The foreclosure rate in the United States has experienced significant fluctuations over the past two decades, reaching its peak in 2010 at **** percent following the financial crisis. Since then, the rate has steadily declined, with a notable drop to **** percent in 2021 due to government interventions during the COVID-19 pandemic. In 2025, the rate stood slightly higher at **** percent but remained well below historical averages, indicating a relatively stable housing market. Impact of economic conditions on foreclosures The foreclosure rate is closely tied to broader economic trends and housing market conditions. During the aftermath of the 2008 financial crisis, the share of non-performing mortgage loans climbed significantly, with loans 90 to 180 days past due reaching *** percent. Since then, the share of seriously delinquent loans has dropped notably, demonstrating a substantial improvement in mortgage performance. Among other things, the improved mortgage performance has to do with changes in the mortgage approval process. Homebuyers are subject to much stricter lending standards, such as higher credit score requirements. These changes ensure that borrowers can meet their payment obligations and are at a lower risk of defaulting and losing their home. Challenges for potential homebuyers Despite the low foreclosure rates, potential homebuyers face significant challenges in the current market. Homebuyer sentiment worsened substantially in 2021 and remained low across all age groups through 2024, with the 45 to 64 age group expressing the most negative outlook. Factors contributing to this sentiment include high housing costs and various financial obligations. For instance, in 2024, ** percent of non-homeowners reported that student loan expenses hindered their ability to save for a down payment.

Graph and download economic data for Large Bank Consumer Mortgage Balances: 30 or More Days Past Due: Including Foreclosures Rates: Balances Based (RCMFLBBALDPDPCT30P) from Q3 2012 to Q3 2025 about 30 days +, FR Y-14M, large, balance, mortgage, consumer, banks, depository institutions, rate, and USA.

The number of properties with foreclosure filings in the United States declined in 2024, but remained below the pre-pandemic level. Foreclosure filings were reported on approximately ******* properties, which was about ****** fewer than in 2023. Despite the decrease, 2024 saw one of the lowest foreclosure rates on record.

United States - Delinquency Rate on Loans Secured by Real Estate, Banks Ranked 1st to 100th Largest in Size by Assets was 1.87% in July of 2025, according to the United States Federal Reserve. Historically, United States - Delinquency Rate on Loans Secured by Real Estate, Banks Ranked 1st to 100th Largest in Size by Assets reached a record high of 11.49 in January of 2010 and a record low of 1.31 in October of 2004. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Delinquency Rate on Loans Secured by Real Estate, Banks Ranked 1st to 100th Largest in Size by Assets - last updated from the United States Federal Reserve on February of 2026.

This statistic shows the foreclosure rates of subprime conventional loans in the United States from 2000 to 2016. In 2016, 7.2 percent of subprime conventional loans were in foreclosure.

Graph and download economic data for Delinquency Rate on Single-Family Residential Mortgages, Booked in Domestic Offices, All Commercial Banks (DRSFRMACBS) from Q1 1991 to Q4 2025 about domestic offices, delinquencies, 1-unit structures, mortgage, residential, commercial, family, domestic, banks, depository institutions, rate, and USA.

Following the drastic increase directly after the COVID-19 pandemic, the delinquency rate started to gradually decline, falling below *** percent in the second quarter of 2023. In the second half of 2023, the delinquency rate picked up but remained stable throughout 2024. In the fourth quarter of 2025, **** percent of mortgage loans were delinquent. That was significantly lower than the **** percent during the onset of the COVID-19 pandemic in 2020 or the peak of *** percent during the subprime mortgage crisis of 2007-2010. What does the mortgage delinquency rate tell us? The mortgage delinquency rate is the share of the total number of mortgaged home loans in the U.S. where payment is overdue by 30 days or more. Many borrowers eventually manage to service their loan, though, as indicated by the markedly lower foreclosure rates. Total home mortgage debt in the U.S. stood at almost ** trillion U.S. dollars in 2024. Not all mortgage loans are made equal ‘Subprime’ loans, being targeted at high-risk borrowers and generally coupled with higher interest rates to compensate for the risk. These loans have far higher delinquency rates than conventional loans. Defaulting on such loans was one of the triggers for the 2007-2010 financial crisis, with subprime delinquency rates reaching almost ** percent around this time. These higher delinquency rates translate into higher foreclosure rates, which peaked at just under ** percent of all subprime mortgages in 2011.

Graph and download economic data for Delinquency Rate on Commercial Real Estate Loans (Excluding Farmland), Booked in Domestic Offices, All Commercial Banks (DRCRELEXFACBS) from Q1 1991 to Q4 2025 about farmland, domestic offices, delinquencies, real estate, commercial, domestic, loans, banks, depository institutions, rate, and USA.

Between 2015 and 2017, Memphis, Tennessee had the highest eviction rate at *** percent. The metropolitan areas with the next highest eviction rates were Phoenix (Arizona), Atlanta (Georgia), Indianapolis (Indiana) and Dallas (Texas) in that period.

Why do evictions occur? Eviction rate refers to the share of renters who are legally removed from a rental property by their landlord, because rent is overdue, the tenant has breached a condition of the rental agreement or for other legally permitted reasons.

Higher rates in the South and Midwest Eviction rates tend to be higher in the South and Midwest of the country, because median incomes are low and foreclosure rates are high. Vacancy rates are consistently higher in the South and Midwest than in the Northeast and West, which means that landlords cannot afford to be as picky when choosing a tenant in the South and Midwest. Tenants who struggle to pay their rent have a much lower chance of being chosen as tenant in the more competitive rental markets, which also keeps the eviction rates lower in those areas.

To date, there has been little research on environmental factors to guide interventions and treatments to improve the health of persons aging with long-term physical disabilities. This project will begin to fill this gap in knowledge by examining the role of characteristics in the social and built environment as they interact with underlying impairments and activity limitations to either hinder or promote the full participation of individuals with physical disabilities in society. The project builds on previous work by linking multiple dimensions of the built and social environment to the health trajectories of individuals in the combined Medicare and Medicaid Data file over a period of 10 years (2007-2016). The project focuses on those neighborhood characteristics hypothesized to be related to healthy aging with physical disability, including the density of recreational centers, public transportation, and neighborhood socioeconomic indicators. Researchers examine indicators of neighborhood safety (based on local crime statistics), since fear of crime may discourage individuals from fully accessing resources in their neighborhood. Based on previous work which showed that snow and ice keep older adults homebound, researchers are also including measures of average temperature and precipitation. Measures of street connectivity tap the connected routes within communities, which may facilitate access to social and physical resources. In addition, socioeconomic disadvantage, racial residential segregation, home foreclosure rates, and low employment opportunities, capture the social environment. All the neighborhood built and social environment data has been made available to the larger research and user community through ICPSR (data sharing core). NaNDA is moving! ICPSR is in the process of curating NaNDA measures and adding them to our data holdings. The current version of most NaNDA data is available as a series in our general archive. For the time being, you can still find some data in the NaNDA repository on openICPSR.

The share of non-performing mortgage loans in the United States has declined significantly since the subprime mortgage crisis in 2008. After the burst of the housing bubble, the share of loans which were 90 to 180 days past due date climbed to *** percent. The fourth quarter of 2010 witnessed the highest rate of loans in foreclosure, bankruptcy, or deed-in-lieu, amounting to *** percent. Between the first quarter of 2022 and the second quarter of 2025, the foreclosure rate stood at *** percent - the lowest figures on record. It increased to *** percent in the third quarter of 2025. Meanwhile, the 30 to 60 days delinquency rate rose to *** percent and the 90 to 180 days delinquency rate remained at *** percent.

The year 2021 saw the peak in issuance of residential mortgage backed securities (MBS), at *** trillion U.S. dollars. Since then, MBS issuance has slowed, reaching *** trillion U.S. dollars in 2025. What are mortgage backed securities? A mortgage backed security is a financial instrument in which mortgages are bundled together and sold to investors. The idea is that the risk of these individual mortgages is pooled when they are packaged together. This is a sound investment policy, unless the foreclosure rate increases significantly in a short amount of time. Mortgage risk Since mortgages are loans backed by an asset, the house, the risk is often considered relatively low. However, the loan maturities are very long, sometimes decades, meaning lenders must factor in the risk of a shift in the economic climate. As such, interest rates on longer mortgages tend to be higher than on shorter loans. The ten-year treasury yield influences these rates, since it is a long-term rate that most investors accept as risk-free. Additionally, a decline in the value of homeowner equity could lead to a situation where the debtor is “underwater” and owes more than the home is worth.

Reference: https://www.zillow.com/research/zhvi-methodology/

Official Background

In setting out to create a new home price index, a major problem Zillow sought to overcome in existing indices was their inability to deal with the changing composition of properties sold in one time period versus another time period. Both a median sale price index and a repeat sales index are vulnerable to such biases (see the analysis here for an example of how influential the bias can be). For example, if expensive homes sell at a disproportionately higher rate than less expensive homes in one time period, a median sale price index will characterize this market as experiencing price appreciation relative to the prior period of time even if the true value of homes is unchanged between the two periods.

The ideal home price index would be based off sale prices for the same set of homes in each time period so there was never an issue of the sales mix being different across periods. This approach of using a constant basket of goods is widely used, common examples being a commodity price index and a consumer price index. Unfortunately, unlike commodities and consumer goods, for which we can observe prices in all time periods, we can’t observe prices on the same set of homes in all time periods because not all homes are sold in every time period.

The innovation that Zillow developed in 2005 was a way of approximating this ideal home price index by leveraging the valuations Zillow creates on all homes (called Zestimates). Instead of actual sale prices on every home, the index is created from estimated sale prices on every home. While there is some estimation error associated with each estimated sale price (which we report here), this error is just as likely to be above the actual sale price of a home as below (in statistical terms, this is referred to as minimal systematic error). Because of this fact, the distribution of actual sale prices for homes sold in a given time period looks very similar to the distribution of estimated sale prices for this same set of homes. But, importantly, Zillow has estimated sale prices not just for the homes that sold, but for all homes even if they didn’t sell in that time period. From this data, a comprehensive and robust benchmark of home value trends can be computed which is immune to the changing mix of properties that sell in different periods of time (see Dorsey et al. (2010) for another recent discussion of this approach).

For an in-depth comparison of the Zillow Home Value Index to the Case Shiller Home Price Index, please refer to the Zillow Home Value Index Comparison to Case-Shiller

Each Zillow Home Value Index (ZHVI) is a time series tracking the monthly median home value in a particular geographical region. In general, each ZHVI time series begins in April 1996. We generate the ZHVI at seven geographic levels: neighborhood, ZIP code, city, congressional district, county, metropolitan area, state and the nation.

Underlying Data

Estimated sale prices (Zestimates) are computed based on proprietary statistical and machine learning models. These models begin the estimation process by subdividing all of the homes in United States into micro-regions, or subsets of homes either near one another or similar in physical attributes to one another. Within each micro-region, the models observe recent sale transactions and learn the relative contribution of various home attributes in predicting the sale price. These home attributes include physical facts about the home and land, prior sale transactions, tax assessment information and geographic location. Based on the patterns learned, these models can then estimate sale prices on homes that have not yet sold.

The sale transactions from which the models learn patterns include all full-value, arms-length sales that are not foreclosure resales. The purpose of the Zestimate is to give consumers an indication of the fair value of a home under the assumption that it is sold as a conventional, non-foreclosure sale. Similarly, the purpose of the Zillow Home Value Index is to give consumers insight into the home value trends for homes that are not being sold out of foreclosure status. Zillow research indicates that homes sold as foreclosures have typical discounts relative to non-foreclosure sales of between 20 and 40 percent, depending on the foreclosure saturation of the market. This is not to say that the Zestimate is not influenced by foreclosure resales. Zestimates are, in fact, influenced by foreclosure sales, but the pathway of this influence is through the downward pressure foreclosure sales put on non-foreclosure sale prices. It is the price signal observed in the latter that we are attempting to measure and, in turn, predict with the Zestimate.

Market Segments Within each region, we calculate the ZHVI for various subsets of homes (or mar...

The Real Estate Sales and Brokerage industry has faced headwinds recently, mainly because of high mortgage rates. Between 2022 and 2023, the Federal Reserve raised its benchmark interest rate 11 times to manage inflation. Although reduced several times since, the aftermath remains prevalent, with mortgage rates still significantly higher than the levels of 2019-2021. This has stifled homebuyer demand, resulting in reduced home sales and pressure on related sectors. Agents and brokers are adjusting to this new reality, with many would-be homeowners delaying or reconsidering their purchasing plans. The office market has also been impacted, facing high vacancy rates. Despite the challenges, there are indicators of resilience in the industry. Housing inventory has increased, alleviating some buying pressures and providing more options for buyers. Brokers and agents are shifting their strategies, focusing more on marketing and price negotiations. Home prices have continued to climb, benefiting agents and brokerages whose commission relies on selling prices. In the office market, despite an increase in vacancies, sales of buildings have been on the rise; brokers have found opportunities by focusing on high-quality assets, such as Class A office spaces. Nonetheless, because of the industry's robust performance from 2020 to 2021, revenue has climbed at a CAGR of 0.7% over the past five years, reaching $240.0 billion in 2025. 2025 revenue will climb an estimated 0.6% as home price appreciation and a rebound in commercial sales volume will fuel tepid growth. The 'higher for longer' mortgage rate environment will persist, but reductions in interest rates will make new building constructions less expensive, leading to a gain in apartment complex constructions and benefiting real estate professionals. Supply constraints will gradually ease as housing starts are projected to strengthen, resulting in a more balanced and sustainable market. The industry will also see technological advancements with a greater reliance on AI-driven lead generation, virtual staging and automated transaction tools. Federal efforts to alleviate housing shortages through regulatory reforms and the use of federal lands for housing construction may boost the industry. Overall, industry revenue will gain at a CAGR of 1.8% to reach $262.6 billion in 2030.

The mortgage delinquency rate for Federal Housing Administration (FHA) loans in the United States has declined since 2020, when it peaked at ***** percent. In the second quarter of 2025, ***** percent of FHA loans were delinquent. Historically, FHA mortgages have the highest delinquency rate of all mortgage types.

As a result of the coronavirus (COVID-19) crisis, many people worldwide faced job insecurity and loss of income. For mortgage borrowers in the United States, this means increased default and foreclosure risk. Forbearance is a type of borrower assistance which allows the lender to negotiate a temporary postponement of a mortgage repayment. It allows a payment period relief in lieu of the creditor foreclosing on any property that was used as collateral for the loan.

As of March 2022, New York was one of the states in the United States with highest forbearance rate for Freddie Mac single-family housing loans with approximately **** percent of current loans in forbearance.

Brief

The dataset contains key factors that could influence Residential home prices in the last 20 years in the United States. This factor falls into two categories i.e. Supply & Demand

The S&P Case-Shiller Housing Price Index(HPI) is taken as the y variable, or dependent variable, as an indicator of change in prices.

Supply_dataset(Monthly_data)

• Building Permits(Permit Number)-Number of building permits allotted
• Construction Spending (Million $)-The amount spent (in millions of USD) is a measure of the activity in the construction industry.
• Housing Starts(New Housing Project)-This is a measure of the number of units of new housing projects started in a given period.
• Homes Sold(units)-House for sale is a basic measure of supply.

Demand_dataset(Quaterly_data)

• Mortgage Rates(%)
• USA GDP(Billions$ )-Quarterly Real GDP (adjusted for inflation)
• Unemployment(%)
• Delinquency Rate(%) on Mortgages(Foreclosure on the mortgage)-an indicator of the number of foreclosures in real estate.

Inspiration

Building a Data Science model to find the factors which influenced the home prices the most in the last 20 years.

Summary

https://docs.google.com/presentation/d/1SFQg-cwu2JRr-85uvU1jYY4KDtTjqKuG/edit#slide=id.p3

Federal Housing Administration (FHA) loans had the highest delinquency rate in the United States in 2025. As of the second quarter of the year, ***** percent of the outstanding one-to-four family housing mortgage loans were ** days or more delinquent. This percentage was lower for conventional loans and Veterans Administration loans. Despite a slight increase, the delinquency rate for all mortgages was one of the lowest on record.

Land contracts are a way of buying a home without a mortgage. While not having a mortgage may sound good, these contracts usually have fewer protections than a mortgage. Read this article to learn more.