29 datasets found
  1. Foreclosure rate U.S. 2005-2024

    • statista.com
    Updated Jun 20, 2025
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    Statista (2025). Foreclosure rate U.S. 2005-2024 [Dataset]. https://www.statista.com/statistics/798766/foreclosure-rate-usa/
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    Dataset updated
    Jun 20, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    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 2024, 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 2023, ** percent of non-homeowners reported that student loan expenses hindered their ability to save for a down payment.

  2. Share of U.S. loans in foreclosure processes 2000-2024, by quarter

    • statista.com
    Updated Jul 11, 2025
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    Statista (2025). Share of U.S. loans in foreclosure processes 2000-2024, by quarter [Dataset]. https://www.statista.com/statistics/205983/total-loans-in-foreclosure-process-in-the-us-since-1990/
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    Dataset updated
    Jul 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In the second quarter of 2024, the share of mortgage loans in the foreclosure process in the U.S. decreased slightly to **** percent. Following the outbreak of the coronavirus crisis, mortgage delinquency rates spiked to the highest levels since the Subprime mortgage crisis (2007-2010). To prevent further impact on homeowners, Congress passed the CARES Act that provides foreclosure protections for borrowers with federally backed mortgage loans. As a result, the foreclosure rate fell to historically low levels.

  3. F

    Large Bank Consumer Mortgage Balances: 30 or More Days Past Due: Including...

    • fred.stlouisfed.org
    json
    Updated Jul 18, 2025
    + more versions
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    (2025). Large Bank Consumer Mortgage Balances: 30 or More Days Past Due: Including Foreclosures Rates: Balances Based [Dataset]. https://fred.stlouisfed.org/series/RCMFLBBALDPDPCT30P
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    jsonAvailable download formats
    Dataset updated
    Jul 18, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    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 Q1 2025 about 30 days +, FR Y-14M, large, balance, mortgage, consumer, banks, depository institutions, rate, and USA.

  4. Foreclosure rates on subprime conventional loans in the U.S. 2000-2016

    • statista.com
    Updated Jul 22, 2025
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    Statista (2025). Foreclosure rates on subprime conventional loans in the U.S. 2000-2016 [Dataset]. https://www.statista.com/statistics/206014/us-foreclosure-rates-on-subprime-conventional-loans-since-2000/
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    Dataset updated
    Jul 22, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    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.

  5. a

    2010 02: Housing Foreclosures In The Bay Area

    • hub.arcgis.com
    • opendata.mtc.ca.gov
    Updated Feb 24, 2010
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    MTC/ABAG (2010). 2010 02: Housing Foreclosures In The Bay Area [Dataset]. https://hub.arcgis.com/documents/8b420d1e0b4c4928ba7a602207f58899
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    Dataset updated
    Feb 24, 2010
    Dataset authored and provided by
    MTC/ABAG
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    San Francisco Bay Area
    Description

    Foreclosure types considered for this analysis include lender owned and third-party owned foreclosures as well as foreclosed properties ready for auction. Contra Costa and Solano counties showed the highest foreclosure rates in the San Francisco Bay Region during the first half of 2009 with up to 170 foreclosures per tract.

  6. r

    Neighborhood Stabilization Program (NSP) Target Areas

    • rigis.org
    Updated Nov 28, 2008
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    Environmental Data Center (2008). Neighborhood Stabilization Program (NSP) Target Areas [Dataset]. https://www.rigis.org/datasets/neighborhood-stabilization-program-nsp-target-areas-
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    Dataset updated
    Nov 28, 2008
    Dataset authored and provided by
    Environmental Data Center
    Area covered
    Description

    This hosted feature layer has been published in RI State Plane Feet NAD 83.The RI Neighborhood Stabilization Program (NSP) Mapping analysis was performed to assist the Office of Housing and Community Development in identifying target areas with both a Foreclosure Rate (Block Group Level) >=6.5% and a Subprime Loan percentage rate >= 1.4% (Zip Code Level). Based on these criteria the following communities were identified as containing such target areas: Central Falls, Cranston, Cumberland, East Providence, Johnston, North Providence, Pawtucket, Providence, Warwick, West Warwick, and Woonsocket. Federal funding, under the Housing and Economic Recovery Act of 2008 (HERA), Neighborhood Stabilization Program (NSP), totaling $19.6 will be expended in these NSP Target Areas to assist in the rehabilitation and redevelopment of abandoned and foreclosed homes, stabilizing communities.The State of Rhode Island distributes funds allocated, giving priority emphasis and consideration to those areas with the greatest need, including those areas with - 1) Highest percentage of home foreclosures; 2) Highest percentage of homes financed by subprime mortgage loans; and 3) Anticipated increases in rate of foreclosure. The RI Office of Housing and Community Development, with the assistance of Rhode Island Housing, utilized the following sources to meet the above requirements. 1) U.S. Department of Housing & Urban Development (HUD) developed foreclosure data to assist grantees in identification of Target Areas. The State utilized HUD's predictive foreclosure rates to identify those areas which are likely to face a significant rise in the rate of home foreclosures. HUD's methodology factored in Home Mortgage Disclosure Act, income, unemployment, and other information in its calculation. The results were analyzed and revealed a high level of consistency with other needs data available. 2) The State obtained subprime mortgage loan information from the Federal Reserve Bank of Boston. Though the data does not include all mortgages, and was only available at the zip code level rather than Census Tract, findings were generally consistent with other need categories. This data was joined to the Foreclosure dataset in order to select areas with both a Foreclosure Rate >=6.5% and a Subprime Loan Rate >=1.4%. 3) The State also obtained, from the Warren Group, actual local foreclosure transaction records. The Warren Group is a source for real estate and banking news and transaction data throughout New England. This entity has analyzed local deed records in assembling information presented. The data set was normalized due to potential limitations. An analysis revealed a high level of consistency with HUD-predictive foreclosure rates.

  7. F

    Nonfarm Real Estate Foreclosures for United States

    • fred.stlouisfed.org
    json
    Updated Aug 17, 2012
    + more versions
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    (2012). Nonfarm Real Estate Foreclosures for United States [Dataset]. https://fred.stlouisfed.org/series/M09075USM476NNBR
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    jsonAvailable download formats
    Dataset updated
    Aug 17, 2012
    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 Nonfarm Real Estate Foreclosures for United States (M09075USM476NNBR) from Jan 1934 to Mar 1963 about real estate, nonfarm, and USA.

  8. T

    United States - Delinquency Rate on Loans Secured by Real Estate, Banks...

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Apr 27, 2018
    + more versions
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    TRADING ECONOMICS (2018). United States - Delinquency Rate on Loans Secured by Real Estate, Banks Ranked 1st to 100th Largest in Size by Assets [Dataset]. https://tradingeconomics.com/united-states/delinquency-rate-on-loans-secured-by-real-estate-top-100-banks-ranked-by-assets-percent-fed-data.html
    Explore at:
    json, excel, csv, xmlAvailable download formats
    Dataset updated
    Apr 27, 2018
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    United States
    Description

    United States - Delinquency Rate on Loans Secured by Real Estate, Banks Ranked 1st to 100th Largest in Size by Assets was 1.94% in January 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 June of 2025.

  9. Mortgage delinquency rate in the U.S. 2000-2025, by quarter

    • statista.com
    • ai-chatbox.pro
    Updated May 27, 2025
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    Statista (2025). Mortgage delinquency rate in the U.S. 2000-2025, by quarter [Dataset]. https://www.statista.com/statistics/205959/us-mortage-delinquency-rates-since-1990/
    Explore at:
    Dataset updated
    May 27, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    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 first 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.

  10. d

    2011 Housing Market Typology.

    • datadiscoverystudio.org
    csv, json, rdf, xml
    Updated Feb 3, 2018
    + more versions
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    (2018). 2011 Housing Market Typology. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/ce139e562b2346ad8c64d799bc2eed7e/html
    Explore at:
    rdf, json, csv, xmlAvailable download formats
    Dataset updated
    Feb 3, 2018
    Description

    description: The Typology will assist city government, local foundations and non-profits to understand local market strengths and to appropriately match neighborhood strategies to market conditions, for the best use of public and private resources. In addition, the typology will inform neighborhood level planning efforts and provide residents with an understanding of the local housing market conditions in their communities. Regional Choice: Competitive housing markets with high owner-occupancy rates and high property values in comparison to all other market types. Foreclosure, vacancy and abandonment rates are low. Middle Market Choice: Housing prices above the city_s average with strong ownership rates, and low vacancies, but with slightly increased foreclosure rates. Middle Market: Median sales values of $91,000 (above the City_s average of $65,000) as well as high homeownership rates. These markets experienced higher foreclosure rates when compared to higher value markets, with slight population loss. Middle Market Stressed: Slightly lower home sale values than the City_s average, and have not shown significant sales price appreciation. Vacancies and foreclosure rates are high, and the rate of population loss has increased in this market type, according to the 2010 Census data. Distressed Market: , Have experienced significant deterioration of the housing stock. This market category contains the highest vacancy rates and the lowest homeownership rates, compared to the other market types. It also has experienced some of the most substantial population losses in the City during the past decade.; abstract: The Typology will assist city government, local foundations and non-profits to understand local market strengths and to appropriately match neighborhood strategies to market conditions, for the best use of public and private resources. In addition, the typology will inform neighborhood level planning efforts and provide residents with an understanding of the local housing market conditions in their communities. Regional Choice: Competitive housing markets with high owner-occupancy rates and high property values in comparison to all other market types. Foreclosure, vacancy and abandonment rates are low. Middle Market Choice: Housing prices above the city_s average with strong ownership rates, and low vacancies, but with slightly increased foreclosure rates. Middle Market: Median sales values of $91,000 (above the City_s average of $65,000) as well as high homeownership rates. These markets experienced higher foreclosure rates when compared to higher value markets, with slight population loss. Middle Market Stressed: Slightly lower home sale values than the City_s average, and have not shown significant sales price appreciation. Vacancies and foreclosure rates are high, and the rate of population loss has increased in this market type, according to the 2010 Census data. Distressed Market: , Have experienced significant deterioration of the housing stock. This market category contains the highest vacancy rates and the lowest homeownership rates, compared to the other market types. It also has experienced some of the most substantial population losses in the City during the past decade.

  11. T

    BAL_2011 Housing Market Typology

    • data.opendatanetwork.com
    application/rdfxml +5
    Updated May 9, 2014
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    (2014). BAL_2011 Housing Market Typology [Dataset]. https://data.opendatanetwork.com/w/5mq8-hzk8/default?cur=WFs1n7wQ2OA&from=9qaL08466kJ
    Explore at:
    tsv, csv, application/rssxml, json, xml, application/rdfxmlAvailable download formats
    Dataset updated
    May 9, 2014
    Description

    The Typology will assist city government, local foundations and non-profits to understand local market strengths and to appropriately match neighborhood strategies to market conditions, for the best use of public and private resources. In addition, the typology will inform neighborhood level planning efforts and provide residents with an understanding of the local housing market conditions in their communities. Regional Choice: Competitive housing markets with high owner-occupancy rates and high property values in comparison to all other market types. Foreclosure, vacancy and abandonment rates are low. Middle Market Choice: Housing prices above the city’s average with strong ownership rates, and low vacancies, but with slightly increased foreclosure rates. Middle Market: Median sales values of $91,000 (above the City’s average of $65,000) as well as high homeownership rates. These markets experienced higher foreclosure rates when compared to higher value markets, with slight population loss. Middle Market Stressed: Slightly lower home sale values than the City’s average, and have not shown significant sales price appreciation. Vacancies and foreclosure rates are high, and the rate of population loss has increased in this market type, according to the 2010 Census data. Distressed Market: , Have experienced significant deterioration of the housing stock. This market category contains the highest vacancy rates and the lowest homeownership rates, compared to the other market types. It also has experienced some of the most substantial population losses in the City during the past decade.

  12. d

    Foreclosure Data | USA Coverage | 74% Right Party Contact Rate | BatchData

    • datarade.ai
    Updated Sep 19, 2024
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    BatchData (2024). Foreclosure Data | USA Coverage | 74% Right Party Contact Rate | BatchData [Dataset]. https://datarade.ai/data-products/batchservice-foreclosure-data-real-time-real-estate-data-batchservice
    Explore at:
    .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Sep 19, 2024
    Dataset authored and provided by
    BatchData
    Area covered
    United States
    Description

    Our foreclosure data offering provides an extensive suite of real-time real estate data, available through both API integration and bulk data delivery. This rich dataset is designed to meet the needs of a variety of users, from real estate investors to foreclosure prevention services and market analysts. With over 31 data points available, this dataset covers multiple aspects of foreclosure processes, including auction details, loan information, foreclosure status, and trustee data. Below is a detailed description of the data points and their potential use cases.

    Data Points Overview for Foreclosure Data:

    1. Auction Data (9+ Data Points) Auction Location, Auction Time, Case Number, Bid Parameters

    2. Loans/Lender Data (9+ Data Points) Lender Name, Original Loan Details, Unpaid Balances, Pre-Foreclosure Flags, Related Documents

    3. Foreclosure Status Data (7+ Data Points) Recording Date, Release Date, Status Indicators and Codes

    4. Trustee Data (6+ Data Points) Trustee Name, Trustee Address, Trustee Phone Number, Sale Number

    Top Use Cases

    1. Surface Investment Opportunities Websites and Applications: Integrate our foreclosure data into real estate platforms to provide users with up-to-date information on potential investment properties. This can enhance search functionality and deliver greater value by identifying promising foreclosure opportunities.

    2. Foreclosure Prevention Services Sales and Marketing: Leverage foreclosure data to target homeowners in distress with tailored marketing efforts. By identifying properties in pre-foreclosure status, you can focus your outreach to offer services designed to prevent foreclosure, such as financial counseling or loan modification programs.

    3. Market Analysis and Predictive Analytics Data-Driven Insights: Utilize the comprehensive dataset to perform in-depth market analysis and develop predictive models. This can help forecast foreclosure trends, assess market conditions, and make informed decisions based on historical and current foreclosure activity.

    Access and Delivery

    Our foreclosure data is accessible through two primary methods: - API Integration: Seamlessly integrate the data into your applications or platforms with our robust API, offering real-time access and automated updates. - Bulk Data Delivery: Obtain large datasets for offline analysis or integration into internal systems through bulk delivery options, providing flexibility in how you utilize the information.

    This comprehensive data listing is designed to empower users with detailed and actionable foreclosure data, facilitating a range of applications from investment analysis to foreclosure prevention and market forecasting.

  13. Mortgage delinquency rate in the U.S. 2024, by loan type

    • statista.com
    Updated Jul 9, 2025
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    Statista (2025). Mortgage delinquency rate in the U.S. 2024, by loan type [Dataset]. https://www.statista.com/statistics/206494/us-mortgage-delinquency-rates-by-loan-type/
    Explore at:
    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Federal Housing Administration (FHA) loans had the highest delinquency rate in the United States in 2024. As of the second quarter of the year, **** percent of 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.

  14. F

    Delinquency Rate on Single-Family Residential Mortgages, Booked in Domestic...

    • fred.stlouisfed.org
    json
    Updated May 21, 2025
    + more versions
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    (2025). Delinquency Rate on Single-Family Residential Mortgages, Booked in Domestic Offices, All Commercial Banks [Dataset]. https://fred.stlouisfed.org/series/DRSFRMACBS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    May 21, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    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 Q1 2025 about domestic offices, delinquencies, 1-unit structures, mortgage, family, residential, commercial, domestic, banks, depository institutions, rate, and USA.

  15. Foreclosures on rustic and urban properties Spain 2014-2022, by property...

    • statista.com
    • ai-chatbox.pro
    Updated Jul 11, 2025
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    Statista (2025). Foreclosures on rustic and urban properties Spain 2014-2022, by property type [Dataset]. https://www.statista.com/statistics/772299/foreclosures-on-rustic-and-urban-properties-in-spain/
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    Dataset updated
    Jul 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Spain
    Description

    The number of foreclosures on rustic and urban properties in Spain has decreased since 2014. In 2022, there were approximately ****** foreclosures, with dwellings on urban land accounting for the largest share.

  16. U.S. metro areas with the highest eviction rates 2015-2017

    • statista.com
    Updated Jul 9, 2025
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    Statista (2025). U.S. metro areas with the highest eviction rates 2015-2017 [Dataset]. https://www.statista.com/statistics/785719/metro-areas-highest-eviction-rates-usa/
    Explore at:
    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    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.

  17. H

    Replication Data for: Economic Distress and Voting: Evidence from the...

    • dataverse.harvard.edu
    • search.datacite.org
    Updated Oct 4, 2020
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    Harvard Dataverse (2020). Replication Data for: Economic Distress and Voting: Evidence from the Subprime Mortgage Crisis [Dataset]. http://doi.org/10.7910/DVN/VYXB4B
    Explore at:
    txt(7158), application/x-stata-syntax(3353), txt(8764), txt(14575), application/x-stata-syntax(2847), tsv(58316052), tex(1102), pdf(8280), txt(14559), tex(1097), application/x-stata-syntax(3396), tex(971), application/x-stata-syntax(3924), application/x-stata-syntax(5388), txt(7838), tsv(602), tsv(99), txt(7881), application/x-stata-syntax(3513), application/x-stata-syntax(3461), application/x-stata-syntax(4473), txt(14950), tsv(36588), txt(15442), txt(7729), application/x-stata-syntax(4636), tex(1082), application/x-stata-syntax(3144), application/x-stata-syntax(3527), application/x-stata-syntax(2734), tex(1491), txt(27304), txt(27445), txt(15305), application/x-stata-syntax(3528), txt(14752), txt(445), tsv(45131), tsv(5605458), txt(7967), tex(2094), application/x-stata-syntax(3551), txt(27887), tex(1093), txt(4468), application/x-stata-syntax(3376), tex(1100), tsv(251003), txt(15457), application/x-stata-14(1165537688), tex(1472), tex(993), tex(735), application/x-stata-syntax(2711), tex(1089), tex(2232), txt(14743), tex(1099), txt(16870), txt(17761), tsv(2947778), application/x-stata-syntax(4661), application/x-stata-syntax(5163), tex(977), application/x-stata-syntax(2277), application/x-stata-syntax(3474), tex(981), txt(15093), pdf(300573), tex(1476), application/x-stata-syntax(4500), type/x-r-syntax(3754), application/x-stata-syntax(2700), pdf(4958), tex(1127), tex(1623)Available download formats
    Dataset updated
    Oct 4, 2020
    Dataset provided by
    Harvard Dataverse
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    We use nationwide deed-level records on home foreclosures to examine the effects of economic distress on electoral outcomes and individual voter turnout. County-level difference-in-differences estimates show that counties that suffered larger increases in foreclosures did not punish or reward members of the incumbent president’s party more than less affected counties. Linking the Ohio voter file to individual foreclosures, difference-in-differences estimates show that individuals whose homes were foreclosed on were less likely to turn out, rather than being mobilized. However, in 2016 counties more exposed to foreclosures supported Trump at substantially higher rates. Taken together, the evidence suggests that the effect of local economic distress on incumbent performance is generally close to zero and only becomes substantial in unusual circumstances.

  18. F

    Delinquency Rate on Commercial Real Estate Loans (Excluding Farmland),...

    • fred.stlouisfed.org
    json
    Updated May 21, 2025
    + more versions
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    (2025). Delinquency Rate on Commercial Real Estate Loans (Excluding Farmland), Booked in Domestic Offices, All Commercial Banks [Dataset]. https://fred.stlouisfed.org/series/DRCRELEXFACBS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    May 21, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    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 Q1 2025 about farmland, domestic offices, delinquencies, real estate, commercial, domestic, loans, banks, depository institutions, rate, and USA.

  19. HUD: Participating Jurisdictions Survey Data

    • datalumos.org
    Updated Feb 14, 2025
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    United States Department of Housing and Urban Development (2025). HUD: Participating Jurisdictions Survey Data [Dataset]. http://doi.org/10.3886/E219406V1
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    Dataset updated
    Feb 14, 2025
    Dataset authored and provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    License

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

    Description

    Text source: https://www.huduser.gov/portal/publications/hsgfin/addi.html In recognition of the fact that a lack of savings is the most significant barrier to homeownership for most low-income families1, Congress passed the American Dream Downpayment Act of 2003, which established the American Dream Downpayment Initiative (ADDI). The ADDI program was designed to provide assistance with downpayments, closing costs, and, if necessary, rehabilitation work done in conjunction with a home purchase. This formula-based program disburses assistance through a network of Participating Jurisdictions (PJs) in all 50 states and affords them significant flexibility in designing homebuyer programs to meet the needs of their communities. Established as part of the HOME program,2 ADDI is a prime example of direct federal assistance to promote low-income homeownership. In recent years there have been growing concerns that many new low-income homeowners have had difficulty maintaining homeownership.3 To address these concerns in the context of the ADDI program, the Fiscal Year 2006 U.S. Senate Report on the Transportation, Treasury and HUD Appropriations Bill directed the U.S. Department of Housing and Urban Development (HUD) to report on the foreclosure and delinquency rate of households who received downpayment assistance through ADDI.4 This report has been developed in response to this congressional mandate. Due to the limited program history of ADDI, and since HOME-assisted homebuyers are quite similar to those assisted by the ADDI, this study jointly estimates annual foreclosure and delinquency rates for both HOME- and ADDI-assisted borrowers who purchased homes during the period from 2001 through 2005.5 While all HOME/ADDI-assisted borrowers were included in the analysis, in order to have the results be representative of the ADDI program, the sample of PJs was limited to those that were eligible for an allocation of ADDI funds in 2004, the year in which the largest number of PJs were eligible. The primary objective of the study, which addresses the congressional inquiry, is to provide an estimate of the foreclosure and delinquency rates among HOME/ADDI-assisted homebuyers. HUD was also interested in an analysis of the reasons behind these outcomes. Thus, a secondary objective of this study is to analyze the factors associated with variations in delinquency and default rates. 1 See, for example, U. S. Department of Housing and Urban Development, Barriers to Minority Homeownership, July 17, 2002, and Herbert et al., Homeownership Gaps Among Low-Income and Minority Borrowers and Neighborhoods, U.S. Department of Housing and Urban Development, March 2005. 2 Created under Title II of the National Affordable Housing Act of 1990, the HOME program is designed to provide affordable housing to low-income households, expand the capacity of nonprofit housing providers, and strengthen the ability of state and local governments to develop and implement affordable housing strate-gies tailored to local needs and priorities. 3 See, for example, Dean Baker, "Who's Dreaming?: Homeownership Among Low-Income Families," Center for Eco-nomic and Policy Research, Washington, DC, January 2005. 4 Throughout our discussion the terms "default" and "foreclosure" are used to refer to the same outcome where homeowners lose their home in foreclosure. 5 Foreclosure and delinquency rates for 2000 are not included here as the data was not consistent enough to produce valid estimations. This report is based in part on surveys of participating jurisdictions.

  20. Share of non-performing mortgage loans in the U.S. 2002-2024, by status

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). Share of non-performing mortgage loans in the U.S. 2002-2024, by status [Dataset]. https://www.statista.com/statistics/1200777/mortgage-delinquency-united-states-usa-by-delinquency-duration/
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    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    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 ** to *** 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. In the third quarter of 2024, the foreclosure rate stood at *** percent - the lowest figures on record. Meanwhile, the ** to ** days delinquency rate rose to *** percent and the ** to *** days delinquency rate rose to *** percent, showing an uptick in the late mortgage payments.

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Statista (2025). Foreclosure rate U.S. 2005-2024 [Dataset]. https://www.statista.com/statistics/798766/foreclosure-rate-usa/
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Foreclosure rate U.S. 2005-2024

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7 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 20, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
United States
Description

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 2024, 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 2023, ** percent of non-homeowners reported that student loan expenses hindered their ability to save for a down payment.

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