33 datasets found
  1. 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.

  2. Understanding the Dynamics and Implications of a Housing Market Recession...

    • kappasignal.com
    Updated May 25, 2023
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    KappaSignal (2023). Understanding the Dynamics and Implications of a Housing Market Recession (Forecast) [Dataset]. https://www.kappasignal.com/2023/05/understanding-dynamics-and-implications.html
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    Dataset updated
    May 25, 2023
    Dataset authored and provided by
    KappaSignal
    License

    https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html

    Description

    This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

    Understanding the Dynamics and Implications of a Housing Market Recession

    Financial data:

    • Historical daily stock prices (open, high, low, close, volume)

    • Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

    • Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

    Machine learning features:

    • Feature engineering based on financial data and technical indicators

    • Sentiment analysis data from social media and news articles

    • Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

    Potential Applications:

    • Stock price prediction

    • Portfolio optimization

    • Algorithmic trading

    • Market sentiment analysis

    • Risk management

    Use Cases:

    • Researchers investigating the effectiveness of machine learning in stock market prediction

    • Analysts developing quantitative trading Buy/Sell strategies

    • Individuals interested in building their own stock market prediction models

    • Students learning about machine learning and financial applications

    Additional Notes:

    • The dataset may include different levels of granularity (e.g., daily, hourly)

    • Data cleaning and preprocessing are essential before model training

    • Regular updates are recommended to maintain the accuracy and relevance of the data

  3. Home price change during recessions U.S. 1980-2019

    • statista.com
    Updated Jul 18, 2025
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    Statista (2025). Home price change during recessions U.S. 1980-2019 [Dataset]. https://www.statista.com/statistics/1091698/home-price-change-during-recessions-us/
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    Dataset updated
    Jul 18, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Home prices fell by **** percent during the Great Recession of 2007 to 2009 in the United States. However, such a significant decrease in prices did not happen in the other four recessions which have occurred since 1980.

  4. F

    Real Residential Property Prices for United States

    • fred.stlouisfed.org
    json
    Updated Jun 26, 2025
    + more versions
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    (2025). Real Residential Property Prices for United States [Dataset]. https://fred.stlouisfed.org/series/QUSR628BIS
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    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
    United States
    Description

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

  5. U.S. housing: Case Shiller National Home Price Index 2000-2024

    • statista.com
    Updated Apr 25, 2025
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    Statista (2025). U.S. housing: Case Shiller National Home Price Index 2000-2024 [Dataset]. https://www.statista.com/statistics/199360/case-shiller-national-home-price-index-for-the-us-since-2000/
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    Dataset updated
    Apr 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The year-end value of the S&P Case Shiller National Home Price Index amounted to 321.45 in 2024. The index value was equal to 100 as of January 2000, so if the index value is equal to 130 in a given year, for example, it means that the house prices increased by 30 percent since 2000. S&P/Case Shiller U.S. home indices – additional informationThe S&P Case Shiller National Home Price Index is calculated on a monthly basis and is based on the prices of single-family homes in nine U.S. Census divisions: New England, Middle Atlantic, East North Central, West North Central, South Atlantic, East South Central, West South Central, Mountain and Pacific. The index is the leading indicator of the American housing market and one of the indicators of the state of the broader economy. The index illustrates the trend of home prices and can be helpful during house purchase decisions. When house prices are rising, a house buyer might want to speed up the house purchase decision as the transaction costs can be much higher in the future. The S&P Case Shiller National Home Price Index has been on the rise since 2011.The S&P Case Shiller National Home Price Index is one of the indices included in the S&P/Case-Shiller Home Price Index Series. Other indices are the S&P/Case Shiller 20-City Composite Home Price Index, the S&P/Case Shiller 10-City Composite Home Price Index and twenty city composite indices.

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

    • statista.com
    Updated Jul 18, 2025
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    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/
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    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.

  7. o

    Replication data for: Unemployment Insurance as a Housing Market Stabilizer

    • openicpsr.org
    Updated Jan 1, 2018
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    Joanne W. Hsu; David A. Matsa; Brian T. Melzer (2018). Replication data for: Unemployment Insurance as a Housing Market Stabilizer [Dataset]. http://doi.org/10.3886/E116160V1
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    Dataset updated
    Jan 1, 2018
    Dataset provided by
    American Economic Association
    Authors
    Joanne W. Hsu; David A. Matsa; Brian T. Melzer
    Description

    This paper studies the impact of unemployment insurance (UI) on the housing market. Exploiting heterogeneity in UI generosity across US states and over time, we find that UI helps the unemployed avoid mortgage default. We estimate that UI expansions during the Great Recession prevented more than 1.3 million foreclosures and insulated home values from labor market shocks. The results suggest that policies that make mortgages more affordable can reduce foreclosures even when borrowers are severely underwater. An optimal UI policy during housing downturns would weigh, among other benefits and costs, the deadweight losses avoided from preventing mortgage defaults.

  8. F

    All-Transactions House Price Index for Reno, NV (MSA)

    • fred.stlouisfed.org
    json
    Updated May 27, 2025
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    (2025). All-Transactions House Price Index for Reno, NV (MSA) [Dataset]. https://fred.stlouisfed.org/series/ATNHPIUS39900Q
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    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
    Reno, Reno-Sparks, NV, Nevada
    Description

    Graph and download economic data for All-Transactions House Price Index for Reno, NV (MSA) (ATNHPIUS39900Q) from Q2 1978 to Q1 2025 about Reno, NV, appraisers, HPI, housing, price index, indexes, price, and USA.

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

    • statista.com
    Updated Sep 2, 2024
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    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/
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    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.

  10. Homeownership rate in the U.S. 1990-2024

    • statista.com
    • ai-chatbox.pro
    Updated Jun 20, 2025
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    Statista (2025). Homeownership rate in the U.S. 1990-2024 [Dataset]. https://www.statista.com/statistics/184902/homeownership-rate-in-the-us-since-2003/
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    Dataset updated
    Jun 20, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The homeownership rate in the United States declined slightly in 2023 and remained stable in 2024. The U.S. homeownership rate was the highest in 2004 before the 2007-2009 recession hit and decimated the housing market. In 2024, the proportion of households occupied by owners stood at **** percent in 2024, *** percentage points below 2004 levels. Homeownership since the recession The rate of homeownership in the U.S. fell in the lead up to the recession and continued to do so until 2016. Despite this trend, the share of Americans who perceived homeownership as part of their personal American dream remained relatively stable. This suggests that the financial hardship caused by the recession led to the fall in homeownership, rather than a change in opinion about the importance of homeownership itself. What the future holds for homeownership Homeownership trends vary from generation to generation. Homeownership among Americans over 65 years old is declining, whereas most Millennial renters plan to buy a home in the near future. This suggests that homeownership will remain important in the future, as Millennials are forecast to head most households over the next two decades.

  11. US Residential Construction Market Analysis, Size, and Forecast 2025-2029

    • technavio.com
    Updated Jan 15, 2025
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    Technavio (2025). US Residential Construction Market Analysis, Size, and Forecast 2025-2029 [Dataset]. https://www.technavio.com/report/residential-construction-market-industry-analysis
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    Dataset updated
    Jan 15, 2025
    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    United States
    Description

    Snapshot img

    US Residential Construction Market Size 2025-2029

    The US residential construction market size is forecast to increase by USD 242.9 million at a CAGR of 4.5% between 2024 and 2029.

    The Residential Construction Market in the US is experiencing significant growth driven by increasing household formation rates and a rising focus on sustainability in new projects. According to the latest data, household formation is projected to continue growing at a steady pace, fueling the demand for new residential units. This trend is particularly evident in urban areas, where population growth and limited space for new development are driving up demand. Meanwhile, the emphasis on sustainability in residential construction is transforming the market landscape. With consumers increasingly prioritizing energy efficiency and eco-friendly features in their homes, builders and developers are responding by incorporating green technologies and sustainable materials into their projects.
    This shift not only appeals to environmentally-conscious consumers but also offers long-term cost savings and regulatory compliance benefits. However, the market is not without challenges. Skilled labor shortages continue to pose a significant hurdle for large-scale residential real estate projects. The ongoing shortage of skilled laborers, including carpenters, electricians, and plumbers, is driving up labor costs and delaying project timelines. To mitigate this challenge, some builders are exploring alternative solutions, such as modular construction and automation, to streamline their operations and reduce their reliance on traditional labor sources. The Residential Construction Market in the US presents significant opportunities for companies seeking to capitalize on the growing demand for new housing units and the shift towards sustainability.
    However, navigating the challenges of labor shortages and rising costs will require innovative solutions and strategic planning. By staying informed of market trends and adapting to evolving consumer preferences, companies can effectively position themselves for success in this dynamic market.
    

    What will be the size of the US Residential Construction Market during the forecast period?

    Request Free Sample

    The residential construction market in the United States continues to exhibit dynamic activity, driven by various economic factors. Housing supply remains a key focus, with ongoing discussions surrounding the affordable housing trend and efforts to increase inventory, particularly for single-family homes and new constructions. Mortgage and federal funds rates have an impact on residential investment, with fluctuations influencing buyer decisions and construction costs. The labor market plays a crucial role, as workforce availability and wages affect both housing starts and cancellation rates. Inflation and interest rates, monitored closely by the Federal Reserve, also shape the market's direction. Recession risks and economic conditions influence construction spending across various sectors, including multifamily and single-family homes.
    Federal programs, such as housing choice vouchers and fair housing initiatives, continue to support home buyers and promote equitable housing opportunities. Building permits and housing starts serve as essential indicators of market health and future growth, with some sectors experiencing double-digit growth. Overall, the residential construction market in the US remains a significant economic driver, shaped by a complex interplay of economic, demographic, and policy factors.
    

    How is this market segmented?

    The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

    Product
    
      Apartments and condominiums
      Luxury Homes
      Other types
    
    
    Type
    
      New construction
      Renovation
    
    
    Application
    
      Single family
      Multi-family
    
    
    Construction Material
    
      Wood-framed
      Concrete
      Steel
      Modular/Prefabricated
    
    
    Geography
    
      US
    

    By Product Insights

    The apartments and condominiums segment is estimated to witness significant growth during the forecast period.

    The residential construction market in the US is experiencing growth in both the apartment and condominium sectors, driven by the increasing trend toward urbanization and changing lifestyle preferences. Apartments, typically owned by property management companies, and condominiums, with individually owned units within a larger complex, contribute significantly to the market. The Federal Reserve's influence on the economy through the federal funds rate and mortgage rates impacts borrowing rates and home construction activity. The affordability of housing, particularly for younger generations, is a concern due to factors such as inflation, labor market conditions, and savings

  12. o

    Replication data for: The Effect of House Prices on Household Borrowing: A...

    • openicpsr.org
    Updated Jun 1, 2019
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    James Cloyne; Kilian Huber; Ethan Ilzetzki; Henrik Kleven (2019). Replication data for: The Effect of House Prices on Household Borrowing: A New Approach [Dataset]. http://doi.org/10.3886/E116205V1
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    Dataset updated
    Jun 1, 2019
    Dataset provided by
    American Economic Association
    Authors
    James Cloyne; Kilian Huber; Ethan Ilzetzki; Henrik Kleven
    Description

    We investigate the effect of house prices on household borrowing using administrative mortgage data from the United Kingdom and a new empirical approach. The data contain household-level information on house prices and borrowing in a panel of homeowners, who refinance at regular and quasi-exogenous intervals. The data and setting allow us to develop an empirical approach that exploits house price variation coming from the idiosyncratic and exogenous timing of refinance events around the Great Recession. We present two main results. First, there is a clear and robust effect of house prices on borrowing. Second, the effect of house prices on borrowing can be explained largely by collateral effects. We study the collateral channel through a multivariate and nonparametric heterogeneity analysis of proxies for collateral and wealth effects.

  13. Great Recession: delinquency rate by loan type in the U.S. 2007-2010

    • statista.com
    Updated Sep 2, 2024
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    Statista (2024). Great Recession: delinquency rate by loan type in the U.S. 2007-2010 [Dataset]. https://www.statista.com/statistics/1342448/global-financial-crisis-us-economic-indicators/
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    Dataset updated
    Sep 2, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2007 - 2012
    Area covered
    United States
    Description

    The Global Financial Crisis of 2008-09 was a period of severe macroeconomic instability for the United States and the global economy more generally. The crisis was precipitated by the collapse of a number of financial institutions who were deeply involved in the U.S. mortgage market and associated credit markets. Beginning in the Summer of 2007, a number of banks began to report issues with increasing mortgage delinquencies and the problem of not being able to accurately price derivatives contracts which were based on bundles of these U.S. residential mortgages. By the end of 2008, U.S. financial institutions had begun to fail due to their exposure to the housing market, leading to one of the deepest recessions in the history of the United States and to extensive government bailouts of the financial sector.

    Subprime and the collapse of the U.S. mortgage market

    The early 2000s had seen explosive growth in the U.S. mortgage market, as credit became cheaper due to the Federal Reserve's decision to lower interest rates in the aftermath of the 2001 'Dot Com' Crash, as well as because of the increasing globalization of financial flows which directed funds into U.S. financial markets. Lower mortgage rates gave incentive to financial institutions to begin lending to riskier borrowers, using so-called 'subprime' loans. These were loans to borrowers with poor credit scores, who would not have met the requirements for a conventional mortgage loan. In order to hedge against the risk of these riskier loans, financial institutions began to use complex financial instruments known as derivatives, which bundled mortgage loans together and allowed the risk of default to be sold on to willing investors. This practice was supposed to remove the risk from these loans, by effectively allowing credit institutions to buy insurance against delinquencies. Due to the fraudulent practices of credit ratings agencies, however, the price of these contacts did not reflect the real risk of the loans involved. As the reality of the inability of the borrowers to repay began to kick in during 2007, the financial markets which traded these derivatives came under increasing stress and eventually led to a 'sudden stop' in trading and credit intermediation during 2008.

    Market Panic and The Great Recession

    As borrowers failed to make repayments, this had a knock-on effect among financial institutions who were highly leveraged with financial instruments based on the mortgage market. Lehman Brothers, one of the world's largest investment banks, failed on September 15th 2008, causing widespread panic in financial markets. Due to the fear of an unprecedented collapse in the financial sector which would have untold consequences for the wider economy, the U.S. government and central bank, The Fed, intervened the following day to bailout the United States' largest insurance company, AIG, and to backstop financial markets. The crisis prompted a deep recession, known colloquially as The Great Recession, drawing parallels between this period and The Great Depression. The collapse of credit intermediation in the economy lead to further issues in the real economy, as business were increasingly unable to pay back loans and were forced to lay off staff, driving unemployment to a high of almost 10 percent in 2010. While there has been criticism of the U.S. government's actions to bailout the financial institutions involved, the actions of the government and the Fed are seen by many as having prevented the crisis from spiraling into a depression of the magnitude of The Great Depression.

  14. New monthly housing construction starts in the U.S. 1968-2025

    • statista.com
    Updated Jul 31, 2025
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    Statista (2025). New monthly housing construction starts in the U.S. 1968-2025 [Dataset]. https://www.statista.com/statistics/184487/us-new-privately-owned-housing-units-started-since-2000/
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    Dataset updated
    Jul 31, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 1968 - Jun 2025
    Area covered
    United States
    Description

    In June 2025, approximately ******* home construction projects started in the United States. The lowest point for housing starts over the past decade was in 2009, just after the 2007-2008 global financial crisis. Since 2010, the number of housing units started has been mostly increasing despite seasonal fluctuations. Statista also has a dedicated topic page on the U.S. housing market as a starting point for additional investigation on this topic. The impact of the global recession The same trend can be seen in home sales over the past two decades. The volume of U.S. home sales began to drop in 2005 and continued until 2010, after which home sales began to increase again. This dip in sales between 2005 and 2010 suggests that supply was outstripping demand, which led to decreased activity in the residential construction sector. Impact of recession on home buyers The financial crisis led to increased unemployment and pay cuts in most sectors, which meant that potential home buyers had less money to spend. The median income of home buyers in the U.S. fluctuated alongside the home sales and starts over the past decade.

  15. Great Recession: unemployment rate in the G7 countries 2007-2011

    • statista.com
    Updated Sep 2, 2024
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    Statista (2024). Great Recession: unemployment rate in the G7 countries 2007-2011 [Dataset]. https://www.statista.com/statistics/1346779/unemployment-rate-g7-great-recession/
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    Dataset updated
    Sep 2, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2007 - 2011
    Area covered
    Worldwide
    Description

    With the collapse of the U.S. housing market and the subsequent financial crisis on Wall Street in 2007 and 2008, economies across the globe began to enter into deep recessions. What had started out as a crisis centered on the United States quickly became global in nature, as it became apparent that not only had the economies of other advanced countries (grouped together as the G7) become intimately tied to the U.S. financial system, but that many of them had experienced housing and asset price bubbles similar to that in the U.S.. The United Kingdom had experienced a huge inflation of housing prices since the 1990s, while Eurozone members (such as Germany, France and Italy) had financial sectors which had become involved in reckless lending to economies on the periphery of the EU, such as Greece, Ireland and Portugal. Other countries, such as Japan, were hit heavily due their export-led growth models which suffered from the decline in international trade. Unemployment during the Great Recession As business and consumer confidence crashed, credit markets froze, and international trade contracted, the unemployment rate in the most advanced economies shot up. While four to five percent is generally considered to be a healthy unemployment rate, nearing full employment in the economy (when any remaining unemployment is not related to a lack of consumer demand), many of these countries experienced rates at least double that, with unemployment in the United States peaking at almost 10 percent in 2010. In large countries, unemployment rates of this level meant millions or tens of millions of people being out of work, which led to political pressures to stimulate economies and create jobs. By 2012, many of these countries were seeing declining unemployment rates, however, in France and Italy rates of joblessness continued to increase as the Euro crisis took hold. These countries suffered from having a monetary policy which was too tight for their economies (due to the ECB controlling interest rates) and fiscal policy which was constrained by EU debt rules. Left with the option of deregulating their labor markets and pursuing austerity policies, their unemployment rates remained over 10 percent well into the 2010s. Differences in labor markets The differences in unemployment rates at the peak of the crisis (2009-2010) reflect not only the differences in how economies were affected by the downturn, but also the differing labor market institutions and programs in the various countries. Countries with more 'liberalized' labor markets, such as the United States and United Kingdom experienced sharp jumps in their unemployment rate due to the ease at which employers can lay off workers in these countries. When the crisis subsided in these countries, however, their unemployment rates quickly began to drop below those of the other countries, due to their more dynamic labor markets which make it easier to hire workers when the economy is doing well. On the other hand, countries with more 'coordinated' labor market institutions, such as Germany and Japan, experiences lower rates of unemployment during the crisis, as programs such as short-time work, job sharing, and wage restraint agreements were used to keep workers in their jobs. While these countries are less likely to experience spikes in unemployment during crises, the highly regulated nature of their labor markets mean that they are slower to add jobs during periods of economic prosperity.

  16. Mortgage Brokers in the UK - Market Research Report (2015-2030)

    • ibisworld.com
    Updated Aug 25, 2024
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    IBISWorld (2024). Mortgage Brokers in the UK - Market Research Report (2015-2030) [Dataset]. https://www.ibisworld.com/united-kingdom/market-research-reports/mortgage-brokers-industry/
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    Dataset updated
    Aug 25, 2024
    Dataset authored and provided by
    IBISWorld
    License

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

    Time period covered
    2014 - 2029
    Area covered
    United Kingdom
    Description

    Mortgage brokers’ revenue is anticipated to climb at a compound annual rate of 4.5% over the five years through 2024-25 to £2.3 billion, including estimated growth of . Rising residential property transactions stimulated by government initiatives and rising house prices have driven industry growth. However, mortgage brokers have faced numerous obstacles, including downward pricing pressures from upstream lenders and a sharp downturn in the housing market as rising mortgage rates ramped up the cost of borrowing. After a standstill in residential real estate activity in the immediate aftermath of the COVID-19 outbreak, ultra-low base rates, the release of pent-up demand, the introduction of tax incentives and buyers reassessing their living situation fuelled a V-shaped recovery in the housing market. This meant new mortgage approvals for house purchases boomed going into 2021-22, ramping up demand for brokerage services. 2022-23 was a year rife with economic headwinds, from rising interest rates to fears of a looming recession. Yet, the housing market stood its ground, with brokers continuing to benefit from rising prices. Elevated mortgage rates eventually hit demand for houses in the first half of 2023, contributing to lacklustre house price growth in 2023-24, hurting revenue, despite a modest recovery in the second half of the year as mortgage rates came down. In 2024-25, lower mortgage rates and an improving economic outlook support house prices, driving revenue growth. Mortgage brokers’ revenue is anticipated to swell at a compound annual rate of 5.3% over the five years through 2029-30 to £2.9 billion. Competition from direct lending will ramp up. Yet, growth opportunities remain. The emergence of niche mortgage products, like those targeting retired individuals and contractors, as well as green mortgages, will support revenue growth in the coming years. AI is also set to transform the industry, improving cost efficiencies by automating tasks like document verification, risk assessment and customer profiling.

  17. United States: duration of recessions 1854-2024

    • statista.com
    Updated Jul 4, 2024
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    Statista (2024). United States: duration of recessions 1854-2024 [Dataset]. https://www.statista.com/statistics/1317029/us-recession-lengths-historical/
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    Dataset updated
    Jul 4, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The Long Depression was, by a large margin, the longest-lasting recession in U.S. history. It began in the U.S. with the Panic of 1873, and lasted for over five years. This depression was the largest in a series of recessions at the turn of the 20th century, which proved to be a period of overall stagnation as the U.S. financial markets failed to keep pace with industrialization and changes in monetary policy. Great Depression The Great Depression, however, is widely considered to have been the most severe recession in U.S. history. Following the Wall Street Crash in 1929, the country's economy collapsed, wages fell and a quarter of the workforce was unemployed. It would take almost four years for recovery to begin. Additionally, U.S. expansion and integration in international markets allowed the depression to become a global event, which became a major catalyst in the build up to the Second World War. Decreasing severity When comparing recessions before and after the Great Depression, they have generally become shorter and less frequent over time. Only three recessions in the latter period have lasted more than one year. Additionally, while there were 12 recessions between 1880 and 1920, there were only six recessions between 1980 and 2020. The most severe recession in recent years was the financial crisis of 2007 (known as the Great Recession), where irresponsible lending policies and lack of government regulation allowed for a property bubble to develop and become detached from the economy over time, this eventually became untenable and the bubble burst. Although the causes of both the Great Depression and Great Recession were similar in many aspects, economists have been able to use historical evidence to try and predict, prevent, or limit the impact of future recessions.

  18. o

    Replication data for: A Simple Model of Subprime Borrowers and Credit Growth...

    • openicpsr.org
    Updated May 1, 2016
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    Alejandro Justiniano; Giorgio E. Primiceri; Andrea Tambalotti (2016). Replication data for: A Simple Model of Subprime Borrowers and Credit Growth [Dataset]. http://doi.org/10.3886/E116314V1
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    Dataset updated
    May 1, 2016
    Dataset provided by
    American Economic Association
    Authors
    Alejandro Justiniano; Giorgio E. Primiceri; Andrea Tambalotti
    Time period covered
    Jan 2000 - Dec 2006
    Area covered
    United States
    Description

    The surge in credit and house prices that preceded the Great Recession was particularly pronounced in ZIP codes with a higher fraction of subprime borrowers (Mian and Sufi, 2009). We present a simple model with prime and subprime borrowers distributed across geographic locations, which can reproduce this stylized fact as a result of an expansion in the supply of credit. Due to their low income, subprime households are constrained in their ability to meet interest payments and hence sustain debt. As a result, when the supply of credit increases and interest rates fall, they take on disproportionately more debt than their prime counterparts, who are not subject to that constraint.

  19. United States Home Warranty Market Size By Product Type (Appliances-Only...

    • verifiedmarketresearch.com
    pdf,excel,csv,ppt
    Updated Jul 16, 2025
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    Verified Market Research (2025). United States Home Warranty Market Size By Product Type (Appliances-Only Plans, Systems-Only Plans), By Sales Channel (Direct-To-Consumer, Real Estate Agents/Brokers) And Forecast [Dataset]. https://www.verifiedmarketresearch.com/product/united-states-home-warranty-market/
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    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Jul 16, 2025
    Dataset authored and provided by
    Verified Market Researchhttps://www.verifiedmarketresearch.com/
    License

    https://www.verifiedmarketresearch.com/privacy-policy/https://www.verifiedmarketresearch.com/privacy-policy/

    Time period covered
    2026 - 2032
    Area covered
    North America, United States
    Description

    United States Home Warranty Market was valued at USD 4,262.56 Million in 2024 and is projected to reach USD 5,682.72 Million by 2032, growing at a CAGR of 4.19% from 2026 to 2032.The aging housing stock in the United States is a significant driver of growth for the U.S. Home Warranty Market, as a significant portion of homes now require ongoing repairs, system upgrades, and appliance replacements. This aging trend has accelerated in recent years, mainly due to a slowdown in new housing construction after the Great Recession, combined with persistent economic barriers including rising material costs, labor shortages, and elevated interest rates that have hampered the supply of newer homes. As a result, millions of homeowners now live-in homes built in earlier decades, creating a vast market need for repair-oriented services like home warranties.

  20. w

    Focus on London - Housing

    • data.wu.ac.at
    • data.europa.eu
    pdf, xls
    Updated Sep 26, 2015
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    London Datastore Archive (2015). Focus on London - Housing [Dataset]. https://data.wu.ac.at/odso/datahub_io/ODU0MDhlYWEtNDQyZS00ODllLWE1ZjEtNDllNzZmZjEwYTU0
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    xls(488448.0), pdf(1675677.0)Available download formats
    Dataset updated
    Sep 26, 2015
    Dataset provided by
    London Datastore Archive
    Area covered
    London
    Description

    FOCUSONLONDON2011: HOUSING:AGROWINGCITY

    With the highest average incomes in the country but the least space to grow, demand for housing in London has long outstripped supply, resulting in higher housing costs and rising levels of overcrowding. The pressures of housing demand in London have grown in recent years, in part due to fewer people leaving London to buy homes in other regions. But while new supply during the recession held up better in London than in other regions, it needs to increase significantly in order to meet housing needs and reduce housing costs to more affordable levels.

    This edition of Focus on London authored by James Gleeson in the Housing Unit looks at housing trends in London, from the demand/supply imbalance to the consequences for affordability and housing need.

    REPORT:

    Read the report in PDF format.

    https://londondatastore-upload.s3.amazonaws.com/fol/fol11-housing-cover-thumb.jpg" alt=""/>

    PRESENTATION:

    How much pressure is London’s popularity putting on housing provision in the capital? This interactive presentation looks at the effect on housing pressure of demographic changes, and recent new housing supply, shown by trends in overcrowding and house prices. Click on the start button at the bottom of the slide to access.

    View Focus on London - Housing: A Growing City on Prezi

    HISTOGRAM:

    This histogram shows a selection of borough data and helps show areas that are similar to one another by each indicator.

    Histogram

    MOTION CHART:

    This motion chart shows how the relationship, between key housing related indicators at borough level, changes over time.

    Motion Chart

    MAP:

    These interactive borough maps help to geographically present a range of housing data within London, as well as presenting trend data where available.

    MAP

    DATA:

    All the data contained within the Housing: A Growing City report as well as the data used to create the charts and maps can be accessed in this spreadsheet.

    FACTS:

    Some interesting facts from the data…

    ● Five boroughs with the highest proportion of households that have lived at their address for less than 12 months in 2009/10:

    1. Westminster – 19 per cent
    2. Wandsworth – 17 per cent
    3. Camden – 16 per cent
    4. Lambeth – 14 per cent
    5. Southwark – 13 per cent

    -31. Harrow – 6 per cent

    -32. Havering – 5 per cent

    ● Five boroughs with the highest percentage point increase between 2004 and 2009 of households in the ‘private rented’ sector:

    1. Newham – 17 per cent
    2. Greenwich – 11 per cent
    3. Enfield – 10 per cent
    4. Camden – 9 per cent
    5. Harrow – 8 per cent

    -32. Islington – 1 per cent

    -33. Bexley – 1 per cent

    ● Five boroughs with the highest percentage difference in median house prices between 2007 Q4 and 2010 Q4:

    1. Kensington & Chelsea – 29 per cent
    2. Westminster – 19 per cent
    3. Camden – 15 per cent
    4. Islington – 14 per cent
    5. Southwark – 10 per cent

    -31. Newham – down 9 per cent

    -32. Barking & D’ham – down 9 per cent

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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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Great Recession: real house price index in Europe's weakest economies 2005-2011

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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.

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