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

    • statista.com
    • ai-chatbox.pro
    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 May 27, 2025
    + more versions
    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
    May 27, 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 Q1 2025 about appraisers, HPI, housing, price index, indexes, price, and USA.

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

    • statista.com
    Updated Sep 2, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2024). 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
    Sep 2, 2024
    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.

  4. F

    Median Sales Price of Houses Sold for the United States

    • fred.stlouisfed.org
    json
    Updated Apr 23, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2025). Median Sales Price of Houses Sold for the United States [Dataset]. https://fred.stlouisfed.org/series/MSPUS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Apr 23, 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 Q1 2025 about sales, median, housing, and USA.

  5. U

    Inflation Data

    • dataverse.unc.edu
    • dataverse-staging.rdmc.unc.edu
    Updated Oct 9, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    UNC Dataverse (2022). Inflation Data [Dataset]. http://doi.org/10.15139/S3/QA4MPU
    Explore at:
    Dataset updated
    Oct 9, 2022
    Dataset provided by
    UNC Dataverse
    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 demographic shift of an ageing population and significant technological automation. So if you think that stocks or equities or ETFs are the best place to put your money in 2022, you might want to think again. The crash of the OTC and small-cap market since February 2021 has been quite an indication of what a correction looks like. According to the Motley Fool what happens after major downturns in the market historically speaking? In each of the previous four instances that the S&P 500's Shiller P/E shot above and sustained 30, the index lost anywhere from 20% to 89% of its value. So what's what we too are due for, reversion to the mean will be realistically brutal after the Fed's hyper-extreme intervention has run its course. Of course what the Fed stimulus has really done is simply allowed the 1% to get a whole lot richer to the point of wealth inequality spiraling out of control in the decades ahead leading us likely to a dystopia in an unfair and unequal version of BigTech capitalism. This has also led to a trend of short squeeze to these tech stocks, as shown in recent years' data. Of course the Fed has to say that's its done all of these things for the people, employment numbers and the labor market. Women in the workplace have been set behind likely 15 years in social progress due to the pandemic and the Fed's response. While the 89% lost during the Great Depression would be virtually impossible today thanks to ongoing intervention from the Federal Reserve and Capitol Hill, a correction of 20% to 50% would be pretty fair and simply return the curve back to a normal trajectory as interest rates going back up eventually in the 2023 to 2025 period. It's very unlikely the market has taken Fed tapering into account (priced-in), since the euphoria of a can't miss market just keeps pushing the markets higher. But all good things must come to an end. Earlier this month, the U.S. Bureau of Labor Statistics released inflation data from July. This report showed that the Consumer Price Index for All Urban Consumers rose 5.2% over the past 12 months. While the Fed and economists promise us this inflation is temporary, others are not so certain. As you print so much money, the money you have is worth less and certain goods cost more. Wage gains in some industries cannot be taken back, they are permanent - in the service sector like restaurants, hospitality and travel that have been among the hardest hit. The pandemic has led to a paradigm shift in the future of work, and that too is not temporary. The Great Resignation means white collar jobs with be more WFM than ever before, with a new software revolution, different transport and energy behaviors and so forth. Climate change alone could slow down global GDP in the 21st century. How can inflation be temporary when so many trends don't appear to be temporary? Sure the price of lumber or used-cars could be temporary, but a global chip shortage is exasperating the automobile sector. The stock market isn't even behaving like it cares about anything other than the Fed, and its $billions of dollars of buying bonds each month. Some central banks will start to taper about December, 2021 (like the European). However Delta could further mutate into a variant that makes the first generation of vaccines less effective. Such a macro event could be enough to trigger the correction we've been speaking about. So stay safe, and keep your money safe. The Last Dance of the 2009 bull market could feel especially more painful because we've been spoiled for so long in the markets. We can barely remember what March, 2020 felt like. Some people sold their life savings simply due to scare tactics by the likes of Bill Ackman. His scare tactics on CNBC won him likely hundreds of millions as the stock market tanked. Hedge funds further gamed the Reddit and Gamestop movement, orchestrating them and leading the new retail investors into meme speculation and a whole bunch of other unsavory things like options trading at such scale we've never seen before. It's not just inflation and higher interest rates, it's how absurdly high valuations have become. Still correlation does not imply causation. Just because inflation has picked up, it doesn't guarantee that stocks will head lower. Nevertheless, weaker buying power associated with higher inflation can't be overlooked as a potential negative for the U.S. economy and equities. The current S&P500 10-year P/E Ratio is 38.7. This is 97% above the modern-era market average of 19.6, putting the current P/E 2.5 standard deviations above the modern-era average. This is just math, folks. History is saying the stock market is 2x its true value. So why and who would be full on the market or an asset class like crypto that is mostly speculative in nature to begin with? Study the following on a historical basis, and due your own due diligence as to the health of the markets: Debt-to-GDP ratio Call to put ratio

  6. T

    United Kingdom House Price Index

    • tradingeconomics.com
    • jp.tradingeconomics.com
    • +12more
    csv, excel, json, xml
    Updated May 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
    May 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 - May 31, 2025
    Area covered
    United Kingdom
    Description

    Housing Index in the United Kingdom decreased to 511.50 points in May from 513.50 points in April of 2025. This dataset provides - United Kingdom House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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

    • statista.com
    Updated Mar 20, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). 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/
    Explore at:
    Dataset updated
    Mar 20, 2025
    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.

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

    • ibisworld.com
    Updated Apr 1, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    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/
    Explore at:
    Dataset updated
    Apr 1, 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.

  9. F

    Real Residential Property Prices for China

    • fred.stlouisfed.org
    json
    Updated Jun 26, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2025). Real Residential Property Prices for China [Dataset]. https://fred.stlouisfed.org/series/QCNR628BIS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 26, 2025
    License

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

    Description

    Graph and download economic data for Real Residential Property Prices for China (QCNR628BIS) from Q2 2005 to Q1 2025 about China, residential, HPI, housing, real, price index, indexes, and price.

  10. Global real estate bubble risk 2024, by market

    • statista.com
    Updated Jun 23, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Global real estate bubble risk 2024, by market [Dataset]. https://www.statista.com/statistics/1060677/global-real-estate-bubble-risk/
    Explore at:
    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    Worldwide
    Description

    In 2024, Miami was the housing market most at risk, with a real estate bubble index score of ****. Tokyo and Zurich followed close behind with **** and ****, respectively. Any market with an index score of *** or higher was deemed to be a bubble risk zone.

  11. f

    S1 Data -

    • figshare.com
    xlsx
    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). 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.

  12. F

    Residential Property Prices for Japan

    • fred.stlouisfed.org
    json
    Updated Jun 26, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2025). Residential Property Prices for Japan [Dataset]. https://fred.stlouisfed.org/series/QJPN628BIS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 26, 2025
    License

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

    Area covered
    Japan
    Description

    Graph and download economic data for Residential Property Prices for Japan (QJPN628BIS) from Q1 1955 to Q4 2024 about Japan, residential, HPI, housing, price index, indexes, and price.

  13. Approximated hazard rate.

    • 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). 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.

  14. J

    Bubbles and Crises: The Role of House Prices and Credit (replication data)

    • journaldata.zbw.eu
    • jda-test.zbw.eu
    pdf, txt, zip
    Updated Dec 7, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    André K. Anundsen; Karsten R. Gerdrup; Frank Hansen; Kasper Kragh-Sørensen; André K. Anundsen; Karsten R. Gerdrup; Frank Hansen; Kasper Kragh-Sørensen (2022). Bubbles and Crises: The Role of House Prices and Credit (replication data) [Dataset]. http://doi.org/10.15456/jae.2022326.0700526408
    Explore at:
    zip(4237174), txt(10822), pdf(546815)Available download formats
    Dataset updated
    Dec 7, 2022
    Dataset provided by
    ZBW - Leibniz Informationszentrum Wirtschaft
    Authors
    André K. Anundsen; Karsten R. Gerdrup; Frank Hansen; Kasper Kragh-Sørensen; André K. Anundsen; Karsten R. Gerdrup; Frank Hansen; Kasper Kragh-Sørensen
    License

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

    Description

    This paper utilizes quarterly panel data for 20 OECD countries over the period 1975:Q1-2014:Q2 to explore the importance of house prices and credit in affecting the likelihood of a financial crisis. Estimating a set of multivariate logit models, we find that booms in credit to both households and non-financial enterprises are important to account for when evaluating the stability of the financial system. In addition, we find that global housing market developments have predictive power for domestic financial stability. Finally, econometric measures of bubble-like behavior in housing and credit markets enter with positive and highly significant coefficients. Specifically, we find that the probability of a crisis increases markedly when bubble-like behavior in house prices coincides with high household leverage.

  15. d

    Data from: Date-stamping US housing market explosivity

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 22, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Balcilar, Mehmet; Katzke, Nico; Gupta, Rangan (2023). Date-stamping US housing market explosivity [Dataset]. http://doi.org/10.7910/DVN/NSSIGL
    Explore at:
    Dataset updated
    Nov 22, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Balcilar, Mehmet; Katzke, Nico; Gupta, Rangan
    Description

    In this paper, the authors set out to date-stamp periods of US housing price explosivity for the period 1830–2013. They make use of several robust techniques that allow them to identify such periods by determining when prices start to exhibit explosivity with respect to its past behaviour and when it recedes to long term stable prices. The first technique used is the Generalized sup ADF (GSADF) test procedure developed by Phillips, Shi, and Yu (Testing for Multiple Bubbles: Historical Episodes of Exuberance and Collapse in the S&P 500, 2013), which allows the recursive identification of multiple periods of price explosivity. The second approach makes use of Robinson’s (Efficient Test of Nonstationary Hypotheses, 1994) test statistic, comparing the null of a unit root process against the alternative of speced orders of fractional integration. The analysis date-stamps several periods of US house price explosivity, allowing us to contextualize its historic relevance.

  16. 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/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

  17. 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.

  18. Case Shiller National Home Price Index in the U.S. 2015-2024, by month

    • statista.com
    • ai-chatbox.pro
    Updated Mar 4, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Case Shiller National Home Price Index in the U.S. 2015-2024, by month [Dataset]. https://www.statista.com/statistics/398370/case-shiller-national-home-price-index-monthly-usa/
    Explore at:
    Dataset updated
    Mar 4, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2015 - Dec 2024
    Area covered
    United States
    Description

    Home prices in the U.S. reach new heights The American housing market continues to show remarkable resilience, with the S&P/Case Shiller U.S. National Home Price Index reaching an all-time high of 325.78 in July 2024. This figure represents a significant increase from the index value of 166.24 recorded in January 2015, highlighting the substantial growth in home prices over the past decade. The S&P Case Shiller National Home Price Index is based on the prices of single-family homes and is the leading indicator of the American housing market and one of the indicators of the state of the broader economy. The S&P Case Shiller National Home Price Index series also includes S&P/Case Shiller 20-City Composite Home Price Index and S&P/Case Shiller 10-City Composite Home Price Index – measuring the home price changes in the major U.S. metropolitan areas, as well as twenty composite indices for the leading U.S. cities. Market fluctuations and recovery Despite the overall upward trend, the housing market has experienced some fluctuations in recent years. During the housing boom in 2021, the number of existing home sales reached the highest level since 2006. However, transaction volumes quickly plummeted, as the soaring interest rates and out-of-reach prices led to housing sentiment deteriorating. Factors influencing home prices Several factors have contributed to the rise in home prices, including a chronic supply shortage, the gradual decline in interest rates, and the spike in demand during the COVID-19 pandemic. During the subprime mortgage crisis (2007-2010), the construction of new homes declined dramatically. Although it has gradually increased since then, the number of new building permits, home starts, and completions are still shy from the levels before the crisis. With demand outweighing supply, competition for homes can be fierce, leading to bidding wars and soaring prices. The supply of existing homes is further constrained, as homeowners are less likely to sell and move homes due to the worsened lending conditions.

  19. f

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

    • tandf.figshare.com
    bin
    Updated Jul 10, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    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 & Francis
    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.

  20. d

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

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 22, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Coupe, Tom (2023). 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
    Explore at:
    Dataset updated
    Nov 22, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Coupe, Tom
    Description

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

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