in the previous quarter.
    • YoY growth data is updated quarterly, available from Mar 2006 to Dec 2024, with an average growth rate of 7.4%.
    • House price data reached an all-time high of 11.7% in Mar 2023 and a record low of 2.2% in Jun 2010.

    CEIC calculates House Price Growth from quarterly House Price Index. Federal Mortgage Society provides House Price Index with base 2017=100.

  4. F

    Average Sales Price of Houses Sold for the United States

    • fred.stlouisfed.org
    json
    Updated Jul 24, 2025
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    (2025). Average Sales Price of Houses Sold for the United States [Dataset]. https://fred.stlouisfed.org/series/ASPUS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 24, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    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.

  5. U

    United States House Prices Growth

    • ceicdata.com
    Updated Nov 27, 2021
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    CEICdata.com (2021). United States House Prices Growth [Dataset]. https://www.ceicdata.com/en/indicator/united-states/house-prices-growth
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    Dataset updated
    Nov 27, 2021
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 1, 2022 - Dec 1, 2024
    Area covered
    United States
    Description

    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.

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

  6. C

    Canada House Prices Growth

    • ceicdata.com
    Updated Mar 15, 2025
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    CEICdata.com (2025). Canada House Prices Growth [Dataset]. https://www.ceicdata.com/en/indicator/canada/house-prices-growth
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    Dataset updated
    Mar 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Feb 1, 2024 - Jan 1, 2025
    Area covered
    Canada
    Description

    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.

    CEIC calculates House Prices Growth from monthly House Price Index. Statistics Canada provides House Price Index with base December 2016=100. House Price Index covers New Housing only.

  7. F

    Commercial Real Estate Prices for United States

    • fred.stlouisfed.org
    json
    Updated Sep 2, 2025
    + more versions
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    (2025). Commercial Real Estate Prices for United States [Dataset]. https://fred.stlouisfed.org/series/COMREPUSQ159N
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 2, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Area covered
    United States
    Description

    Graph and download economic data for Commercial Real Estate Prices for United States (COMREPUSQ159N) from Q1 2005 to Q1 2025 about real estate, commercial, rate, and USA.

  8. S

    Switzerland House Prices Growth

    • ceicdata.com
    Updated Mar 15, 2025
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    CEICdata.com (2025). Switzerland House Prices Growth [Dataset]. https://www.ceicdata.com/en/indicator/switzerland/house-prices-growth
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    Dataset updated
    Mar 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 1, 2022 - Dec 1, 2024
    Area covered
    Switzerland
    Description

    Key information about House Prices Growth

    • Switzerland house prices grew 0.9% YoY in Dec 2024, following an increase of 1.9% YoY in the previous quarter.
    • YoY growth data is updated quarterly, available from Mar 1971 to Dec 2024, with an average growth rate of 2.4%.
    • House price data reached an all-time high of 26.2% in Mar 1973 and a record low of -9.0% in Dec 1975.

    CEIC calculates House Prices Growth from quarterly Real Estate Price Index. Swiss National Bank provides Real Estate Price Index with base Q1 2000=100. House Prices Growth covers single family homes only.

  9. Residential Real Estate Market Analysis, Size, and Forecast 2025-2029: North...

    • technavio.com
    pdf
    Updated Jun 14, 2025
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    Technavio (2025). Residential Real Estate Market Analysis, Size, and Forecast 2025-2029: North America (US, Canada, and Mexico), Europe (France, Germany, and UK), APAC (Australia, Japan, and South Korea), South America (Brazil), and Rest of World (ROW) [Dataset]. https://www.technavio.com/report/residential-real-estate-market-analysis
    Explore at:
    pdfAvailable download formats
    Dataset updated
    Jun 14, 2025
    Dataset provided by
    TechNavio
    Authors
    Technavio
    License

    https://www.technavio.com/content/privacy-noticehttps://www.technavio.com/content/privacy-notice

    Time period covered
    2025 - 2029
    Area covered
    Europe, France, Brazil, Japan, North America, Germany, Canada, United States, United Kingdom, Mexico
    Description

    Snapshot img

    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?

    Get Key Insights on Market Forecast (PDF) Request Free Sample

    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.

    Request Free Sample

    The Sales segment was valued at USD 926.50 billion in 2019 and showed a gradual increase during the forecast period.

    Request Free Sample

    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

  10. F

    Real Residential Property Prices for United States

    • fred.stlouisfed.org
    json
    Updated Sep 25, 2025
    + more versions
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    (2025). Real Residential Property Prices for United States [Dataset]. https://fred.stlouisfed.org/series/QUSR628BIS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 25, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Area covered
    United States
    Description

    Graph and download economic data for Real Residential Property Prices for United States (QUSR628BIS) from Q1 1970 to Q2 2025 about residential, HPI, housing, real, price index, indexes, price, and USA.

  11. Median sale price of existing homes sold in the U.S. 1990-2024 with forecast...

    • statista.com
    Updated Mar 4, 2025
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    Statista Research Department (2025). Median sale price of existing homes sold in the U.S. 1990-2024 with forecast for 2027 [Dataset]. https://www.statista.com/topics/1618/residential-housing-in-the-us/
    Explore at:
    Dataset updated
    Mar 4, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    United States
    Description

    The U.S. housing market continues to evolve, with the median price for existing homes forecast to fall to 408,000 U.S. dollars by 2027. This projection comes after a period of significant growth and recent fluctuations, reflecting the complex interplay of economic factors affecting the real estate sector. The rising costs have not only impacted home prices but also down payments, with the median down payment more than doubling since 2012. Regional variations in housing costs Home prices and down payments vary dramatically across the United States. While the national median down payment stood at approximately 26,700 U.S. dollars in early 2024, homebuyers in states like California, Massachusetts, and Hawaii faced down payments exceeding 74,000 U.S. dollars. This disparity highlights the challenges of homeownership in high-cost markets and underscores the importance of location in determining housing affordability. Market dynamics and future outlook The housing market has shown signs of cooling after years of rapid growth, with a modest price increase of 4.1 percent in 2024. This slowdown can be attributed in part to rising mortgage rates, which have tempered demand. Despite these challenges, most states continued to see year-over-year price growth in 2025, with Rhode Island and West Virginia leading the packby home appreciation. As the market adjusts to new economic realities, potential homebuyers and investors alike will be watching closely for signs of stabilization or renewed growth in the coming years.

  12. F

    All-Transactions House Price Index for California

    • fred.stlouisfed.org
    json
    Updated Aug 26, 2025
    + more versions
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    (2025). All-Transactions House Price Index for California [Dataset]. https://fred.stlouisfed.org/series/CASTHPI
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Aug 26, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    California
    Description

    Graph and download economic data for All-Transactions House Price Index for California (CASTHPI) from Q1 1975 to Q2 2025 about appraisers, CA, HPI, housing, price index, indexes, price, and USA.

  13. F

    All-Transactions House Price Index for the United States

    • fred.stlouisfed.org
    json
    Updated Aug 26, 2025
    + more versions
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    (2025). All-Transactions House Price Index for the United States [Dataset]. https://fred.stlouisfed.org/series/USSTHPI
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Aug 26, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for All-Transactions House Price Index for the United States (USSTHPI) from Q1 1975 to Q2 2025 about appraisers, HPI, housing, price index, indexes, price, and USA.

  14. S

    Sweden House Prices Growth

    • ceicdata.com
    Updated Jun 15, 2021
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    CEICdata.com (2021). Sweden House Prices Growth [Dataset]. https://www.ceicdata.com/en/indicator/sweden/house-prices-growth
    Explore at:
    Dataset updated
    Jun 15, 2021
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 1, 2022 - Dec 1, 2024
    Area covered
    Sweden
    Description

    Key information about House Prices Growth

    • Sweden house prices grew 2.6% YoY in Dec 2024, following an increase of 1.5% YoY in the previous quarter.
    • YoY growth data is updated quarterly, available from Mar 1987 to Dec 2024, with an average growth rate of 7.1%.
    • House price data reached an all-time high of 20.8% in Jun 1989 and a record low of -15.3% in Dec 1992.

    CEIC calculates House Prices Growth from quarterly Real Estate Price Index. Statistics Sweden provides Real Estate Price Index with base 1981=100. House Prices Growth covers 1 or 2 dwelling buildings for permanent living only.

  15. Zillow.com House Price Prediction

    • kaggle.com
    Updated Aug 25, 2024
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    Mohamed Maideen (2024). Zillow.com House Price Prediction [Dataset]. https://www.kaggle.com/datasets/mohamedmaideen/zillow-com-house-price-prediction
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 25, 2024
    Dataset provided by
    Kaggle
    Authors
    Mohamed Maideen
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    Zillow.com is a popular real estate marketplace that provides a comprehensive platform for buying, selling, renting, and exploring homes. Founded in 2006 by Rich Barton and Lloyd Frink, Zillow has become one of the go-to resources for people navigating the real estate market.

    Key Features: Home Listings: Zillow offers an extensive database of homes for sale and rent. Users can search for properties by various criteria including location, price range, number of bedrooms, and more.

    Zestimate®: One of Zillow's standout features is its Zestimate, an estimated market value for a home based on public data, user-submitted data, and other relevant information. While it's not a definitive appraisal, it provides a starting point for understanding a home's potential market value.

    Market Trends: Zillow provides valuable insights into real estate trends and statistics, such as average home prices, appreciation rates, and market health indicators. This can be particularly useful for buyers and sellers looking to understand market dynamics.

    Tools for Buyers and Sellers: The platform offers various tools and calculators to help users with financial planning, including mortgage calculators, affordability calculators, and home value estimators. Sellers can use Zillow to list their homes, connect with potential buyers, and track their property’s performance on the market.

    Zillow Offers: For those looking to sell their home quickly, Zillow Offers is a service that allows homeowners to receive a cash offer from Zillow, potentially streamlining the selling process.

    This dataset is collected from zillow.com using API. This is the raw version of the data fetched using API which requires data cleaning, feature extraction and feature engineering to get useful information for the house price prediction.

  16. c

    Housing Market Study Typologies

    • data.cityofrochester.gov
    Updated Feb 18, 2020
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    Open_Data_Admin (2020). Housing Market Study Typologies [Dataset]. https://data.cityofrochester.gov/maps/RochesterNY::housing-market-study-typologies
    Explore at:
    Dataset updated
    Feb 18, 2020
    Dataset authored and provided by
    Open_Data_Admin
    Area covered
    Description

    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.

  17. y

    Case-Shiller Charlotte, NC Home Price Index YoY

    • ycharts.com
    html
    Updated Sep 30, 2025
    + more versions
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    Standard and Poor's (2025). Case-Shiller Charlotte, NC Home Price Index YoY [Dataset]. https://ycharts.com/indicators/case_shiller_home_price_index_annual_change_charlotte
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Sep 30, 2025
    Dataset provided by
    YCharts
    Authors
    Standard and Poor's
    License

    https://www.ycharts.com/termshttps://www.ycharts.com/terms

    Time period covered
    Jan 31, 1988 - Jul 31, 2025
    Area covered
    Charlotte, North Carolina
    Variables measured
    Case-Shiller Charlotte, NC Home Price Index YoY
    Description

    View monthly updates and historical trends for Case-Shiller Charlotte, NC Home Price Index YoY. Source: Standard and Poor's. Track economic data with YCha…

  18. T

    Hong Kong House Price Index

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Oct 24, 2025
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    TRADING ECONOMICS (2025). Hong Kong House Price Index [Dataset]. https://tradingeconomics.com/hong-kong/housing-index
    Explore at:
    excel, xml, csv, jsonAvailable download formats
    Dataset updated
    Oct 24, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 2, 1994 - Oct 19, 2025
    Area covered
    Hong Kong
    Description

    Housing Index in Hong Kong decreased to 141.09 points in October 19 from 141.92 points in the previous week. This dataset provides - Hong Kong House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  19. T

    Philippines Residential Property Prices

    • tradingeconomics.com
    • es.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, Philippines Residential Property Prices [Dataset]. https://tradingeconomics.com/philippines/residential-property-prices
    Explore at:
    csv, excel, json, xmlAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 31, 2009 - Mar 31, 2025
    Area covered
    Philippines
    Description

    Residential Property Prices in Philippines increased 7.56 percent in March of 2025 over the same month in the previous year. This dataset includes a chart with historical data for Philippines Residential Property Prices.

  20. y

    Columbus, OH House Price Index

    • ycharts.com
    html
    Updated Aug 26, 2025
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    Federal Housing Finance Agency (2025). Columbus, OH House Price Index [Dataset]. https://ycharts.com/indicators/columbus_oh_house_price_purchase_only_index
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Aug 26, 2025
    Dataset provided by
    YCharts
    Authors
    Federal Housing Finance Agency
    License

    https://www.ycharts.com/termshttps://www.ycharts.com/terms

    Time period covered
    Mar 31, 1991 - Jun 30, 2025
    Area covered
    Ohio, Columbus
    Variables measured
    Columbus, OH House Price Index
    Description

    View quarterly updates and historical trends for Columbus, OH House Price Index. Source: Federal Housing Finance Agency. Track economic data with YCharts …

Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
TRADING ECONOMICS (2025). United States House Price Index YoY [Dataset]. https://tradingeconomics.com/united-states/house-price-index-yoy

United States House Price Index YoY

United States House Price Index YoY - Historical Dataset (1992-01-31/2025-07-31)

Explore at:
2 scholarly articles cite this dataset (View in Google Scholar)
json, excel, xml, csvAvailable download formats
Dataset updated
Sep 30, 2025
Dataset authored and provided by
TRADING ECONOMICS
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
Jan 31, 1992 - Jul 31, 2025
Area covered
United States
Description

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.

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