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

    • statista.com
    Updated Nov 29, 2025
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    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/
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    Dataset updated
    Nov 29, 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

    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
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    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. F

    All-Transactions House Price Index for the United States

    • fred.stlouisfed.org
    json
    Updated Nov 25, 2025
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    (2025). All-Transactions House Price Index for the United States [Dataset]. https://fred.stlouisfed.org/series/USSTHPI
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    jsonAvailable download formats
    Dataset updated
    Nov 25, 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 Q3 2025 about appraisers, HPI, housing, price index, indexes, price, and USA.

  4. 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/
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    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.

  5. c

    Data from: Comparing Two House-Price Booms

    • clevelandfed.org
    Updated Feb 27, 2024
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    Federal Reserve Bank of Cleveland (2024). Comparing Two House-Price Booms [Dataset]. https://www.clevelandfed.org/publications/economic-commentary/2024/ec-202404-comparing-two-house-price-booms
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    Dataset updated
    Feb 27, 2024
    Dataset authored and provided by
    Federal Reserve Bank of Cleveland
    Description

    In this Economic Commentary , we compare characteristics of the 2000–2006 house-price boom that preceded the Great Recession to the house-price boom that began in 2020 during the COVID-19 pandemic. These two episodes of high house-price growth have important differences, including the behavior of rental rates, the dynamics of housing supply and demand, and the state of the mortgage market. The absence of changes in fundamentals during the 2000s is consistent with the literature emphasizing house-price beliefs during this prior episode. In contrast to during the 2000s boom, changes in fundamentals (including rent and demand growth) played a more dominant role in the 2020s house-price boom.

  6. Data from: Why Didn't Canada's Housing Market Go Bust?

    • clevelandfed.org
    Updated Sep 9, 2009
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    Federal Reserve Bank of Cleveland (2009). Why Didn't Canada's Housing Market Go Bust? [Dataset]. https://www.clevelandfed.org/publications/economic-commentary/2009/ec-20090909-why-didnt-canadas-housing-market-go-bust
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    Dataset updated
    Sep 9, 2009
    Dataset authored and provided by
    Federal Reserve Bank of Clevelandhttps://www.clevelandfed.org/
    Area covered
    Canada
    Description

    Housing markets in the United States and Canada are similar in many respects, but each has fared quite differently since the onset of the financial crisis. A comparison of the two markets suggests that relaxed lending standards likely played a critical role in the U.S. housing bust.

  7. U

    Inflation Data

    • dataverse-staging.rdmc.unc.edu
    • dataverse.unc.edu
    Updated Oct 9, 2022
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    Linda Wang; Linda Wang (2022). Inflation Data [Dataset]. http://doi.org/10.15139/S3/QA4MPU
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    Dataset updated
    Oct 9, 2022
    Dataset provided by
    UNC Dataverse
    Authors
    Linda Wang; Linda Wang
    License

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

    Description

    This is not going to be an article or Op-Ed about Michael Jordan. Since 2009 we've been in the longest bull-market in history, that's 11 years and counting. However a few metrics like the stock market P/E, the call to put ratio and of course the Shiller P/E suggest a great crash is coming in-between the levels of 1929 and the dot.com bubble. Mean reversion historically is inevitable and the Fed's printing money experiment could end in disaster for the stock market in late 2021 or 2022. You can read Jeremy Grantham's Last Dance article here. You are likely well aware of Michael Burry's predicament as well. It's easier for you just to skim through two related videos on this topic of a stock market crash. Michael Burry's Warning see this YouTube. Jeremy Grantham's Warning See this YouTube. Typically when there is a major event in the world, there is a crash and then a bear market and a recovery that takes many many months. In March, 2020 that's not what we saw since the Fed did some astonishing things that means a liquidity sloth and the risk of a major inflation event. The pandemic represented the quickest decline of at least 30% in the history of the benchmark S&P 500, but the recovery was not correlated to anything but Fed intervention. Since the pandemic clearly isn't disappearing and many sectors such as travel, business travel, tourism and supply chain disruptions appear significantly disrupted - the so-called economic recovery isn't so great. And there's this little problem at the heart of global capitalism today, the stock market just keeps going up. Crashes and corrections typically occur frequently in a normal market. But the Fed liquidity and irresponsible printing of money is creating a scenario where normal behavior isn't occurring on the markets. According to data provided by market analytics firm Yardeni Research, the benchmark index has undergone 38 declines of at least 10% since the beginning of 1950. Since March, 2020 we've barely seen a down month. September, 2020 was flat-ish. The S&P 500 has more than doubled since those lows. Look at the angle of the curve: The S&P 500 was 735 at the low in 2009, so in this bull market alone it has gone up 6x in valuation. That's not a normal cycle and it could mean we are due for an epic correction. I have to agree with the analysts who claim that the long, long bull market since 2009 has finally matured into a fully-fledged epic bubble. There is a complacency, buy-the dip frenzy and general meme environment to what BigTech can do in such an environment. The weight of Apple, Amazon, Alphabet, Microsoft, Facebook, Nvidia and Tesla together in the S&P and Nasdaq is approach a ridiculous weighting. When these stocks are seen both as growth, value and companies with unbeatable moats the entire dynamics of the stock market begin to break down. Check out FANG during the pandemic. BigTech is Seen as Bullet-Proof me valuations and a hysterical speculative behavior leads to even higher highs, even as 2020 offered many younger people an on-ramp into investing for the first time. Some analysts at JP Morgan are even saying that until retail investors stop charging into stocks, markets probably don’t have too much to worry about. Hedge funds with payment for order flows can predict exactly how these retail investors are behaving and monetize them. PFOF might even have to be banned by the SEC. The risk-on market theoretically just keeps going up until the Fed raises interest rates, which could be in 2023! For some context, we're more than 1.4 years removed from the bear-market bottom of the coronavirus crash and haven't had even a 5% correction in nine months. This is the most over-priced the market has likely ever been. At the night of the dot-com bubble the S&P 500 was only 1,400. Today it is 4,500, not so many years after. Clearly something is not quite right if you look at history and the P/E ratios. A market pumped with liquidity produces higher earnings with historically low interest rates, it's an environment where dangerous things can occur. In late 1997, as the S&P 500 passed its previous 1929 peak of 21x earnings, that seemed like a lot, but nothing compared to today. For some context, the S&P 500 Shiller P/E closed last week at 38.58, which is nearly a two-decade high. It's also well over double the average Shiller P/E of 16.84, dating back 151 years. So the stock market is likely around 2x over-valued. Try to think rationally about what this means for valuations today and your favorite stock prices, what should they be in historical terms? The S&P 500 is up 31% in the past year. It will likely hit 5,000 before a correction given the amount of added liquidity to the system and the QE the Fed is using that's like a huge abuse of MMT, or Modern Monetary Theory. This has also lent to bubbles in the housing market, crypto and even commodities like Gold with long-term global GDP meeting many headwinds in the years ahead due to a...

  8. T

    United Kingdom House Price Index

    • tradingeconomics.com
    • it.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Oct 15, 2025
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    TRADING ECONOMICS (2025). United Kingdom House Price Index [Dataset]. https://tradingeconomics.com/united-kingdom/housing-index
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    json, excel, xml, csvAvailable download formats
    Dataset updated
    Oct 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 - Oct 31, 2025
    Area covered
    United Kingdom
    Description

    Housing Index in the United Kingdom increased to 517.10 points in October from 514.20 points in September of 2025. This dataset provides - United Kingdom House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  9. Annual change of housing consumer price in U.S. cities 2000-2024

    • statista.com
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    Statista, Annual change of housing consumer price in U.S. cities 2000-2024 [Dataset]. https://www.statista.com/statistics/196606/change-of-us-housing-consumer-price-index-since-2000/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The consumer price of housing in urban areas of the United States increased by over four percent in 2024. 2022 and 2023 saw the largest price increases on a year-over-year basis since 2000. Meanwhile, 2010 was the only year in which housing prices decreased. One of the main reasons for that may have been the subprime mortgage crisis of 2007. During that period, the value of new residential construction put in place in the U.S. stagnated.

  10. Residential Real Estate in China - Market Research Report (2015-2030)

    • ibisworld.com
    Updated Apr 15, 2025
    + more versions
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    IBISWorld (2025). Residential Real Estate in China - Market Research Report (2015-2030) [Dataset]. https://www.ibisworld.com/china/market-research-reports/residential-real-estate-industry/
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    Dataset updated
    Apr 15, 2025
    Dataset authored and provided by
    IBISWorld
    License

    https://www.ibisworld.com/about/termsofuse/https://www.ibisworld.com/about/termsofuse/

    Time period covered
    2015 - 2030
    Area covered
    China
    Description

    Revenue for the Residential Real Estate industry in China is expected to decrease at a CAGR of 9.8% over the five years through 2025. This trend includes an expected decrease of 9.6% in the current year.Since August 2020, the People's Bank of China and the China Banking and Insurance Regulatory Commission have proposed three debt indicators for real estate development and management companies through which the company's financial health can be rated. This new policy has exacerbated the company's debt pressure, making it unable to repay old debts by borrowing new debt. Some real estate companies faced a liquidity crisis.In 2022, the city's lockdown and laying-off caused by COVID-19 epidemic led to the pressure of delaying the delivery of houses. The industry's newly constructed and completed areas decreased significantly throughout the year. In addition, the epidemic has impacted sales in the industry, and some sales offices have been forced to close temporarily. In 2022, the residential sales area decreased by 26.8%, and the residential sales decreased by 31.2%.Industry revenue will recover at an annualized 0.7% over the five years through 2030. Over the next five years, the industry's drag on GDP will weaken, and industry growth will stabilize. However, high housing prices have become a major social problem in China. Under the measures on the principle that residential real estate is used for living, not speculation, the financial attributes of real estate will gradually weaken, and housing prices will tend to stabilize.

  11. Approximated hazard rate.

    • plos.figshare.com
    xls
    Updated Sep 6, 2024
    + more versions
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    Kwangwon Ahn; Minhyuk Jeong; Jinu Kim; Domenico Tarzia; Ping Zhang (2024). Approximated hazard rate. [Dataset]. http://doi.org/10.1371/journal.pone.0309483.t005
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    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.

  12. T

    China Newly Built House Prices YoY Change

    • tradingeconomics.com
    • id.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Nov 14, 2025
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    TRADING ECONOMICS (2025). China Newly Built House Prices YoY Change [Dataset]. https://tradingeconomics.com/china/housing-index
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    xml, excel, csv, jsonAvailable download formats
    Dataset updated
    Nov 14, 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, 2011 - Oct 31, 2025
    Area covered
    China
    Description

    Housing Index in China remained unchanged at -2.20 percent in October. 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.

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

    • statista.com
    Updated Sep 2, 2024
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    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/
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    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.

  14. Crisis 2008-2009 Housing Data

    • kaggle.com
    zip
    Updated Aug 31, 2019
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    Ievgen Iosifov (2019). Crisis 2008-2009 Housing Data [Dataset]. https://www.kaggle.com/eiosifov/crisis-20082009-housing-data
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    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

  15. Dow Jones: monthly value 1920-1955

    • statista.com
    Updated Jun 27, 2022
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    Statista (2022). Dow Jones: monthly value 1920-1955 [Dataset]. https://www.statista.com/statistics/1249670/monthly-change-value-dow-jones-depression/
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    Dataset updated
    Jun 27, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 1920 - Dec 1955
    Area covered
    United States
    Description

    Throughout the 1920s, prices on the U.S. stock exchange rose exponentially, however, by the end of the decade, uncontrolled growth and a stock market propped up by speculation and borrowed money proved unsustainable, resulting in the Wall Street Crash of October 1929. This set a chain of events in motion that led to economic collapse - banks demanded repayment of debts, the property market crashed, and people stopped spending as unemployment rose. Within a year the country was in the midst of an economic depression, and the economy continued on a downward trend until late-1932.

    It was during this time where Franklin D. Roosevelt (FDR) was elected president, and he assumed office in March 1933 - through a series of economic reforms and New Deal policies, the economy began to recover. Stock prices fluctuated at more sustainable levels over the next decades, and developments were in line with overall economic development, rather than the uncontrolled growth seen in the 1920s. Overall, it took over 25 years for the Dow Jones value to reach its pre-Crash peak.

  16. Forecast house price growth in the UK 2025-2029

    • statista.com
    Updated Nov 29, 2025
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    Statista (2025). Forecast house price growth in the UK 2025-2029 [Dataset]. https://www.statista.com/statistics/376079/uk-house-prices-forecast/
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    Dataset updated
    Nov 29, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United Kingdom
    Description

    After a period of rapid increase, house price growth in the UK has moderated. In 2025, house prices are forecast to increase by ****percent. Between 2025 and 2029, the average house price growth is projected at *** percent. According to the source, home building is expected to increase slightly in this period, fueling home buying. On the other hand, higher borrowing costs despite recent easing of mortgage rates and affordability challenges may continue to suppress transaction activity. Historical house price growth in the UK House prices rose steadily between 2015 and 2020, despite minor fluctuations. In the following two years, prices soared, leading to the house price index jumping by about 20 percent. As the market stood in April 2025, the average price for a home stood at approximately ******* British pounds. Rents are expected to continue to grow According to another forecast, the prime residential market is also expected to see rental prices grow in the next five years. Growth is forecast to be stronger in 2025 and slow slightly until 2029. The rental market in London is expected to follow a similar trend, with Outer London slightly outperforming Central London.

  17. T

    Canada Average House Prices

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +12more
    csv, excel, json, xml
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    TRADING ECONOMICS, Canada Average House Prices [Dataset]. https://tradingeconomics.com/canada/average-house-prices
    Explore at:
    json, csv, xml, excelAvailable 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, 2005 - Oct 31, 2025
    Area covered
    Canada
    Description

    Average House Prices in Canada increased to 688800 CAD in October from 687600 CAD in September of 2025. This dataset includes a chart with historical data for Canada Average House Prices.

  18. Data from: Mitigating housing market shocks: an agent-based reinforcement...

    • tandf.figshare.com
    • datasetcatalog.nlm.nih.gov
    bin
    Updated Jul 10, 2024
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    Sedar Olmez; Alison Heppenstall; Jiaqi Ge; Corinna Elsenbroich; Dan Birks (2024). Mitigating housing market shocks: an agent-based reinforcement learning approach with implications for real-time decision support [Dataset]. http://doi.org/10.6084/m9.figshare.26232214.v1
    Explore at:
    binAvailable download formats
    Dataset updated
    Jul 10, 2024
    Dataset provided by
    Taylor & Francishttps://taylorandfrancis.com/
    Authors
    Sedar Olmez; Alison Heppenstall; Jiaqi Ge; Corinna Elsenbroich; Dan Birks
    License

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

    Description

    Research in modelling housing market dynamics using agent-based models (ABMs) has grown due to the rise of accessible individual-level data. This research involves forecasting house prices, analysing urban regeneration, and the impact of economic shocks. There is a trend towards using machine learning (ML) algorithms to enhance ABM decision-making frameworks. This study investigates exogenous shocks to the UK housing market and integrates reinforcement learning (RL) to adapt housing market dynamics in an ABM. Results show agents can learn real-time trends and make decisions to manage shocks, achieving goals like adjusting the median house price without pre-determined rules. This model is transferable to other housing markets with similar complexities. The RL agent adjusts mortgage interest rates based on market conditions. Importantly, our model shows how a central bank agent learned conservative behaviours in sensitive scenarios, aligning with a 2009 study, demonstrating emergent behavioural patterns.

  19. H

    Replication Data for: How Global is the Affordable Housing Crisis?...

    • dataverse.harvard.edu
    • search.dataone.org
    Updated Jul 1, 2020
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    Tom Coupe (2020). Replication Data for: How Global is the Affordable Housing Crisis? International Journal of Housing Markets and Analysis [Dataset]. http://doi.org/10.7910/DVN/NVGSV7
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 1, 2020
    Dataset provided by
    Harvard Dataverse
    Authors
    Tom Coupe
    License

    https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/NVGSV7https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/NVGSV7

    Description

    these are the Replication files for: How Global is the Affordable Housing Crisis? accepted by the International Journal of Housing Markets and Analysis

  20. F

    S&P CoreLogic Case-Shiller MA-Boston Home Price Index

    • fred.stlouisfed.org
    json
    Updated Nov 25, 2025
    + more versions
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    (2025). S&P CoreLogic Case-Shiller MA-Boston Home Price Index [Dataset]. https://fred.stlouisfed.org/series/BOXRSA
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    jsonAvailable download formats
    Dataset updated
    Nov 25, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-pre-approvalhttps://fred.stlouisfed.org/legal/#copyright-pre-approval

    Area covered
    Boston, Massachusetts
    Description

    Graph and download economic data for S&P CoreLogic Case-Shiller MA-Boston Home Price Index (BOXRSA) from Jan 1987 to Sep 2025 about Boston, NH, MA, HPI, housing, price index, indexes, price, and USA.

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

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Dataset updated
Nov 29, 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.

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