100+ datasets found
  1. m

    House Price and the Stock Market Prices

    • data.mendeley.com
    • narcis.nl
    Updated May 21, 2019
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    Yun Hong (2019). House Price and the Stock Market Prices [Dataset]. http://doi.org/10.17632/72k38djkhm.1
    Explore at:
    Dataset updated
    May 21, 2019
    Authors
    Yun Hong
    License

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

    Description

    The house price data are collected from the official website of China's National Bureau of Statistics . We acquired the month-on-month growth data of house prices since January 2006, then compiled the house price index based on January 2006 as 100. The Shanghai Stock Exchange Index (SSEI) data which are treated as stock market prices are derived from the CSMAR database. After that, we calculate the monthly house price and stock price return as , where are proxied by the monthly house price index and SSEI, and represent the returns series. 157 observations from January 2006 to March 2019 are obtained.

  2. F

    Equity Market Volatility Tracker: Housing And Land Management

    • fred.stlouisfed.org
    json
    Updated Dec 2, 2025
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    (2025). Equity Market Volatility Tracker: Housing And Land Management [Dataset]. https://fred.stlouisfed.org/series/EMVHOUSELANDMGMT
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Dec 2, 2025
    License

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

    Description

    Graph and download economic data for Equity Market Volatility Tracker: Housing And Land Management (EMVHOUSELANDMGMT) from Jan 1985 to Nov 2025 about land, management, volatility, uncertainty, equity, housing, and USA.

  3. Share of pre-owned homes in the housing market in different countries and...

    • statista.com
    Updated Nov 29, 2025
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    Statista (2025). Share of pre-owned homes in the housing market in different countries and Japan 2023 [Dataset]. https://www.statista.com/statistics/1406169/japan-used-home-market-share-compared-to-other-countries/
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    Dataset updated
    Nov 29, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Japan
    Description

    In 2023, the second-hand home market in Japan accounted for **** percent of the overall housing market. This was significantly lower than the share of the pre-owned home market in the United States, England, and France in 2023.

  4. Negative Equity in U.S. Housing Market

    • kaggle.com
    zip
    Updated Jan 10, 2023
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    The Devastator (2023). Negative Equity in U.S. Housing Market [Dataset]. https://www.kaggle.com/datasets/thedevastator/negative-equity-in-u-s-housing-market-2017-summa
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    zip(6592634 bytes)Available download formats
    Dataset updated
    Jan 10, 2023
    Authors
    The Devastator
    Area covered
    United States
    Description

    Negative Equity in U.S. Housing Market

    Measuring Home Values, Debt, and Credit Risk

    By Zillow Data [source]

    About this dataset

    This dataset, Negative Equity in the US Housing Market, provides an in-depth look into the negative equity occurring across the United States during this single quarter. Included are metrics such as total amount of negative equity in millions of dollars, total number of homes in negative equity, percentage of homes with mortgages that are in negative equity and more. These data points provide helpful insights into both regional and national trends regarding the prevalence and rate of home mortgage delinquency stemming from a diminishment of value from peak levels.

    Home types available for analysis include 'all homes', condos/co-ops, multifamily units containing five or more housing units as well as duplexes/triplexes. Additionally, Cash buyers rates for particular areas can also be determined by referencing this collection. Further metrics such as mortgage affordability rates and impacts on overall indebtedness are readily calculated using information related to Zillow's Home Value Index (ZHVI) forecast methodology and TransUnion data respectively.

    Other variables featured within this dataset include characteristics like region type (i.e city, county ..etc), size rank based on population values , percentage change in ZHVI since peak levels as well as loan-to-value ratio greater than 200 across all regions constituted herein (NE). Moreover Zillow's own Secondary Mortgage Market Survey data is utilized to acquire average mortgage quote rates while correlative Census Bureau NCHS median household income figures represent typical assessable proportions between wages and debt obligations . So whether you're looking to assess effects along metro lines or detailed buffering through zip codes , this database should prove sufficient for insightful explorations! Nonetheless users must strictly adhere to all conditions encompassed within Terms Of Use commitments put forth by our lead provider before accessing any resources included herewith

    More Datasets

    For more datasets, click here.

    Featured Notebooks

    • 🚨 Your notebook can be here! 🚨!

    Research Ideas

    • Analyzing regional and state trends in negative equity: Analyze geographic differences in the percentage of mortgages “underwater”, total amount of negative equity, number of homes at least 90 days late, and other key indicators to provide insight into the factors influencing negative equity across regions, states and cities.
    • Tracking the recovery rate over time: Track short-term changes in numbers related to negative equity (e.g., region or area ZHVI Change from Peak) to monitor recovery rates over time as well as how different policy interventions are affecting homeownership levels in affected areas.
    • Exploring best practices for promoting housing affordability: Compare affordability metrics (e.g., mortgage payments, price-to-income ratios) across different geographic locations over time to identify best practices for empowering homeowners and promoting stability within the housing market while reducing local inequality impacts related to availability of affordable housing options and access to credit markets like mortgages/loans etc

    Acknowledgements

    If you use this dataset in your research, please credit the original authors. Data Source

    License

    See the dataset description for more information.

    Columns

    File: NESummary_2017Q1_Public.csv | Column name | Description | |:------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------| | RegionType | The type of region (e.g., city, county, metro etc.) (String) | | City | Name of the city (String) | | County | Name of the county (String) | | State | Name of the state (String) | | Metro ...

  5. F

    Equity Market Volatility Tracker: Macroeconomic News and Outlook: Real...

    • fred.stlouisfed.org
    json
    Updated Nov 6, 2025
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    (2025). Equity Market Volatility Tracker: Macroeconomic News and Outlook: Real Estate Markets [Dataset]. https://fred.stlouisfed.org/series/EMVMACRORE
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Nov 6, 2025
    License

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

    Description

    Graph and download economic data for Equity Market Volatility Tracker: Macroeconomic News and Outlook: Real Estate Markets (EMVMACRORE) from Jan 1985 to Oct 2025 about volatility, uncertainty, equity, real estate, and USA.

  6. E

    Europe Residential Real Estate Market Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Mar 7, 2025
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    Data Insights Market (2025). Europe Residential Real Estate Market Report [Dataset]. https://www.datainsightsmarket.com/reports/europe-residential-real-estate-market-17256
    Explore at:
    ppt, doc, pdfAvailable download formats
    Dataset updated
    Mar 7, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Europe
    Variables measured
    Market Size
    Description

    Discover the latest trends in the booming €1.95 trillion European residential real estate market. Explore growth forecasts (CAGR 4.5%), key drivers, regional breakdowns (UK, Germany, France), leading companies, and market challenges until 2033. Recent developments include: November 2023: DoorFeed, a Proptech company, raised EUR 12 million (USD 13.24 million) in seed funding, led by Motive Ventures and Stride and supported by renowned investors, including Seedcamp. Founded by veteran proptech entrepreneur and ex-Uber employee James Kirimi, DoorFeed aims to be the first choice for institutional investors seeking to invest in residential real estate. The company is looking to expand its footprint across Europe, with a focus on Spain, Germany, and the United Kingdom., October 2023: H.I.G, a global alternative investment firm with over USD 59 billion in assets under management, invested in the real estate development company, The Grounds Real Estate Development AG (“the Transaction”), which is listed on the alternative stock exchange. The proceeds of the transaction are expected to be utilized to fund the capital expenditures of the current projects of The Grounds. The Grounds, based in Berlin, specializes in the acquisition and development of German residential properties located in large metropolitan areas. In the transaction, the major shareholders of The Grounds, which currently hold 73% of the company’s shares, have agreed to grant H. I.G. the right to share in future rights issues.. Key drivers for this market are: Increasing Developments in the Residential Segment, Investments in the Senior Living Units. Potential restraints include: Limited Availability of Land Hindering the Market. Notable trends are: Student Housing to Gain Traction.

  7. Global Financial Crisis: Fannie Mae stock price and percentage change...

    • statista.com
    Updated Dec 1, 2022
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    Statista (2022). Global Financial Crisis: Fannie Mae stock price and percentage change 2000-2010 [Dataset]. https://www.statista.com/statistics/1349749/global-financial-crisis-fannie-mae-stock-price/
    Explore at:
    Dataset updated
    Dec 1, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The Federal National Mortgage Association, commonly known as Fannie Mae, was created by the U.S. congress in 1938, in order to maintain liquidity and stability in the domestic mortgage market. The company is a government-sponsored enterprise (GSE), meaning that while it was a publicly traded company for most of its history, it was still supported by the federal government. While there is no legally binding guarantee of shares in GSEs or their securities, it is generally acknowledged that the U.S. government is highly unlikely to let these enterprises fail. Due to these implicit guarantees, GSEs are able to access financing at a reduced cost of interest. Fannie Mae's main activity is the purchasing of mortgage loans from their originators (banks, mortgage brokers etc.) and packaging them into mortgage-backed securities (MBS) in order to ease the access of U.S. homebuyers to housing credit. The early 2000s U.S. mortgage finance boom During the early 2000s, Fannie Mae was swept up in the U.S. housing boom which eventually led to the financial crisis of 2007-2008. The association's stated goal of increasing access of lower income families to housing finance coalesced with the interests of private mortgage lenders and Wall Street investment banks, who had become heavily reliant on the housing market to drive profits. Private lenders had begun to offer riskier mortgage loans in the early 2000s due to low interest rates in the wake of the "Dot Com" crash and their need to maintain profits through increasing the volume of loans on their books. The securitized products created by these private lenders did not maintain the standards which had traditionally been upheld by GSEs. Due to their market share being eaten into by private firms, however, the GSEs involved in the mortgage markets began to also lower their standards, resulting in a 'race to the bottom'. The fall of Fannie Mae The lowering of lending standards was a key factor in creating the housing bubble, as mortgages were now being offered to borrowers with little or no ability to repay the loans. Combined with fraudulent practices from credit ratings agencies, who rated the junk securities created from these mortgage loans as being of the highest standard, this led directly to the financial panic that erupted on Wall Street beginning in 2007. As the U.S. economy slowed down in 2006, mortgage delinquency rates began to spike. Fannie Mae's losses in the mortgage security market in 2006 and 2007, along with the losses of the related GSE 'Freddie Mac', had caused its share value to plummet, stoking fears that it may collapse. On September 7th 2008, Fannie Mae was taken into government conservatorship along with Freddie Mac, with their stocks being delisted from stock exchanges in 2010. This act was seen as an unprecedented direct intervention into the economy by the U.S. government, and a symbol of how far the U.S. housing market had fallen.

  8. Negative Equity Trends in US Housing Markets

    • kaggle.com
    zip
    Updated Jan 10, 2023
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    The Devastator (2023). Negative Equity Trends in US Housing Markets [Dataset]. https://www.kaggle.com/datasets/thedevastator/negative-equity-trends-in-us-housing-markets-201
    Explore at:
    zip(3193953 bytes)Available download formats
    Dataset updated
    Jan 10, 2023
    Authors
    The Devastator
    Description

    Negative Equity Trends in US Housing Markets

    Time Series Data Across Regions and Housing Types

    By Zillow Data [source]

    About this dataset

    • This unique dataset explores the trends in negative equity within US housing markets from 2011 to 2017, allowing users to uncover the various factors and determinants that affected the outcome in each market. With data provided on all home types such as single-family homes, condominiums, and co-ops, as well as special metrics such as cash buyers and affordability analyses, you will be able to gain a comprehensive understanding of how these forces have interacted over time. Using this data you can not only learn more about historical behavior but also make predictions for future trends in these impacts.

    • In addition to data collected by Zillow through their own internal resources, they have also partnered with TransUnion and other affiliate sources to give an even more precise look into what has been driving these changing dynamics across US housing markets. Such information includes negative equity metrics which allow us to track actual outstanding home-related debt amounts over time - a valuable resource when evaluating potential investments or relocations!

    • And of course with any dataset there are a few guiding principles that one should take note of before delving in – this is especially true when it comes down to copyright issues or prohibited uses; though all data can be freely obtained here for public use - clear attribution of such information is legally required at all times (as stated on Zillow’s very own Terms & Conditions page). Furthermore additional resources such as Mortgage Rate Series or Jumbo Mortgages are also available through Zillow; again making sure that appropriate disclaimers are read before utilizing them.

    Regardless this little treasure trove of knowledge is waiting at your fingertips – whether you’re trying your luck investing wise or just looking for an area where renting rates are equitable compared real estate values; it provides everything you need understand regional housing market fluctuations over the last half decade!

    More Datasets

    For more datasets, click here.

    Featured Notebooks

    • 🚨 Your notebook can be here! 🚨!

    How to use the dataset

    This dataset provides historical and current trends in negative equity (the amount a mortgage is underwater) across the United States. It contains negative equity data from Zillow, one of the leading real estate data providers. The dataset covers all housing types (including single family, condominiums and co-ops). Additionally, it includes cash buyers share, mortgage affordability index, rental affordability index and other relative measures of affordability for US metro areas. This guide will help you understand how to use this data set for your own analysis.

    Overview of Covered Data:

    The dataset contains time series data that shows your current trend in negative equity rate as well as some associated metrics across different scales such as region, county, city and MSA level. To access this information you will need to take following columns into consideration while using this data set:

    • RegionName: Name of the region (e.g., city/county/MSA)
    • SizeRank: Ranking of the region by size
    • RegionType: Type of region (e.g., city/county/state)
    • StateName: Name of the state
    • MSA: Metropolitan Statistical Area FORMAT_4C A4 RINFOX_ RTI Information Exchange File Format [multi value 9] FORMAT_3E A3 FITS Flexible Image Transport System VERSION 4C 3E 1 Language Indicator 0 0 1 1 DONTCOPY 536880031 FILEEXTN 3 Stream Type buffer 'USTD' file version 2 HNEED 8 FILETYPE 'UDIO' creation date 05 FEB 1985 Source FMT0025 APPLICAT TRAINFORM File Organization Spooled Files DF140520 Header Block Length in Words 682 with Header Offset 636 / ULQUACK INTLCHAN * ETBFMT(V7R2),D*RECORD ACCOUNT CRFTIME FT240187 batch process status continuous Availability Continuous Version number V03C02 LOADAT AT04

    Research Ideas

    • Analyzing which markets have been disproportionately affected by the housing crisis and utilizing this information to inform investment strategies and...
  9. H

    Replication Data for: Volatility Spillovers between Iran’s Housing and Stock...

    • dataverse.harvard.edu
    Updated Oct 23, 2025
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    Soheil Hataminia (2025). Replication Data for: Volatility Spillovers between Iran’s Housing and Stock Markets: A DCC-GARCH Approach [Dataset]. http://doi.org/10.7910/DVN/57T6KO
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Oct 23, 2025
    Dataset provided by
    Harvard Dataverse
    Authors
    Soheil Hataminia
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Iran
    Description

    This dataset contains the monthly time series data used in the study "Volatility Spillovers between Iran's Housing and Stock Markets: A DCC-GARCH Approach" by Mohammadzadeh Asl & Hataminia.

  10. North America Prefabricated Housing Market Size & Share Analysis - Industry...

    • mordorintelligence.com
    pdf,excel,csv,ppt
    Updated Oct 24, 2025
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    Mordor Intelligence (2025). North America Prefabricated Housing Market Size & Share Analysis - Industry Research Report - Growth Trends [Dataset]. https://www.mordorintelligence.com/industry-reports/north-america-prefabricated-housing-market
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Oct 24, 2025
    Dataset provided by
    Authors
    Mordor Intelligence
    License

    https://www.mordorintelligence.com/privacy-policyhttps://www.mordorintelligence.com/privacy-policy

    Time period covered
    2019 - 2030
    Area covered
    North America
    Description

    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).

  11. 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
    France, Brazil, Mexico, Germany, United Kingdom, United States, Europe, Canada, North America, Japan
    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

  12. t

    Affordable Housing Market Demand, Size and Competitive Analysis | TechSci...

    • techsciresearch.com
    Updated Dec 3, 2025
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    TechSci Research (2025). Affordable Housing Market Demand, Size and Competitive Analysis | TechSci Research [Dataset]. https://www.techsciresearch.com/report/affordable-housing-market/19991.html
    Explore at:
    Dataset updated
    Dec 3, 2025
    Dataset authored and provided by
    TechSci Research
    License

    https://www.techsciresearch.com/privacy-policy.aspxhttps://www.techsciresearch.com/privacy-policy.aspx

    Description

    The Affordable Housing Market will grow from USD 226.47 Billion in 2025 to USD 322.89 Billion by 2031 at a 6.09% CAGR.

    Pages185
    Market Size2025 USD 226.47 Billion
    Forecast Market SizeUSD 322.89 Billion
    CAGR6.09%
    Fastest Growing SegmentMetro
    Largest MarketAsia Pacific
    Key Players['Dominium', 'Related Group', 'LDG Development', 'Tata Projects', 'Pennrose', 'The NRP Group', 'Prestige Group', 'Skanska AB', 'Jonathan Rose Companies LLC', 'Equity Residential']

  13. Annual home price appreciation in the U.S. 2025, by state

    • statista.com
    Updated Nov 29, 2025
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    Statista (2025). Annual home price appreciation in the U.S. 2025, by state [Dataset]. https://www.statista.com/statistics/1240802/annual-home-price-appreciation-by-state-usa/
    Explore at:
    Dataset updated
    Nov 29, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    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.

  14. Washington D.C. housing market 2024

    • kaggle.com
    zip
    Updated Jun 5, 2024
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    Natasha Lekh (2024). Washington D.C. housing market 2024 [Dataset]. https://www.kaggle.com/datasets/datadetective08/washington-d-c-housing-market-2024
    Explore at:
    zip(147382065 bytes)Available download formats
    Dataset updated
    Jun 5, 2024
    Authors
    Natasha Lekh
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Area covered
    Washington
    Description

    These datasets contain comprehensive information on current real estate listings in Washington, D.C., obtained from Zillow, and offer a detailed overview of the Washington, D.C. 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 full dataset includes all details for each listing for sale, such as:

    • 📍 Complete address, city, state, zip code, latitude/longitude coordinates
    • 🏡 Property type (single family, condo, apartment, etc.)
    • 💵 Listing price
    • 🛏️ Number of bedrooms and bathrooms
    • 📐 Square footage
    • 🌳 Lot size in acres (if applicable)
    • 🏗️ Year of construction
    • 🏘️ HOA fees (if applicable)
    • 💸 Property tax history
    • ✨ Amenities such as rooftop terraces, concierge services, etc.
    • 🏫 Nearby schools and their GreatSchools ratings
    • 🧑‍💼 Property and listing agents, brokers, and their contact information
    • 🕒 Availability for tours and open houses
    • 🖼️ Links to listing photos

    With over 5,000 current listings, this dataset is perfect for in-depth analysis of the Washington, D.C. housing market and the Washington, D.C. real estate scene. Potential applications include:

    • Comparing listing prices and price per square foot across various neighborhoods and property types
    • Mapping listings to visualize the spatial distribution of available inventory
    • Analyzing the age of available housing stock using year-of-construction data
    • Assessing typical HOA fees and property taxes for listings
    • Identifying listings with desirable amenities
    • Evaluating school quality near listings using GreatSchools ratings
    • Contacting listing agents programmatically using the provided agent information

    Whether you're a real estate professional, market analyst, data scientist, or simply interested in the Washington, D.C., housing market, this dataset offers a wealth of information to explore. You can begin investigating and discovering insights into Washington, D.C. real estate today.

  15. A

    Affordable Housing Market Report

    • promarketreports.com
    doc, pdf, ppt
    Updated Feb 11, 2025
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    Pro Market Reports (2025). Affordable Housing Market Report [Dataset]. https://www.promarketreports.com/reports/affordable-housing-market-26535
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    ppt, doc, pdfAvailable download formats
    Dataset updated
    Feb 11, 2025
    Dataset authored and provided by
    Pro Market Reports
    License

    https://www.promarketreports.com/privacy-policyhttps://www.promarketreports.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    Affordable Housing Market Analysis The global affordable housing market is projected to reach $1,983.52 billion by 2033, exhibiting a CAGR of 4.71% from 2025 to 2033. The rising population, urbanization, affordability crisis, and supportive government policies are the primary drivers fueling market growth. The increasing demand for affordable single-family homes, multi-family units, and townhouses, coupled with the adoption of innovative construction methods like prefabrication, 3D printing, and sustainable construction, are key trends shaping the market. The market faces restraints such as escalating land and construction costs, regulatory challenges, and the shortage of skilled labor. Nevertheless, the emergence of crowdfunding platforms and non-profit organizations providing financial assistance, as well as government subsidies and tax incentives, are expected to mitigate these constraints. The market is segmented based on housing type, funding source, construction method, and target demographics. D.R. Horton, Taylor Morrison, PulteGroup, Zillow, Hovnanian Enterprises, and Lennar Corporation are notable companies in the global affordable housing market, with operations in key regions like North America, Europe, and Asia Pacific. Recent developments include: Recent developments in the Affordable Housing Market have highlighted the urgent need for innovative housing solutions as governments and organizations strive to address the growing housing crisis exacerbated by economic challenges and population growth. Various nations are prioritizing policies that encourage public-private partnerships to stimulate investment in affordable housing initiatives. Additionally, the integration of sustainable building practices and smart technologies is gaining traction as stakeholders aim to improve energy efficiency while reducing construction costs. Recent collaborations among international entities and local governments focus on leveraging funding for housing projects, particularly in urban areas where demand is surging. Moreover, rising material costs and labor shortages are prompting stakeholders to explore alternative building materials and methods, including modular construction and 3D printing, to streamline processes. These trends underscore a collective commitment to creating equitable housing opportunities while navigating the complexities of market dynamics, aiming for significant progress by 2032. Overall, this evolving landscape reflects a concerted effort to promote affordability, sustainability, and accessibility in housing worldwide.. Key drivers for this market are: Green building technologies adoption Public-private partnerships expansion Innovative financing solutions development Urban regeneration projects implementation Digital platforms for housing access. Potential restraints include: rising urbanization, government initiatives; increasing housing demand; socioeconomic disparities; affordable financing options.

  16. R

    Residential Real Estate Market in the United States Report

    • marketreportanalytics.com
    doc, pdf, ppt
    Updated Apr 29, 2025
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    Market Report Analytics (2025). Residential Real Estate Market in the United States Report [Dataset]. https://www.marketreportanalytics.com/reports/residential-real-estate-market-in-the-united-states-91967
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    pdf, doc, pptAvailable download formats
    Dataset updated
    Apr 29, 2025
    Dataset authored and provided by
    Market Report Analytics
    License

    https://www.marketreportanalytics.com/privacy-policyhttps://www.marketreportanalytics.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global, United States
    Variables measured
    Market Size
    Description

    Discover the latest trends and insights into the booming US residential real estate market. Our comprehensive analysis reveals a steady CAGR of 2.04%, key drivers, market segmentation, and leading players. Learn about growth projections through 2033 and understand the opportunities and challenges shaping this dynamic sector. Recent developments include: May 2022: Resource REIT Inc. completed the sale of all of its outstanding shares of common stock to Blackstone Real Estate Income Trust Inc. for USD 14.75 per share in an all-cash deal valued at USD 3.7 billion, including the assumption of the REIT's debt., February 2022: The largest owner of commercial real estate in the world and private equity company Blackstone is growing its portfolio of residential rentals and commercial properties in the United States. The company revealed that it would shell out about USD 6 billion to buy Preferred Apartment Communities, an Atlanta-based real estate investment trust that owns 44 multifamily communities and roughly 12,000 homes in the Southeast, mostly in Atlanta, Nashville, Charlotte, North Carolina, and the Florida cities of Jacksonville, Orlando, and Tampa.. Notable trends are: Existing Home Sales Witnessing Strong Growth.

  17. m

    Money Supply, House Price and the Stock Market Dynamics in China: Evidence...

    • data.mendeley.com
    • narcis.nl
    Updated Aug 1, 2019
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    Yun Hong (2019). Money Supply, House Price and the Stock Market Dynamics in China: Evidence from a TVP-VAR Model with Stochastic Volatility [Dataset]. http://doi.org/10.17632/w34rgh6zgr.1
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    Dataset updated
    Aug 1, 2019
    Authors
    Yun Hong
    License

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

    Area covered
    China
    Description

    The house price data are collected from the official website of China's National Bureau of Statistics . We acquired the month-on-month growth data of the house price for 70 large and medium-sized representative cities in China since January 2006, then compiled the composite house price index (Houidx) based on January 2006 as 100. We use the Shanghai stock exchange composite index (SSEI) to measure the stock market price level, and the seasonal adjusted broad money M2 (M2) to proxy for the money supplying, both indexes are collected from the Wind database. The monthly house price shock (hous), stock price change (ssei) or the money supply growth (m2) are calculated as (ln(Idxt) - ln(Idxt-1))×100, where Index are the Houidx, SSEI or M2, correspondingly. 158 observations from February 2006 to March 2019 are obtained.

  18. US Residential Real Estate Market Size & 2030 Share

    • mordorintelligence.com
    pdf,excel,csv,ppt
    Updated Nov 27, 2025
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    Mordor Intelligence (2025). US Residential Real Estate Market Size & 2030 Share [Dataset]. https://www.mordorintelligence.com/industry-reports/residential-real-estate-market-in-usa
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Nov 27, 2025
    Dataset provided by
    Authors
    Mordor Intelligence
    License

    https://www.mordorintelligence.com/privacy-policyhttps://www.mordorintelligence.com/privacy-policy

    Time period covered
    2019 - 2030
    Area covered
    United States
    Description

    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)

  19. Share of pre-owned home market in the housing market Japan 2014-2023

    • statista.com
    Updated Sep 23, 2017
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    Statista (2017). Share of pre-owned home market in the housing market Japan 2014-2023 [Dataset]. https://www.statista.com/statistics/1203178/japan-existing-dwelling-transactions-as-a-share-of-new-dwelling-constructions/
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    Dataset updated
    Sep 23, 2017
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Japan
    Description

    In 2023, the second-hand home market in Japan accounted for **** percent of the overall housing market. In 2019, the share reached a peak amid a decline in the number of construction starts and an increase in existing home transactions.

  20. House Prices US Shiller

    • kaggle.com
    zip
    Updated Oct 28, 2025
    + more versions
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    yedige ashmet (2025). House Prices US Shiller [Dataset]. https://www.kaggle.com/datasets/yedigeashmet/house-prices
    Explore at:
    zip(51570 bytes)Available download formats
    Dataset updated
    Oct 28, 2025
    Authors
    yedige ashmet
    License

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

    Area covered
    United States
    Description

    Case-Shiller Index of U.S. Residential House Prices

    This dataset provides comprehensive insights into U.S. residential house prices through the S&P Case-Shiller Home Price Index, which includes both the national index and indices for 20 metropolitan regions. The data is derived from the S&P Case-Shiller Index, a widely recognized and reliable measure of U.S. housing price movements. It is updated monthly and utilizes the "repeat sales method" to track the price changes of the same properties over time, making it an accurate reflection of housing appreciation.

    Data Overview

    The dataset includes: - S&P/Case-Shiller U.S. National Home Price Index: A composite index of single-family home prices across nine U.S. Census divisions. - Indices for 20 Metropolitan Regions: Regional indices that highlight housing price trends in major U.S. cities.

    Key Methodology

    The index uses a "repeat sales" approach, which tracks properties that have been sold at least twice to capture changes in their value over time. This method minimizes biases from changes in housing stock or individual property characteristics. The index originated in the 1980s through the work of Karl E. Case and Robert J. Shiller, pioneers in developing the repeat sales technique. It remains one of the most trusted tools for measuring U.S. housing market trends.

    The indices are used widely by policymakers, economists, and analysts to gauge housing market conditions and make informed decisions.

    Use Cases

    This dataset can be used for: - Housing Market Analysis: Track trends in national and metropolitan housing prices. - Econometric Modeling: Analyze the relationship between housing prices and macroeconomic factors. - Forecasting: Build models to predict future housing market movements.

    Source

    Data sourced from: https://github.com/datasets/house-prices-us Original source: https://datahub.io/core/house-prices-us

Share
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Email
Click to copy link
Link copied
Close
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Yun Hong (2019). House Price and the Stock Market Prices [Dataset]. http://doi.org/10.17632/72k38djkhm.1

House Price and the Stock Market Prices

Explore at:
13 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
May 21, 2019
Authors
Yun Hong
License

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

Description

The house price data are collected from the official website of China's National Bureau of Statistics . We acquired the month-on-month growth data of house prices since January 2006, then compiled the house price index based on January 2006 as 100. The Shanghai Stock Exchange Index (SSEI) data which are treated as stock market prices are derived from the CSMAR database. After that, we calculate the monthly house price and stock price return as , where are proxied by the monthly house price index and SSEI, and represent the returns series. 157 observations from January 2006 to March 2019 are obtained.

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