100+ datasets found
  1. Number of home sales in the U.S. 2014-2024 with forecast until 2026

    • statista.com
    Updated Jun 20, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Number of home sales in the U.S. 2014-2024 with forecast until 2026 [Dataset]. https://www.statista.com/statistics/275156/total-home-sales-in-the-united-states-from-2009/
    Explore at:
    Dataset updated
    Jun 20, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The number of home sales in the United States peaked in 2021 at almost ************* after steadily rising since 2018. Nevertheless, the market contracted in the following year, with transaction volumes falling to ***********. Home sales remained muted in 2024, with a mild increase expected in 2025 and 2026. A major factor driving this trend is the unprecedented increase in mortgage interest rates due to high inflation. How have U.S. home prices developed over time? The average sales price of new homes has also been rising since 2011. Buyer confidence seems to have recovered after the property crash, which has increased demand for homes and also the prices sellers are demanding for homes. At the same time, the affordability of U.S. homes has decreased. Both the number of existing and newly built homes sold has declined since the housing market boom during the coronavirus pandemic. Challenges in housing supply The number of housing units in the U.S. rose steadily between 1975 and 2005 but has remained fairly stable since then. Construction increased notably in the 1990s and early 2000s, with the number of construction starts steadily rising, before plummeting amid the infamous housing market crash. Housing starts slowly started to pick up in 2011, mirroring the economic recovery. In 2022, the supply of newly built homes plummeted again, as supply chain challenges following the COVID-19 pandemic and tariffs on essential construction materials such as steel and lumber led to prices soaring.

  2. F

    All-Transactions House Price Index for the United States

    • fred.stlouisfed.org
    json
    Updated Aug 26, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (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.

  3. Crisis 2008-2009 Housing Data

    • kaggle.com
    zip
    Updated Aug 31, 2019
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ievgen Iosifov (2019). Crisis 2008-2009 Housing Data [Dataset]. https://www.kaggle.com/datasets/eiosifov/crisis-20082009-housing-data
    Explore at:
    zip(1727 bytes)Available download formats
    Dataset updated
    Aug 31, 2019
    Authors
    Ievgen Iosifov
    Description

    Context

    Data augmentation for housing prices

    Content

    US Housing Data for 2008-2009 (pre crisis and crisis year) to predict housing prices more accurate

    Inspiration

    Housing price prediction competition on Kaggle

  4. o

    Replication data for: A Real Estate Boom with Chinese Characteristics

    • openicpsr.org
    Updated Feb 1, 2017
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Edward Glaeser; Wei Huang; Yueran Ma; Andrei Shleifer (2017). Replication data for: A Real Estate Boom with Chinese Characteristics [Dataset]. http://doi.org/10.3886/E113990V1
    Explore at:
    Dataset updated
    Feb 1, 2017
    Dataset provided by
    American Economic Association
    Authors
    Edward Glaeser; Wei Huang; Yueran Ma; Andrei Shleifer
    Area covered
    China
    Description

    Chinese housing prices rose by over 10 percent per year in real terms between 2003 and 2014 and are now between two and ten times higher than the construction cost of apartments. At the same time, Chinese developers built 100 billion square feet of residential real estate. This boom has been accompanied by a large increase in the number of vacant homes, held by both developers and households. This boom may turn out to be a housing bubble followed by a crash, yet that future is far from certain. The demand for real estate in China is so strong that current prices might be sustainable, especially given the sparse alternative investments for Chinese households, so long as the level of new supply is radically curtailed. Whether that happens depends on the policies of the Chinese government, which must weigh the benefits of price stability against the costs of restricting urban growth.

  5. Great Recession: real house price index in Europe's weakest economies...

    • statista.com
    Updated Sep 2, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2024). Great Recession: real house price index in Europe's weakest economies 2005-2011 [Dataset]. https://www.statista.com/statistics/1348857/great-recession-house-price-bubbles-eu/
    Explore at:
    Dataset updated
    Sep 2, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2005 - 2011
    Area covered
    Europe
    Description

    Portugal, Italy, Ireland, Greece, and Spain were widely considered the Eurozone's weakest economies during the Great Recession and subsequent Eurozone debt crisis. These countries were grouped together due to the similarities in their economic crises, with much of them driven by house price bubbles which had inflated over the early 2000s, before bursting in 2007 due to the Global Financial Crisis. Entry into the Euro currency by 2002 had meant that banks could lend to house buyers in these countries at greatly reduced rates of interest.

    This reduction in the cost of financing contributed to creating housing bubbles, which were further boosted by pro-cyclical housing policies among many of the countries' governments. In spite of these economies experiencing similar economic problems during the crisis, Italy and Portugal did not experience housing bubbles in the same way in which Greece, Ireland, and Spain did. In the latter countries, their real housing prices (which are adjusted for inflation) peaked in 2007, before quickly declining during the recession. In particular, house prices in Ireland dropped by over 40 percent from their peak in 2007 to 2011.

  6. f

    S1 Data -

    • figshare.com
    xlsx
    Updated Sep 6, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Kwangwon Ahn; Minhyuk Jeong; Jinu Kim; Domenico Tarzia; Ping Zhang (2024). S1 Data - [Dataset]. http://doi.org/10.1371/journal.pone.0309483.s002
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Sep 6, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Kwangwon Ahn; Minhyuk Jeong; Jinu Kim; Domenico Tarzia; Ping Zhang
    License

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

    Description

    Housing markets are often characterized by price bubbles, and governments have instituted policies to stabilize them. Under this circumstance, this study addresses the following questions. (1) Does policy tightening change expectations in housing prices, revealing a regime change? (2) If so, what determines the housing market’s reaction to policy tightening? To answer these questions, we examine the effects of policy tightening that occurred in 2016 on the Chinese housing market where a price boom persisted in the post-2000 period. Using a log-periodic power law model and employing a modified multi-population genetic algorithm for parameter estimation, we find that tightening policy in China did not cause a market crash; instead, shifting the Chinese housing market from faster-than-exponential growth to a soft landing. We attribute this regime shift to low sensitivity in the Chinese housing market to global perturbations. Our findings suggest that government policies can help stabilize housing prices and improve market conditions when implemented expediently. Moreover, policymakers should consider preparedness for the possibility of an economic crisis and other social needs (e.g., housing affordability) for overall social welfare when managing housing price bubbles.

  7. Approximated hazard rate.

    • plos.figshare.com
    xls
    Updated Sep 6, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Kwangwon Ahn; Minhyuk Jeong; Jinu Kim; Domenico Tarzia; Ping Zhang (2024). Approximated hazard rate. [Dataset]. http://doi.org/10.1371/journal.pone.0309483.t005
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Sep 6, 2024
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Kwangwon Ahn; Minhyuk Jeong; Jinu Kim; Domenico Tarzia; Ping Zhang
    License

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

    Description

    Housing markets are often characterized by price bubbles, and governments have instituted policies to stabilize them. Under this circumstance, this study addresses the following questions. (1) Does policy tightening change expectations in housing prices, revealing a regime change? (2) If so, what determines the housing market’s reaction to policy tightening? To answer these questions, we examine the effects of policy tightening that occurred in 2016 on the Chinese housing market where a price boom persisted in the post-2000 period. Using a log-periodic power law model and employing a modified multi-population genetic algorithm for parameter estimation, we find that tightening policy in China did not cause a market crash; instead, shifting the Chinese housing market from faster-than-exponential growth to a soft landing. We attribute this regime shift to low sensitivity in the Chinese housing market to global perturbations. Our findings suggest that government policies can help stabilize housing prices and improve market conditions when implemented expediently. Moreover, policymakers should consider preparedness for the possibility of an economic crisis and other social needs (e.g., housing affordability) for overall social welfare when managing housing price bubbles.

  8. T

    United Kingdom House Price Index

    • tradingeconomics.com
    • it.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Aug 15, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    TRADING ECONOMICS (2025). United Kingdom House Price Index [Dataset]. https://tradingeconomics.com/united-kingdom/housing-index
    Explore at:
    json, excel, xml, csvAvailable download formats
    Dataset updated
    Aug 15, 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, 1983 - Aug 31, 2025
    Area covered
    United Kingdom
    Description

    Housing Index in the United Kingdom increased to 516.20 points in August from 514.60 points in July of 2025. This dataset provides - United Kingdom House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  9. U

    United States House Prices Growth

    • ceicdata.com
    Updated Feb 15, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com (2020). United States House Prices Growth [Dataset]. https://www.ceicdata.com/en/indicator/united-states/house-prices-growth
    Explore at:
    Dataset updated
    Feb 15, 2020
    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.

  10. T

    China Newly Built House Prices YoY Change

    • tradingeconomics.com
    • id.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    TRADING ECONOMICS, China Newly Built House Prices YoY Change [Dataset]. https://tradingeconomics.com/china/housing-index
    Explore at:
    xml, excel, csv, jsonAvailable 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
    Jan 31, 2011 - Jul 31, 2025
    Area covered
    China
    Description

    Housing Index in China decreased by 2.80 percent in July from -3.20 percent in June of 2025. This dataset provides the latest reported value for - China Newly Built House Prices YoY Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  11. F

    Average Sales Price of Houses Sold for the United States

    • fred.stlouisfed.org
    json
    Updated Jul 24, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (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.

  12. F

    All-Transactions House Price Index for North Dakota

    • fred.stlouisfed.org
    json
    Updated Aug 26, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2025). All-Transactions House Price Index for North Dakota [Dataset]. https://fred.stlouisfed.org/series/NDSTHPI
    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
    North Dakota
    Description

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

  13. f

    Unit root tests.

    • plos.figshare.com
    xls
    Updated Sep 6, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Kwangwon Ahn; Minhyuk Jeong; Jinu Kim; Domenico Tarzia; Ping Zhang (2024). Unit root tests. [Dataset]. http://doi.org/10.1371/journal.pone.0309483.t004
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Sep 6, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Kwangwon Ahn; Minhyuk Jeong; Jinu Kim; Domenico Tarzia; Ping Zhang
    License

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

    Description

    Housing markets are often characterized by price bubbles, and governments have instituted policies to stabilize them. Under this circumstance, this study addresses the following questions. (1) Does policy tightening change expectations in housing prices, revealing a regime change? (2) If so, what determines the housing market’s reaction to policy tightening? To answer these questions, we examine the effects of policy tightening that occurred in 2016 on the Chinese housing market where a price boom persisted in the post-2000 period. Using a log-periodic power law model and employing a modified multi-population genetic algorithm for parameter estimation, we find that tightening policy in China did not cause a market crash; instead, shifting the Chinese housing market from faster-than-exponential growth to a soft landing. We attribute this regime shift to low sensitivity in the Chinese housing market to global perturbations. Our findings suggest that government policies can help stabilize housing prices and improve market conditions when implemented expediently. Moreover, policymakers should consider preparedness for the possibility of an economic crisis and other social needs (e.g., housing affordability) for overall social welfare when managing housing price bubbles.

  14. T

    United States FHFA House Price Index

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    TRADING ECONOMICS, United States FHFA House Price Index [Dataset]. https://tradingeconomics.com/united-states/housing-index
    Explore at:
    xml, excel, json, csvAvailable 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
    Jan 31, 1991 - Jun 30, 2025
    Area covered
    United States
    Description

    Housing Index in the United States decreased to 433.80 points in June from 434.60 points in May 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.

  15. Number of existing homes sold in the U.S. 1995-2024, with a forecast until...

    • statista.com
    Updated Apr 28, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Number of existing homes sold in the U.S. 1995-2024, with a forecast until 2026 [Dataset]. https://www.statista.com/statistics/226144/us-existing-home-sales/
    Explore at:
    Dataset updated
    Apr 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The number of U.S. home sales in the United States declined in 2024, after soaring in 2021. A total of four million transactions of existing homes, including single-family, condo, and co-ops, were completed in 2024, down from 6.12 million in 2021. According to the forecast, the housing market is forecast to head for recovery in 2025, despite transaction volumes expected to remain below the long-term average. Why have home sales declined? The housing boom during the coronavirus pandemic has demonstrated that being a homeowner is still an integral part of the American dream. Nevertheless, sentiment declined in the second half of 2022 and Americans across all generations agreed that the time was not right to buy a home. A combination of factors has led to house prices rocketing and making homeownership unaffordable for the average buyer. A survey among owners and renters found that the high home prices and unfavorable economic conditions were the two main barriers to making a home purchase. People who would like to purchase their own home need to save up a deposit, have a good credit score, and a steady and sufficient income to be approved for a mortgage. In 2022, mortgage rates experienced the most aggressive increase in history, making the total cost of homeownership substantially higher. Are U.S. home prices expected to fall? The median sales price of existing homes stood at 413,000 U.S. dollars in 2024 and was forecast to increase slightly until 2026. The development of the S&P/Case Shiller U.S. National Home Price Index shows that home prices experienced seven consecutive months of decline between June 2022 and January 2023, but this trend reversed in the following months. Despite mild fluctuations throughout the year, home prices in many metros are forecast to continue to grow, albeit at a much slower rate.

  16. U.S. metro areas at highest risk of a housing downturn in recession 2019

    • statista.com
    Updated Jul 18, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). U.S. metro areas at highest risk of a housing downturn in recession 2019 [Dataset]. https://www.statista.com/statistics/1091659/housing-market-metro-highest-risk-downturn-recession-usa/
    Explore at:
    Dataset updated
    Jul 18, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2019
    Area covered
    United States
    Description

    In a 2019 analysis, Riverside, California was the most at risk of a housing downturn in a recession out of the ** largest metro areas in the United States. The Californian metro area received an overall score of **** percent, which was compiled after factors such as home price volatility and average home loan-to-value ratio were examined.

  17. d

    Data from: Effect of the \"Xiong’an New Area\" policy on The Real estate...

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 19, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Li, Qi (2023). Effect of the \"Xiong’an New Area\" policy on The Real estate market in Beijing [Dataset]. http://doi.org/10.7910/DVN/YC9I68
    Explore at:
    Dataset updated
    Nov 19, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Li, Qi
    Area covered
    Beijing
    Description

    The establishment of Xiong’an New Area is an important decision for China to remove non-capital functions. The paper takes the “Xiong’an New Area” policy as a quasi-natural experiment and uses the Synthetic control method and the Difference-in-Difference method to study the influence of establishing Xiongan New Area on the quantity and price of new and second-hand housing markets in Beijing. The study finds that after the establishment of Xiongan New Area, the overall quantity of new houses in Beijing fall, while that of second-hand houses rise. The new housing price rises steadily, the second-hand housing price has an obvious downward trend. On whole, the "Xiong’an New Area" policy has a great influence on the second-hand housing quantity, the new housing price and the second-hand housing price index in Beijing. Based on the empirical results, in order to promote the rational development of Beijing's real estate market through the "Xiong’an New Area" policy, and to achieve the national policy goal of "no speculation on housing" and "housing for housing", we need to strengthen the planning and construction of the area.

  18. F

    All-Transactions House Price Index for California

    • fred.stlouisfed.org
    json
    Updated Aug 26, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (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.

  19. f

    The best fit of log-periodic power law parameters.

    • figshare.com
    xls
    Updated Sep 6, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Kwangwon Ahn; Minhyuk Jeong; Jinu Kim; Domenico Tarzia; Ping Zhang (2024). The best fit of log-periodic power law parameters. [Dataset]. http://doi.org/10.1371/journal.pone.0309483.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Sep 6, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Kwangwon Ahn; Minhyuk Jeong; Jinu Kim; Domenico Tarzia; Ping Zhang
    License

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

    Description

    The best fit of log-periodic power law parameters.

  20. T

    United States House Price Index MoM

    • tradingeconomics.com
    • ru.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Mar 15, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    TRADING ECONOMICS (2025). United States House Price Index MoM [Dataset]. https://tradingeconomics.com/united-states/house-price-index-mom
    Explore at:
    excel, xml, csv, jsonAvailable download formats
    Dataset updated
    Mar 15, 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
    Feb 28, 1991 - Jun 30, 2025
    Area covered
    United States
    Description

    House Price Index MoM in the United States decreased to -0.20 percent in June from -0.10 percent in May of 2025. This dataset includes a chart with historical data for the United States FHFA House Price Index MoM.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Statista (2025). Number of home sales in the U.S. 2014-2024 with forecast until 2026 [Dataset]. https://www.statista.com/statistics/275156/total-home-sales-in-the-united-states-from-2009/
Organization logo

Number of home sales in the U.S. 2014-2024 with forecast until 2026

Explore at:
Dataset updated
Jun 20, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
United States
Description

The number of home sales in the United States peaked in 2021 at almost ************* after steadily rising since 2018. Nevertheless, the market contracted in the following year, with transaction volumes falling to ***********. Home sales remained muted in 2024, with a mild increase expected in 2025 and 2026. A major factor driving this trend is the unprecedented increase in mortgage interest rates due to high inflation. How have U.S. home prices developed over time? The average sales price of new homes has also been rising since 2011. Buyer confidence seems to have recovered after the property crash, which has increased demand for homes and also the prices sellers are demanding for homes. At the same time, the affordability of U.S. homes has decreased. Both the number of existing and newly built homes sold has declined since the housing market boom during the coronavirus pandemic. Challenges in housing supply The number of housing units in the U.S. rose steadily between 1975 and 2005 but has remained fairly stable since then. Construction increased notably in the 1990s and early 2000s, with the number of construction starts steadily rising, before plummeting amid the infamous housing market crash. Housing starts slowly started to pick up in 2011, mirroring the economic recovery. In 2022, the supply of newly built homes plummeted again, as supply chain challenges following the COVID-19 pandemic and tariffs on essential construction materials such as steel and lumber led to prices soaring.

Search
Clear search
Close search
Google apps
Main menu