24 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. F

    Large Bank Consumer Mortgage Balances: 60 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: 60 or More Days Past Due: Including Foreclosures Rates: Balances Based [Dataset]. https://fred.stlouisfed.org/series/RCMFLBBALDPDPCT60P
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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: 60 or More Days Past Due: Including Foreclosures Rates: Balances Based (RCMFLBBALDPDPCT60P) from Q3 2012 to Q1 2025 about 60 days +, FR Y-14M, large, balance, mortgage, consumer, banks, depository institutions, rate, and USA.

  3. 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.

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

    • statista.com
    Updated Jul 11, 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
    Jul 11, 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 ******* properties, which was about ****** fewer than in 2023. Despite the decrease, 2024 saw one of the lowest foreclosure rates on record.

  5. 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.

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

    • statista.com
    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.

  8. Risk of eviction for U.S. homeowners due to foreclosure in 2023

    • statista.com
    Updated Jul 11, 2025
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    Statista (2025). Risk of eviction for U.S. homeowners due to foreclosure in 2023 [Dataset]. https://www.statista.com/statistics/1251484/foreclosure-risk-for-house-owners-usa/
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    Dataset updated
    Jul 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 18, 2023 - Oct 30, 2023
    Area covered
    United States
    Description

    About ***** percent of U.S. homeowners with a mortgage who were behind on mortgage payments in ************ were very likely to face eviction in the next two months due to a foreclosure. Additionally, ** percent of the respondents were somewhat likely to be evicted. In 2022, the foreclosure rate in the U.S. picked up, after a long period of steady decline after the subprime mortgage crisis.

  9. 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.

  10. Foreclosure completion time in the U.S. 2007-2018

    • statista.com
    Updated Dec 4, 2018
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    Statista (2018). Foreclosure completion time in the U.S. 2007-2018 [Dataset]. https://www.statista.com/statistics/947629/foreclosure-completion-usa/
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    Dataset updated
    Dec 4, 2018
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    This statistic shows the average number of days taken to complete a foreclosure in the United States from the first quarter of 2007 to the third quarter of 2018. In the third quarter of 2018, foreclosures in the U.S. were completed, on average, in *** days.

  11. 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.

  12. 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
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    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.

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

    • search.datacite.org
    • dataverse.harvard.edu
    Updated 2020
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    Jesse Yoder (2020). Replication Data for: Economic Distress and Voting: Evidence from the Subprime Mortgage Crisis [Dataset]. http://doi.org/10.7910/dvn/vyxb4b
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    Dataset updated
    2020
    Dataset provided by
    DataCitehttps://www.datacite.org/
    Harvard Dataverse
    Authors
    Jesse Yoder
    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.

  14. 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.

  15. Likelihood of foreclosure according to consumers in the U.S. 2018

    • statista.com
    Updated Nov 6, 2020
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    Statista (2020). Likelihood of foreclosure according to consumers in the U.S. 2018 [Dataset]. https://www.statista.com/statistics/946579/likelihood-foreclosure-home-mortgage-usa/
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    Dataset updated
    Nov 6, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 1, 2018 - Oct 2, 2018
    Area covered
    United States
    Description

    This statistic shows the likelihood of residence being foreclosed upon according to mortgage holders in the United States in 2018. In 2018, 70 percent of the respondents said that it was very unlikely that they would experience the foreclosure of their residence.

  16. o

    Supplementary data for: Long-Term Impacts of Individual Development Accounts...

    • openicpsr.org
    Updated Jul 10, 2025
    + more versions
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    Michal Grinstein-Weiss; Michael Sherraden; William G. Gale; William M. Rohe; Mark Schreiner; Clinton Key (2025). Supplementary data for: Long-Term Impacts of Individual Development Accounts on Homeownership among Baseline Renters: Follow-Up Evidence from a Randomized Experiment [Dataset]. http://doi.org/10.3886/E235722V1
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    Dataset updated
    Jul 10, 2025
    Authors
    Michal Grinstein-Weiss; Michael Sherraden; William G. Gale; William M. Rohe; Mark Schreiner; Clinton Key
    Description

    We examine the long-term effects of a 1998-2003 randomized experiment in Tulsa, Oklahoma with Individual Development Accounts that offered low-income households 2:1 matching funds for housing down payments. Prior work shows that, among households who rented in 1998, homeownership rates increased more through 2003 in the treatment group than for controls. We show that control group renters caught up rapidly with the treatment group after the experiment ended. As of 2009, the program had an economically small and statistically insignificant effect on homeownership rates, the number of years respondents owned homes, home equity, and foreclosure activity among baseline renters. (JEL D14, H75, R21, R31)

  17. Real Estate Sales & Brokerage in the US - Market Research Report (2015-2030)...

    • ibisworld.com
    Updated Apr 15, 2025
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    IBISWorld (2025). Real Estate Sales & Brokerage in the US - Market Research Report (2015-2030) [Dataset]. https://www.ibisworld.com/united-states/market-research-reports/real-estate-sales-brokerage-industry/
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    Dataset updated
    Apr 15, 2025
    Dataset authored and provided by
    IBISWorld
    License

    https://www.ibisworld.com/about/termsofuse/https://www.ibisworld.com/about/termsofuse/

    Time period covered
    2015 - 2030
    Area covered
    United States
    Description

    The real estate sales and brokerage industry is navigating a complex landscape with high mortgage rates and dropping home sales. The Federal Reserve's decision to raise the benchmark interest rate 11 times across 2022 and 2023 to combat inflation led to a significant climb in mortgage rates, dampening buyer demand and affordability. This gain has deterred homeowners from selling, leading to low housing inventory. Despite the rate cuts that came in 2024, mortgage rates remain high, with the typical 30-year fixed mortgage staying above 6.5%. Existing home sales also hit a near 30-year low in 2024, mainly because of high home prices and tight supply. Amid these challenges, the real estate market has seen a surge in home values, propelling industry growth. This growth greatly benefits real estate agents and brokerages, who often base their commissions on the house's selling price. Despite the high vacancy rates, the office market also shows signs of picking up, primarily because of demand for high-quality assets such as Class A office spaces and modern buildings. Increased competitive pressure necessitates more aggressive marketing tactics to secure listings and attract sellers. Nonetheless, because of the industry's robust performance from 2020 to 2021, revenue has climbed at a CAGR of 0.8% over the past five years, reaching $241.3 billion in 2025. 2025 revenue will climb an estimated 1.0% as home price appreciation and a rebound in commercial sales volume will fuel tepid growth. The higher-for-longer interest rate environment is expected to slow the industry's growth. The high mortgage rates and escalating home prices will likely price out many potential home buyers from the market, forcing customers to rent or live in multifamily complexes. The limited new office construction will stimulate office building sales and intensify brokerage activity. The housing stock situation is expected to remain tight, with homeowners staying in their homes for longer and contributing to home price appreciation. Amid these conditions, a likely shift toward new construction and build-to-rent properties for agents and brokers is anticipated. Increased competition in the form of market saturation and disruption from online platforms will inhibit profit growth. Overall, industry revenue will gain at a CAGR of 2.3% to reach $270.8 billion in 2030.

  18. Mortgage delinquency rates for VA loans in the U.S. 2000-2024, by quarter

    • statista.com
    Updated Jul 9, 2025
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    Statista (2025). Mortgage delinquency rates for VA loans in the U.S. 2000-2024, by quarter [Dataset]. https://www.statista.com/statistics/205991/us-veterans-administration-loans-since-1990/
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    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The mortgage delinquency rate for Veterans Administration (VA) loans in the United States has decreased since 2020. Under the effects of the coronavirus pandemic, the mortgage delinquency rate for VA loans spiked from **** percent in the first quarter of 2020 to **** percent in the second quarter of the year. In the second quarter of 2024, the delinquency rate amounted to **** percent. Historically, VA mortgages have significantly lower delinquency rate than conventional mortgages.

  19. Residential mortgage backed security issuance in the U.S. 1996-2024

    • statista.com
    Updated Jun 20, 2025
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    Statista (2025). Residential mortgage backed security issuance in the U.S. 1996-2024 [Dataset]. https://www.statista.com/statistics/275746/rmbs-issuance-in-the-united-states/
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    Dataset updated
    Jun 20, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The year 2021 saw the peak in issuance of residential mortgage backed securities (MBS), at *** trillion U.S. dollars. Since then, MBS issuance has slowed, reaching *** trillion U.S. dollars in 2023. What are mortgage backed securities? A mortgage backed security is a financial instrument in which mortgages are bundled together and sold to investors. The idea is that the risk of these individual mortgages is pooled when they are packaged together. This is a sound investment policy, unless the foreclosure rate increases significantly in a short amount of time. Mortgage risk Since mortgages are loans backed by an asset, the house, the risk is often considered relatively low. However, the loan maturities are very long, sometimes decades, meaning lenders must factor in the risk of a shift in the economic climate. As such, interest rates on longer mortgages tend to be higher than on shorter loans. The ten-year treasury yield influences these rates, since it is a long-term rate that most investors accept as risk-free. Additionally, a decline in the value of homeowner equity could lead to a situation where the debtor is “underwater” and owes more than the home is worth.

  20. Code for: "Disability and Distress: The Effect of Disability Programs on...

    • openicpsr.org
    Updated Mar 16, 2021
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    Manasi Deshpande; Tal Gross; Yalun Su (2021). Code for: "Disability and Distress: The Effect of Disability Programs on Financial Outcomes" [Dataset]. http://doi.org/10.3886/E118462V1
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    Dataset updated
    Mar 16, 2021
    Dataset provided by
    American Economic Associationhttp://www.aeaweb.org/
    Authors
    Manasi Deshpande; Tal Gross; Yalun Su
    License

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

    Time period covered
    2000 - 2014
    Area covered
    United States
    Description

    What is the relationship between disability programs and financial distress? We provide the first evidence on this relationship using several markers of financial distress: bankruptcy, foreclosure, eviction, and home sale. Rates of these adverse financial events peak around the time of disability application. Using variation induced by an age-based eligibility rule, we find that disability allowance reduces the likelihood of bankruptcy by 20 percent, foreclosure by 33 percent, and home sale by 15 percent. We present evidence that these changes reflect true reductions in financial distress. Considering these extreme events increases the optimal disability benefit amount and suggests a shorter optimal waiting time between application and benefit receipt.

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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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