The foreclosure rate in the United States has experienced significant fluctuations over the past two decades, reaching its peak in 2010 at 2.23 percent following the financial crisis. Since then, the rate has steadily declined, with a notable drop to 0.11 percent in 2021 due to government interventions during the COVID-19 pandemic. In 2024, the rate stood slightly higher at 0.23 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 4.6 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 2023, 52 percent of non-homeowners reported that student loan expenses hindered their ability to save for a down payment.

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What is Foreclosure?

Foreclosure is the legal process of taking possession of a mortgaged property when the borrower fails to keep up with mortgage payments. The foreclosure process varies from state to state, depending on whether the state has a judicial or nonjudicial process. Judicial process requires court action on a foreclosed property, where a nonjudicial process does not.

Foreclosure and Pre-Foreclosure Data Includes:

• 9 Different types of Judicial vs Non-Judicial
• Auctions
• Public Notices
• Lis Pendens
• Releases
• Defendant and Plaintiff Names
• Recording Dates, Published Dates, and Auction Dates
• Original Mortgage Information

Monthly foreclosures in Connecticut by county, 2008 through the present. Data updated monthly by the Connecticut Housing Finance Authority and tracked in the following dashboard: https://www.chfa.org/about-us/ct-monthly-housing-market-dashboard/. CHFA has stopped maintaining the dashboard and associated datasets, and this dataset will no longer be updated as of 2022.

This statistic shows the foreclosure filings in the United States as of June 2017, by state. South Dakota had the lowest rate with only one in every 24,583 housing units being subject to foreclosure.

Gain unmatched access to data on all stages of the pre-foreclosure and foreclosure process from a single source.

In 2017, the County Department of Economic Development, in conjunction with Reinvestment Fund, completed the 2016 Market Value Analysis (MVA) for Allegheny County. A similar MVA was completed with the Pittsburgh Urban Redevelopment Authority in 2016. The Market Value Analysis (MVA) offers an approach for community revitalization; it recommends applying interventions not only to where there is a need for development but also in places where public investment can stimulate private market activity and capitalize on larger public investment activities. The MVA is a unique tool for characterizing markets because it creates an internally referenced index of a municipality’s residential real estate market. It identifies areas that are the highest demand markets as well as areas of greatest distress, and the various markets types between. The MVA offers insight into the variation in market strength and weakness within and between traditional community boundaries because it uses Census block groups as the unit of analysis. Where market types abut each other on the map becomes instructive about the potential direction of market change, and ultimately, the appropriateness of types of investment or intervention strategies.

The 2016 Allegheny County MVA does not include the City of Pittsburgh, which was characterized at the same time in the fourth update of the City of Pittsburgh’s MVA. All calculations herein therefore do not include the City of Pittsburgh. While the methodology between the City and County MVA's are very similar, the classification of communities will differ, and so the data between the two should not be used interchangeably.

Allegheny County's MVA utilized data that helps to define the local real estate market. Most data used covers the 2013-2016 period, and data used in the analysis includes:

•Residential Real Estate Sales; • Mortgage Foreclosures; • Residential Vacancy; • Parcel Year Built; • Parcel Condition; • Owner Occupancy; and • Subsidized Housing Units.

The MVA uses a statistical technique known as cluster analysis, forming groups of areas (i.e., block groups) that are similar along the MVA descriptors, noted above. The goal is to form groups within which there is a similarity of characteristics within each group, but each group itself different from the others. Using this technique, the MVA condenses vast amounts of data for the universe of all properties to a manageable, meaningful typology of market types that can inform area-appropriate programs and decisions regarding the allocation of resources.

During the research process, staff from the County and Reinvestment Fund spent an extensive amount of effort ensuring the data and analysis was accurate. In addition to testing the data, staff physically examined different areas to verify the data sets being used were appropriate indicators and the resulting MVA categories accurately reflect the market.

Please refer to the report (included here as a pdf) for more information about the data, methodology, and findings.

In 2021, Allegheny County Economic Development (ACED), in partnership with Urban Redevelopment Authority of Pittsburgh(URA), completed the a Market Value Analysis (MVA) for Allegheny County. This analysis services as both an update to previous MVA’s commissioned separately by ACED and the URA and combines the MVA for the whole of Allegheny County (inclusive of the City of Pittsburgh). The MVA is a unique tool for characterizing markets because it creates an internally referenced index of a municipality’s residential real estate market. It identifies areas that are the highest demand markets as well as areas of greatest distress, and the various markets types between. The MVA offers insight into the variation in market strength and weakness within and between traditional community boundaries because it uses Census block groups as the unit of analysis. Where market types abut each other on the map becomes instructive about the potential direction of market change, and ultimately, the appropriateness of types of investment or intervention strategies.

This MVA utilized data that helps to define the local real estate market. The data used covers the 2017-2019 period, and data used in the analysis includes:

• Residential Real Estate Sales
• Mortgage Foreclosures
• Residential Vacancy
• Parcel Year Built
• Parcel Condition
• Building Violations
• Owner Occupancy
• Subsidized Housing Units

The MVA uses a statistical technique known as cluster analysis, forming groups of areas (i.e., block groups) that are similar along the MVA descriptors, noted above. The goal is to form groups within which there is a similarity of characteristics within each group, but each group itself different from the others. Using this technique, the MVA condenses vast amounts of data for the universe of all properties to a manageable, meaningful typology of market types that can inform area-appropriate programs and decisions regarding the allocation of resources.

Please refer to the presentation and executive summary for more information about the data, methodology, and findings.

Monthly foreclosures in Connecticut by county, 2008 through the present. Data updated monthly by the Connecticut Housing Finance Authority and tracked in the following dashboard: https://www.chfa.org/about-us/ct-monthly-housing-market-dashboard/.

DisclaimerBefore using this layer, please review the 2018 Rochester Citywide Housing Market Study for the full background and context that is required for interpreting and portraying this data. Please click here to access the study. Please also note that the housing market typologies were based on analysis of property data from 2008 to 2018, and is a snapshot of market conditions within that time frame. For an accurate depiction of current housing market typologies, this analysis would need to be redone with the latest available data.About the DataThis is a webmap of a polygon feature layer containing the boundaries of all census blockgroups in the city of Rochester. Beyond the unique identifier fields including GEOID, the only other field is the housing market typology for that blockgroup. The map is visualized based on market typology score with strongest market in pink, and weakest market in dark blue.Information from the 2018 Housing Market Study- Housing Market TypologiesThe City of Rochester commissioned a Citywide Housing Market Study in 2018 as a technical study to help inform development of the City's new Comprehensive Plan, Rochester 2034 , and retained czb, LLC - a firm with national expertise based in Alexandria, VA - to perform the analysis.Any understanding of Rochester’s housing market – and any attempt to develop strategies to influence the market in ways likely to achieve community goals – must begin with recognition that market conditions in the city are highly uneven. On some blocks, competition for real estate is strong and expressed by pricing and investment levels that are above city averages. On other blocks, private demand is much lower and expressed by above average levels of disinvestment and physical distress. Still other blocks are in the middle – both in terms of condition of housing and prevailing prices. These block-by-block differences are obvious to most residents and shape their options, preferences, and actions as property owners and renters. And, importantly, these differences shape the opportunities and challenges that exist in each neighborhood, the types of policy and investment tools to utilize in response to specific needs, and the level and range of available resources, both public and private, to meet those needs. The City of Rochester has long appreciated that a one-size-fits-all approach to housing and neighborhood strategy is inadequate in such a diverse market environment, and that is no less true today. To concisely describe distinct market conditions and trends across the city in this study, a Housing Market Typology was developed using a wide range of indicators to gauge market health and investment behaviors. This section of the Citywide Housing Market Study introduces the typology and its components. In later sections, the typology is used as a tool for describing and understanding demographic and economic patterns within the city, the implications of existing market patterns on strategy development, and how existing or potential policy and investment tools relate to market conditions.Overview of Housing Market Typology PurposeThe Housing Market Typology in this study is a tool for understanding recent market conditions and variations within Rochester and informing housing and neighborhood strategy development. As with any typology, it is meant to simplify complex information into a limited number of meaningful categories to guide action. Local context and knowledge remain critical to understanding market conditions and should always be used alongside the typology to maximize its usefulness.Geographic Unit of Analysis The Block Group – a geographic unit determined by the U.S. Census Bureau – is the unit of analysis for this typology, which utilizes parcel-level data. There are over 200 Block Groups in Rochester, most of which cover a small cluster of city blocks and are home to between 600 and 3,000 residents. For this tool, the Block Group provides geographies large enough to have sufficient data to analyze and small enough to reveal market variations within small areas.Four Components for CalculationAnalysis of multiple datasets led to the identification of four typology components that were most helpful in drawing out market variations within the city:• Terms of Sale• Market Strength• Bank Foreclosures• Property DistressThose components are described one-by-one on in the full study document (LINK), with detailed methodological descriptions provided in the Appendix.A Spectrum of Demand The four components were folded together to create the Housing Market Typology. The seven categories of the typology describe a spectrum of housing demand – with lower scores indicating higher levels of demand, and higher scores indicating weaker levels of demand. Typology 1 are areas with the highest demand and strongest market, while typology 3 are the weakest markets. For more information please visit: https://www.cityofrochester.gov/HousingMarketStudy2018/

The number of housing units in the United States has grown year-on-year and in 2023, there were approximately 145 million homes. That was an increase of about 1.3 percent from the previous year - the highest annual increase recorded in the past 15 years. Homeownership in the U.S. Most of the housing stock in the U.S. is owner-occupied, meaning that the person who owns the home uses it as a primary residence. Homeownership is an integral part of the American Dream, with about two in three Americans living in an owner-occupied home. For older generations, the homeownership rate is even higher, showing that buying a home is an important milestone in life. Housing transactions slowing down During the coronavirus pandemic, the U.S. experienced a housing market boom and witnessed an increase in the number of homes sold. Since 2020, when the market peaked, new homes transactions have slowed down and so have the sales of existing homes. That has affected the development of home prices, with several states across the country experiencing a decline in house prices.

In late 2016, the URA, in conjunction with Reinvestment Fund, completed the 2016 Market Value Analysis (MVA) for the City of Pittsburgh. The Market Value Analysis (MVA) offers an approach for community revitalization; it recommends applying interventions not only to where there is a need for development but also in places where public investment can stimulate private market activity and capitalize on larger public investment activities. The MVA is a unique tool for characterizing markets because it creates an internally referenced index of a municipality’s residential real estate market. It identifies areas that are the highest demand markets as well as areas of greatest distress, and the various markets types between. The MVA offers insight into the variation in market strength and weakness within and between traditional neighborhood boundaries because it uses Census block groups as the unit of analysis. Where market types abut each other on the map becomes instructive about the potential direction of market change, and ultimately, the appropriateness of types of investment or intervention strategies. Pittsburgh’s 2016 MVA utilized data that helps to define the local real estate market between July, 2013 and June, 2016: • Median Sales Price • Variance of Sales Price • Percent Households Owner Occupied • Density of Residential Housing Units • Percent Rental with Subsidy • Foreclosures as a Percent of Sales • Permits as a Percent of Housing Units • Percent of Housing Units Built Before 1940 • Percent of Properties with Assessed Condition “Poor” or worse • Vacant Housing Units as a Percentage of Habitable Units The MVA uses a statistical technique known as cluster analysis, forming groups of areas (i.e., block groups) that are similar along the MVA descriptors, noted above. The goal is to form groups within which there is a similarity of characteristics within each group, but each group itself different from the others. Using this technique, the MVA condenses vast amounts of data for the universe of all properties to a manageable, meaningful typology of market types that can inform area-appropriate programs and decisions regarding the allocation of resources. During the research process, staff from the URA and Reinvestment Fund spent an extensive amount of effort ensuring the data and analysis was accurate. In addition to testing the data, staff physically examined different areas to verify the data sets being used were appropriate indicators and the resulting MVA categories accurately reflect the market.

The number of transactions in the residential real estate market in Italy decreased in 2023, after a slight surge the year before. With 709,591 property sales, 2023 saw one of the highest transaction activity during the observation period. When looking at regional figures, Lombardy accounted for almost one in four transactions in the residential real estate sector. Impact of the coronavirus pandemic on the market During the coronavirus pandemic, the market contracted, with the number of transactions falling by 7.7 percent. That was followed by home sales surging in 2021, by more than one third. The market slowed down in 2022, but all regions, except for Emilia Romagna, recorded an increase in terms of transactions value. When looking at absolute numbers, Lombardy performed the best: the transactions’ value in the residential real estate sector in the region amounted to approximately 31 billion euros. Lazio, Liguria, and Tuscany: the most expensive regions Lombardy might be leading in terms of total transactions value, but it is not the region with the most valuable residential properties. In fact, calculations about the average price of transactions in the sector reveal that Tuscany, Lazio and Aosta Valley have the most expensive properties in Italy. In 2023, all three regions registered an average transaction value of about 195,000 euros.

This article examines the federal response to mortgage distress during the Great Depression. It documents features of the housing cycle of the 1920s and early 1930s, focusing on the growth of mortgage debt and the subsequent sharp increase in mortgage defaults and foreclosures during the Depression. It summarizes the major federal initiatives to reduce foreclosures and reform mortgage market practices, focusing especially on the activities of the Home Owners' Loan Corporation (HOLC), which acquired and refinanced one million delinquent mortgages between 1933 and 1936. Because the conditions under which the HOLC operated were unusual, the author cautions against drawing strong policy lessons from the HOLC's activities. Nonetheless, similarities between the Great Depression and the recent episode suggest that a review of the historical experience can provide insights about alternative policies to relieve mortgage distress.

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 2024 about domestic offices, delinquencies, 1-unit structures, mortgage, family, residential, commercial, domestic, banks, depository institutions, rate, and USA.

Among the 30 markets with the largest inventory of industrial and logistics real estate, Orange County, CA had the lowest vacancy rate of one percent in the first quarter of 2024. Chicago, IL, the largest market by total inventory, ranked 13th, with 4.6 percent of industrial and logistics real estate vacant. Phoenix, AZ, was the market with the highest rate at almost 11 percent. Overall, the share of vacant industrial and logistics properties has increased since 2022.

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 Housing Inventory: Active Listing Count in Florida (ACTLISCOUFL) from Jul 2016 to Feb 2025 about active listing, FL, listing, and USA.

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 2024 about farmland, domestic offices, delinquencies, real estate, commercial, domestic, loans, banks, depository institutions, rate, and USA.

Since 1995, River City Housing (RCH) has developed and sold over 130 new construction and 91 acquisition/rehab single family homes to income-qualified, first-time homebuyers. We help to make purchasing one of our houses even more affordable by providing down payment assistance to our homebuyers to help cover their down payment, prepaids and closing costs. RCH actively entered the rehab market at the end of 2009 to meet the overwhelming availability of foreclosures in an effort to help stabilize a volatile housing market. Currently we have eight homes, both acquisition/rehabilitations and new construction, in process. We have proudly maintained a reputation for high quality workmanship and strongly support creating housing that is energy-efficient so it is safe and affordable at the time of purchase, and affordable long-term. It is our intention to help the owner avoid becoming cost burdened with costly maintenance and repairs, so we prioritize repairs and new installations on major mechanicals, roofs, electrical and plumbing systems, added insulation in attics and crawl spaces, and energy efficient doors, windows, and appliances.

River city Housing’s mission is to improve the quality of life for low and moderate-income families and strengthen neighborhoods by developing safe and affordable housing. We believe so strongly in homeownership because owners benefit by gaining equity through the property and value of their home, achieving housing stability for themselves and their families, and receiving all of the added benefits homeownership offers.

RCH is also fully committed to bridging the black wealth gap by increasing black home ownership, particularly for current and legacy residents in neighborhoods where redlining and other discriminatory policies were enacted to restrict homeownership. We are one of several organizations thinking innovatively about ways to develop more affordable housing options in these particular neighborhoods including but not limited to the creation of Louisville’s first Community Land Trust to support this effort.

https://wfpl.org/louisville-takes-steps-for-first-community-land-trust-an-affordable-housing-tool/