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.

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

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.

This paper studies the role of the Federal Reserve's policy in the recent boom and bust of the housing market, and in the ensuing recession. By estimating a structural dynamic factor model on a panel of 109 US quarterly variables from 1982 to 2010, we find that, although the Federal Reserve's policy between 2002 and 2004 was slightly expansionary, its contribution to the recent housing cycle was negligible. We also show that a more restrictive policy would have smoothed the cycle but not prevented the recession. We thus find no role for the Federal Reserve in causing the recession.

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.

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.

In a 2019 analysis, Riverside, California was the most at risk of a housing downturn in a recession out of the 50 largest metro areas in the United States. The Californian metro area received an overall score of 72.8 percent, which was compiled after factors such as home price volatility and average home loan-to-value ratio were examined.

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.

Looming Shadows: A Deep Dive into the 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

Home prices fell by 16.7 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.

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.

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.

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.

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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?

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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

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.

The Great Recession was a period of economic contraction which came in the wake of the Global Financial Crisis of 2007-2008. The recession was triggered by the collapse of the U.S. housing market and subsequent bankruptcies among Wall Street financial institutions, the most significant of which being the bankruptcy of Lehman Brothers in September 2008, the largest bankruptcy in U.S. history. These economic convulsions caused consumer confidence, measured by the Consumer Confidence Index (CCI), to drop sharply in 2007 and the beginning of 2008. How does the Consumer Confidence Index work? The CCI measures household's expectation of their future economic situation and, consequently, their likely future spending and savings decisions. A score of 100 in the index would indicate a neutral economic outlook, with consumers neither being optimistic nor pessimistic about the near future. Scores below 100 are then more pessimistic, while scores above 100 indicate optimism about the economy. Consumer confidence can have a self-fulfilling effect on the economy, as when consumers are pessimistic about the economy, they tend to save and postpone spending, contracting aggregate demand and causing the economy to slow down. Conversely, when consumers are optimistic and willing to spend, this can have a reinforcing effect as wages and employment may rise when consumers spend more. CCI and the Great Recession As the reality of the trouble which the U.S. financial sector was in set in over 2007, consumer confidence dropped sharply from being slightly positive, to being deeply pessimistic by the Summer of 2008. While confidence began to slowly rebound up until September 2008, with the panic caused by Lehman's bankruptcy and the freezing of new credit creation, the CCI plummeted once more, reaching its lowest point during the recession in February 2008. The U.S. government stepped in to prevent the bankruptcy of AIG in 2008, promising to do the same for any future possible failures in the financial system. This 'backstopping' policy, whereby the government assured that the economy would not be allowed to fall further into crisis, along with the Federal Reserve's unconventional monetary policies used to restart the economy, contributed to a rebound in consumer confidence in 2009 and 2010. In spite of this, consumers still remained pessimistic about the economy.

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.

In April 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.

To improve estimates of household consumption behavior, we extend a widely-used model by allowing for dynamic consumption elasticities with respect to transitory income shocks. Applying our model to biennial household survey data, we find a significant structural break in marginal propensities to consume from before to after the housing market boom and bust just prior to the Great Recession, with the average level for all households estimated to have increased by more than 40%. There is important heterogeneity across households grouped by different balance sheet characteristics and our results suggest the increase for all households was driven by higher short-run consumption elasticities for homeowners with low liquid wealth. The change appears to be related to tighter borrowing constraints for homeowners more than a shift in wealth distributions.

The U.S. Department of Energys Zero Energy Ready Home (ZERH) recognition program builds upon the building science requirements of ENERGY STAR Certified Homes, Version 3 and best practices tested by the Building America research and demonstration program. Multifamily units (units in buildings with five or more apartments) comprise an increasingly important segment in the U.S. new housing market. Over the past 30 years, this segment has averaged 24% of residential building permits and since the recession in 2008 averages 34% of new residential building permits. This study analyses two multifamily homes, one townhouse and one apartment. The study looks to improve the efficiency of these homes to meet ENERGY STAR standards. Apartment - 2 bedroom apartment unit Townhome - 3 bedroom townhome unit

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.