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

    • ai-chatbox.pro
    • statista.com
    Updated May 20, 2025
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    Statista Research Department (2025). Foreclosure rate U.S. 2005-2024 [Dataset]. https://www.ai-chatbox.pro/?_=%2Ftopics%2F1685%2Fmortgage-industry-of-the-united-states%2F%23XgboD02vawLbpWJjSPEePEUG%2FVFd%2Bik%3D
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    Dataset updated
    May 20, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    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 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.

  2. F

    Large Bank Consumer Mortgage Balances: 60 or More Days Past Due: Including...

    • fred.stlouisfed.org
    json
    Updated Apr 9, 2025
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    (2025). Large Bank Consumer Mortgage Balances: 60 or More Days Past Due: Including Foreclosures Rates: Accounts Based [Dataset]. https://fred.stlouisfed.org/series/RCMFLBACTDPDPCT60P
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    jsonAvailable download formats
    Dataset updated
    Apr 9, 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: 60 or More Days Past Due: Including Foreclosures Rates: Accounts Based (RCMFLBACTDPDPCT60P) from Q3 2012 to Q4 2024 about 60 days +, accounts, FR Y-14M, large, balance, mortgage, consumer, banks, depository institutions, rate, and USA.

  3. Number of properties with foreclosure filings U.S. 2005-2024

    • statista.com
    Updated May 15, 2025
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    Statista (2025). Number of properties with foreclosure filings U.S. 2005-2024 [Dataset]. https://www.statista.com/statistics/798630/number-of-properties-with-foreclosure-filings-usa/
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    Dataset updated
    May 15, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    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 322,100 properties, which was about 34,900 fewer than in 2023. Despite the decrease, 2024 saw one of the lowest foreclosure rates on record.

  4. Foreclosure filings in the U.S. 2017, by state

    • statista.com
    Updated Nov 6, 2020
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    Statista (2020). Foreclosure filings in the U.S. 2017, by state [Dataset]. https://www.statista.com/statistics/612770/foreclosure-filings-ratio-usa-by-state/
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    Dataset updated
    Nov 6, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jun 2017
    Area covered
    United States
    Description

    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.

  5. Data from: Assessing the Link Between Foreclosure and Crime Rates: A...

    • catalog.data.gov
    • icpsr.umich.edu
    Updated Mar 12, 2025
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    National Institute of Justice (2025). Assessing the Link Between Foreclosure and Crime Rates: A Multi-level Analysis of Neighborhoods Across 29 Large United States Cities, 2007-2009 [Dataset]. https://catalog.data.gov/dataset/assessing-the-link-between-foreclosure-and-crime-rates-a-multi-level-analysis-of-neig-2007
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    National Institute of Justicehttp://nij.ojp.gov/
    Area covered
    United States
    Description

    These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. The study integrated neighborhood-level data on robbery and burglary gathered from local police agencies across the United States, foreclosure data from RealtyTrac (a real estate information company), and a wide variety of social, economic, and demographic control variables from multiple sources. Using census tracts to approximate neighborhoods, the study regressed 2009 neighborhood robbery and burglary rates on foreclosure rates measured for 2007-2008 (a period during which foreclosure spiked dramatically in the nation), while accounting for 2007 robbery and burglary rates and other control variables that captured differences in social, economic, and demographic context across American neighborhoods and cities for this period. The analysis was based on more than 7,200 census tracts in over 60 large cities spread across 29 states. Core research questions were addressed with a series of multivariate multilevel and single-level regression models that accounted for the skewed nature of neighborhood crime patterns and the well-documented spatial dependence of crime. The study contains one data file with 8,198 cases and 99 variables.

  6. F

    Nonfarm Real Estate Foreclosures for United States

    • fred.stlouisfed.org
    json
    Updated Aug 17, 2012
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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.

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

    • statista.com
    Updated Jan 28, 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
    Jan 28, 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 0.43 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.

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

    • statista.com
    Updated Dec 7, 2024
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    Statista (2024). 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
    Dec 7, 2024
    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.

  9. 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
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    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.

  10. r

    Neighborhood Stabilization Program (NSP) Target Areas

    • rigis.org
    • rigis-edc.opendata.arcgis.com
    • +1more
    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.

  11. U.S. federal housing administration loan entering foreclosure processes...

    • statista.com
    Updated Dec 7, 2024
    + more versions
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    Statista (2024). U.S. federal housing administration loan entering foreclosure processes 2000-2018 [Dataset]. https://www.statista.com/statistics/206057/us-federal-housing-loans-entering-foreclosure-process-since-1990/
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    Dataset updated
    Dec 7, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    This statistic presents the share of federal housing administration loans entering the foreclosure process in the United States from 2000 to 2018. The share of federal housing administration loans entering the foreclosure process decreased from 2.3 percent in 2000 to 2 percent in 2018.

    Under the effects of the coronavirus pandemic, delinquency rates surged for all loan types in 2020. Nevertheless, due the Coronavirus Aid, Relief, and Economic Security Act (CARES Act), foreclosure rates remained low.

  12. o

    Replication data for: Macroeconomic Effects of Bankruptcy and Foreclosure...

    • openicpsr.org
    Updated Aug 1, 2016
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    Kurt Mitman (2016). Replication data for: Macroeconomic Effects of Bankruptcy and Foreclosure Policies [Dataset]. http://doi.org/10.3886/E116138V1
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    Dataset updated
    Aug 1, 2016
    Dataset provided by
    American Economic Association
    Authors
    Kurt Mitman
    Area covered
    United States
    Description

    I study the implications of two major debt-relief policies in the United States: the Bankruptcy Abuse Prevention and Consumer Protection Act (BAPCPA) and the Home Affordable Refinance Program (HARP). To do so, I develop a model of housing and default that includes relevant dimensions of credit-market policy and captures rich heterogeneity in household balance sheets. The model also explains the observed cross-state variation in consumer default rates. I find that BAPCPA significantly reduced bankruptcy rates, but increased foreclosure rates when house prices fell. HARP reduced foreclosures by 1 percentage point and provided substantial welfare gains to households with high loan-to-value mortgages.

  13. 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/
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    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.

  14. Share of U.S. veterans administration loans entering foreclosure processes...

    • statista.com
    Updated Dec 7, 2024
    + more versions
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    Statista (2024). Share of U.S. veterans administration loans entering foreclosure processes 2000-2018 [Dataset]. https://www.statista.com/statistics/206054/us-vva-loans-entering-foreclosure-process-since-1990/
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    Dataset updated
    Dec 7, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    This statistic presents the share of veterans administration loans entering the foreclosure process in the United States from 2000 to 2018. The share of veterans administration loans entering the foreclosure process decreased from 1.5 percent in 2000 to 1.1 percent in 2018.

    Under the effects of the coronavirus pandemic, delinquency rates surged for all loan types in 2020. Nevertheless, due the Coronavirus Aid, Relief, and Economic Security Act (CARES Act), foreclosure rates remained low.

  15. Share of U.S. prime conventional loans in foreclosure processes 2005-2018

    • statista.com
    Updated Dec 7, 2024
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    Statista (2024). Share of U.S. prime conventional loans in foreclosure processes 2005-2018 [Dataset]. https://www.statista.com/statistics/205996/us-foreclosure-rates-on-prime-conventional-loans-since-2000/
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    Dataset updated
    Dec 7, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    This statistic presents the share of prime conventional loans in the foreclosure process in the United States from 2005 to 2018. The share of prime conventional loans in the foreclosure process was 0.9 percent in 2005 and it remained the same in 2018. Under the effects of the coronavirus pandemic, delinquency rates surged for all loan types in 2020. Nevertheless, due the Coronavirus Aid, Relief, and Economic Security Act (CARES Act), foreclosure rates remained low.

  16. 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
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    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.

  17. 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
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    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.

  18. 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.

  19. CoreLogic Smart Data Platform: Owner Transfer and Mortgage

    • redivis.com
    application/jsonl +7
    Updated Aug 1, 2024
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    Stanford University Libraries (2024). CoreLogic Smart Data Platform: Owner Transfer and Mortgage [Dataset]. http://doi.org/10.57761/8twx-xz17
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    parquet, application/jsonl, sas, avro, csv, spss, arrow, stataAvailable download formats
    Dataset updated
    Aug 1, 2024
    Dataset provided by
    Redivis Inc.
    Authors
    Stanford University Libraries
    Description

    Abstract

    The Owner Transfer and Mortgage data covers over 450 million properties, and includes over 50 years of sales history. The tables were generated in June 2024, and cover all U.S. states, the U.S. Virgin Islands, Guam, and Washington, D.C.

    The Owner Transfer data provides historical information about property sales and ownership-related transactions, including full, nominal, and quitclaim transactions (involving a change in title/ownership). It contains comprehensive property and transaction information, such as property characteristics, current ownership, transaction history, title company, cash purchase/foreclosure/resale/short sale indicators, and buyer information.

    The Mortgage data provides historical information at the mortgage level, including purchase, refinance, equity, as well as details associated with each transaction, such as lender, loan amount, loan date, interest rate, etc. Mortgage details include mortgage amount, type of loan (conventional, FHA, VHA), mortgage rate type, mortgage purpose (cash out first, consolidation, standalone subordinate), mortgage ARM features, and mortgage indicators such as fixed-rate, conforming loan, construction loan, and private party. The Mortgage data also includes subordinate mortgage types, rate details, and lender details (NMLS ID, Loan Company, Loan Officers).

    The CoreLogic Smart Data Platform (SDP) Owner Transfer and Mortgage data was formerly known as the CoreLogic Deed data. The CoreLogic Deed data contained both owner transfer and mortgage information. In the CoreLogic Smart Data Platform (SDP), this data was separated into two tables: Owner Transfer and Mortgage. Between the two tables, the CoreLogic Smart Data Platform (SDP) Owner Transfer and Mortgage data contains almost all of the variables that were included in the CoreLogic Deed data. Further, each CoreLogic Smart Data Platform (SDP) table is augmented with additional owner transfer and mortgage characteristics.

    Methodology

    In the United States, parcel data is public record information that describes a division of land (also referred to as "property" or "real estate"). Each parcel is given a unique identifier called an Assessor’s Parcel Number or APN. The two principal types of records maintained by county government agencies for each parcel of land are deed and property tax records. When a real estate transaction takes place (e.g. a change in ownership), a property deed must be signed by both the buyer and seller. The deed will then be filed with the County Recorder’s offices, sometimes called the County Clerk-Recorder or other similar title. Property tax records are maintained by County Tax Assessor’s offices; they show the amount of taxes assessed on a parcel and include a detailed description of any structures or buildings on the parcel, including year built, square footages, building type, amenities like a pool, etc. There is not a uniform format for storing parcel data across the thousands of counties and county equivalents in the U.S.; laws and regulations governing real estate/property sales vary by state. Counties and county equivalents also have inconsistent approaches to archiving historical parcel data.

    To fill researchers’ needs for uniform parcel data, CoreLogic collects, cleans, and normalizes public records that they collect from U.S. County Assessor and Recorder offices. CoreLogic augments this data with information gathered from other public and non-public sources (e.g., loan issuers, real estate agents, landlords, etc.). The Stanford Libraries has purchased bulk extracts from CoreLogic’s parcel data, including mortgage, owner transfer, pre-foreclosure, and historical and contemporary tax assessment data. Data is bundled into pipe-delimited text files, which are uploaded to Data Farm (Redivis) for preview, extraction and analysis.

    For more information about how the data was prepared for Redivis, please see CoreLogic 2024 GitLab.

    Usage

    The Property, Mortgage, Owner Transfer, Historical Property and Pre-Foreclosure data can be linked on the CLIP, a unique identification number assigned to each property.

    Mortgage records can be linked to a transaction using the MORTGAGE_COMPOSITE_TRANSACTION_ID.

    For more information about included variables, please see:

    • core_logic_sdp_owner_transfer_data_dictionary_2024.txt
    • core_logic_sdp_mortgage_data_dictionary_2024.txt
    • Mortgage_v3.xlsx
    • Owner Transfer_v3.xlsx

    %3C!-- --%3E

    For a count of records per FIPS code, please see core_logic_sdp_owner_transfer_counts_2024.txt and core_logic_sdp_mortgage_counts_2024.txt.

    For more information about how the CoreLogic Smart Data Platform: Owner Transfer and Mortgage data compares to legacy data, please see core_logic_legacy_content_mapping.pdf.

    Bulk Data Access

    Data access is required to view this section.

  20. Forbearance rate of housing loans the U.S. 2022, by state

    • statista.com
    Updated Jun 5, 2024
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    Statista (2024). Forbearance rate of housing loans the U.S. 2022, by state [Dataset]. https://www.statista.com/statistics/1200682/mortgage-forbearance-rate-united-states-usa-by-state/
    Explore at:
    Dataset updated
    Jun 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 2022
    Area covered
    United States
    Description

    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 0.87 percent of current loans in forbearance.

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Statista Research Department (2025). Foreclosure rate U.S. 2005-2024 [Dataset]. https://www.ai-chatbox.pro/?_=%2Ftopics%2F1685%2Fmortgage-industry-of-the-united-states%2F%23XgboD02vawLbpWJjSPEePEUG%2FVFd%2Bik%3D
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Foreclosure rate U.S. 2005-2024

Explore at:
Dataset updated
May 20, 2025
Dataset provided by
Statistahttp://statista.com/
Authors
Statista Research Department
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 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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