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

    • statista.com
    Updated Jun 20, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Foreclosure rate U.S. 2005-2024 [Dataset]. https://www.statista.com/statistics/798766/foreclosure-rate-usa/
    Explore at:
    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

    Data from: No Spillover Effect of the Foreclosure Crisis on Weight Change:...

    • datasetcatalog.nlm.nih.gov
    Updated Sep 28, 2016
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Dow, William H.; Downing, Janelle; Warton, Margaret; Laraia, Barbara; Schillinger, Dean; Adler, Nancy; Karter, Andrew; Rodriguez, Hector (2016). No Spillover Effect of the Foreclosure Crisis on Weight Change: The Diabetes Study of Northern California (DISTANCE) [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0001568611
    Explore at:
    Dataset updated
    Sep 28, 2016
    Authors
    Dow, William H.; Downing, Janelle; Warton, Margaret; Laraia, Barbara; Schillinger, Dean; Adler, Nancy; Karter, Andrew; Rodriguez, Hector
    Area covered
    California
    Description

    The emerging body of research suggests the unprecedented increase in housing foreclosures and unemployment between 2007 and 2009 had detrimental effects on health. Using data from electronic health records of 105,919 patients with diabetes in Northern California, this study examined how increases in foreclosure rates from 2006 to 2010 affected weight change. We anticipated that two of the pathways that explain how the spike in foreclosure rates affects weight gain—increasing stress and declining salutary health behaviors- would be acute in a population with diabetes because of metabolic sensitivity to stressors and health behaviors. Controlling for unemployment, housing prices, temporal trends, and time-invariant confounders with individual fixed effects, we found no evidence of an association between the foreclosure rate in each patient's census block of residence and body mass index. Our results suggest, although more than half of the population was exposed to at least one foreclosure within their census block, the foreclosure crisis did not independently impact weight change.

  3. y

    California Consumers With New Foreclosure

    • ycharts.com
    html
    Updated Aug 5, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Federal Reserve Bank of New York (2025). California Consumers With New Foreclosure [Dataset]. https://ycharts.com/indicators/california_consumers_with_new_foreclosure
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Aug 5, 2025
    Dataset provided by
    YCharts
    Authors
    Federal Reserve Bank of New York
    License

    https://www.ycharts.com/termshttps://www.ycharts.com/terms

    Time period covered
    Jun 30, 1999 - Jun 30, 2025
    Area covered
    California
    Variables measured
    California Consumers With New Foreclosure
    Description

    View quarterly updates and historical trends for California Consumers With New Foreclosure. Source: Federal Reserve Bank of New York. Track economic data …

  4. f

    Linear regression of block foreclosure rate on body mass index (BMI) within...

    • plos.figshare.com
    xls
    Updated Jun 3, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Janelle Downing; Andrew Karter; Hector Rodriguez; William H. Dow; Nancy Adler; Dean Schillinger; Margaret Warton; Barbara Laraia (2023). Linear regression of block foreclosure rate on body mass index (BMI) within individual fixed effects. [Dataset]. http://doi.org/10.1371/journal.pone.0151334.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Janelle Downing; Andrew Karter; Hector Rodriguez; William H. Dow; Nancy Adler; Dean Schillinger; Margaret Warton; Barbara Laraia
    License

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

    Description

    Linear regression of block foreclosure rate on body mass index (BMI) within individual fixed effects.

  5. f

    Baseline Characteristics of Participants and Their Neighborhoods, According...

    • plos.figshare.com
    xls
    Updated May 30, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Janelle Downing; Andrew Karter; Hector Rodriguez; William H. Dow; Nancy Adler; Dean Schillinger; Margaret Warton; Barbara Laraia (2023). Baseline Characteristics of Participants and Their Neighborhoods, According to Exposure to Foreclosures in 2008. [Dataset]. http://doi.org/10.1371/journal.pone.0151334.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Janelle Downing; Andrew Karter; Hector Rodriguez; William H. Dow; Nancy Adler; Dean Schillinger; Margaret Warton; Barbara Laraia
    License

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

    Description

    Baseline Characteristics of Participants and Their Neighborhoods, According to Exposure to Foreclosures in 2008.

  6. f

    Linear regression of foreclosures on body mass index (BMI) with individual...

    • plos.figshare.com
    xls
    Updated May 31, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Janelle Downing; Andrew Karter; Hector Rodriguez; William H. Dow; Nancy Adler; Dean Schillinger; Margaret Warton; Barbara Laraia (2023). Linear regression of foreclosures on body mass index (BMI) with individual fixed effects for Medicaid Patients. [Dataset]. http://doi.org/10.1371/journal.pone.0151334.t004
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Janelle Downing; Andrew Karter; Hector Rodriguez; William H. Dow; Nancy Adler; Dean Schillinger; Margaret Warton; Barbara Laraia
    License

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

    Description

    Linear regression of foreclosures on body mass index (BMI) with individual fixed effects for Medicaid Patients.

  7. u

    Canadian and U.S. Residential Mortgage Arrears and Foreclosure Rates -...

    • data.urbandatacentre.ca
    Updated Jul 5, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2023). Canadian and U.S. Residential Mortgage Arrears and Foreclosure Rates - Catalogue - Canadian Urban Data Catalogue (CUDC) [Dataset]. https://data.urbandatacentre.ca/dataset/canadian-and-u-s-residential-mortgage-arrears-and-foreclosure-rates
    Explore at:
    Dataset updated
    Jul 5, 2023
    Area covered
    United States, Canada
    Description

    Residential mortgage arrears and foreclosure rates in Canada and the U.S. from 2002 to today. This table lets housing professionals compare data by type of mortgage in the U.S. and by region in Canada.

  8. u

    Canadian and U.S. Mortgage Arrears and Foreclosure Rates (Archived) -...

    • data.urbandatacentre.ca
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Canadian and U.S. Mortgage Arrears and Foreclosure Rates (Archived) - Catalogue - Canadian Urban Data Catalogue (CUDC) [Dataset]. https://data.urbandatacentre.ca/dataset/save-page-to-my-folder-save-share-this-page-share-canadian-and-u-s-mortgage-arrears-and-foreclosure
    Explore at:
    Area covered
    United States, Canada
    Description

    Annual residential mortgage arrears and foreclosure rates in Canada and the U.S. from 1990 to 2013. This table is archived for reference, research and record-keeping purposes only. It is not subject to Government of Canada Web Standards and has not been altered or updated since it was archived.

  9. Key sample characteristics a.

    • plos.figshare.com
    xls
    Updated May 30, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Vanessa M. Oddo; Jessica C. Jones-Smith (2023). Key sample characteristics a. [Dataset]. http://doi.org/10.1371/journal.pone.0233734.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Vanessa M. Oddo; Jessica C. Jones-Smith
    License

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

    Description

    Key sample characteristics a.

  10. f

    County fixed-effects regression estimates for the relationship between...

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Vanessa M. Oddo; Jessica C. Jones-Smith (2023). County fixed-effects regression estimates for the relationship between unemployment rate and LGA births in California, 2008–2011. [Dataset]. http://doi.org/10.1371/journal.pone.0233734.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Vanessa M. Oddo; Jessica C. Jones-Smith
    License

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

    Area covered
    California
    Description

    County fixed-effects regression estimates for the relationship between unemployment rate and LGA births in California, 2008–2011.

  11. F

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

    • fred.stlouisfed.org
    json
    Updated Aug 18, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (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
    Aug 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 Delinquency Rate on Single-Family Residential Mortgages, Booked in Domestic Offices, All Commercial Banks (DRSFRMACBS) from Q1 1991 to Q2 2025 about domestic offices, delinquencies, 1-unit structures, mortgage, family, residential, commercial, domestic, banks, depository institutions, rate, and USA.

  12. f

    Mean and standard deviation of within and between individual.

    • plos.figshare.com
    xls
    Updated Jun 4, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Janelle Downing; Andrew Karter; Hector Rodriguez; William H. Dow; Nancy Adler; Dean Schillinger; Margaret Warton; Barbara Laraia (2023). Mean and standard deviation of within and between individual. [Dataset]. http://doi.org/10.1371/journal.pone.0151334.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Janelle Downing; Andrew Karter; Hector Rodriguez; William H. Dow; Nancy Adler; Dean Schillinger; Margaret Warton; Barbara Laraia
    License

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

    Description

    Mean and standard deviation of within and between individual.

  13. f

    County fixed-effects regression estimates for the relationship between...

    • figshare.com
    xls
    Updated May 30, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Vanessa M. Oddo; Jessica C. Jones-Smith (2023). County fixed-effects regression estimates for the relationship between unemployment rate and LGA births, 2008–2011, stratified by race/ethnicity. [Dataset]. http://doi.org/10.1371/journal.pone.0233734.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Vanessa M. Oddo; Jessica C. Jones-Smith
    License

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

    Description

    County fixed-effects regression estimates for the relationship between unemployment rate and LGA births, 2008–2011, stratified by race/ethnicity.

  14. f

    County fixed-effects regression estimates for the relationship between...

    • plos.figshare.com
    xls
    Updated Jun 2, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Vanessa M. Oddo; Jessica C. Jones-Smith (2023). County fixed-effects regression estimates for the relationship between unemployment rate and secondary outcomes, 2008–2011. [Dataset]. http://doi.org/10.1371/journal.pone.0233734.t004
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Vanessa M. Oddo; Jessica C. Jones-Smith
    License

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

    Description

    County fixed-effects regression estimates for the relationship between unemployment rate and secondary outcomes, 2008–2011.

  15. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Statista (2025). Foreclosure rate U.S. 2005-2024 [Dataset]. https://www.statista.com/statistics/798766/foreclosure-rate-usa/
Organization logo

Foreclosure rate U.S. 2005-2024

Explore at:
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.

Search
Clear search
Close search
Google apps
Main menu