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.

2021 Foreclosure Properties registered with the LAHD from January 1, 2021 through December 31, 2021.

Analysis of ‘2021 Registered Foreclosure Properties’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/eab64bdf-3cb1-4bd4-8011-b931f5648dd5 on 27 January 2022.

--- Dataset description provided by original source is as follows ---

2021 Foreclosure Properties registered with the LAHD from January 1, 2021 through December 31, 2021.

--- Original source retains full ownership of the source dataset ---

The portion of the homes and condominiums sold that were identified as being owned by the bank (REO) out of all residential properties sold in a calendar year.Source: RBIntel Years Available: 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023

Financial institutions that have filed an exemption affidavit in 2021 pursuant to HB 2009.

Analysis of ‘2020 Registered Foreclosure Properties’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/548b5fad-cb01-4deb-a0fa-d36dacd0b681 on 30 September 2021.

--- Dataset description provided by original source is as follows ---

2020 Foreclosure Properties registered with the HCIDLA from January 1, 2020 through December 31, 2020.

--- Original source retains full ownership of the source dataset ---

In 2021, Allegheny County Economic Development (ACED), in partnership with Urban Redevelopment Authority of Pittsburgh(URA), completed the a Market Value Analysis (MVA) for Allegheny County. This analysis services as both an update to previous MVA’s commissioned separately by ACED and the URA and combines the MVA for the whole of Allegheny County (inclusive of the City of Pittsburgh). The MVA is a unique tool for characterizing markets because it creates an internally referenced index of a municipality’s residential real estate market. It identifies areas that are the highest demand markets as well as areas of greatest distress, and the various markets types between. The MVA offers insight into the variation in market strength and weakness within and between traditional community boundaries because it uses Census block groups as the unit of analysis. Where market types abut each other on the map becomes instructive about the potential direction of market change, and ultimately, the appropriateness of types of investment or intervention strategies. This MVA utilized data that helps to define the local real estate market. The data used covers the 2017-2019 period, and data used in the analysis includes: Residential Real Estate Sales Mortgage Foreclosures Residential Vacancy Parcel Year Built Parcel Condition Building Violations Owner Occupancy Subsidized Housing Units The MVA uses a statistical technique known as cluster analysis, forming groups of areas (i.e., block groups) that are similar along the MVA descriptors, noted above. The goal is to form groups within which there is a similarity of characteristics within each group, but each group itself different from the others. Using this technique, the MVA condenses vast amounts of data for the universe of all properties to a manageable, meaningful typology of market types that can inform area-appropriate programs and decisions regarding the allocation of resources. Please refer to the presentation and executive summary for more information about the data, methodology, and findings.

The number of U.S. home sales in the United States declined in 2024, after soaring in 2021. A total of four million transactions of existing homes, including single-family, condo, and co-ops, were completed in 2024, down from 6.12 million in 2021. According to the forecast, the housing market is forecast to head for recovery in 2025, despite transaction volumes expected to remain below the long-term average. Why have home sales declined? The housing boom during the coronavirus pandemic has demonstrated that being a homeowner is still an integral part of the American dream. Nevertheless, sentiment declined in the second half of 2022 and Americans across all generations agreed that the time was not right to buy a home. A combination of factors has led to house prices rocketing and making homeownership unaffordable for the average buyer. A survey among owners and renters found that the high home prices and unfavorable economic conditions were the two main barriers to making a home purchase. People who would like to purchase their own home need to save up a deposit, have a good credit score, and a steady and sufficient income to be approved for a mortgage. In 2022, mortgage rates experienced the most aggressive increase in history, making the total cost of homeownership substantially higher. Are U.S. home prices expected to fall? The median sales price of existing homes stood at 413,000 U.S. dollars in 2024 and was forecast to increase slightly until 2026. The development of the S&P/Case Shiller U.S. National Home Price Index shows that home prices experienced seven consecutive months of decline between June 2022 and January 2023, but this trend reversed in the following months. Despite mild fluctuations throughout the year, home prices in many metros are forecast to continue to grow, albeit at a much slower rate.

Analysis of ‘2021 Foreclosure Avoidance Program Beneficiary Exemption Affidavits Pursuant To HB 2009’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/b66fc711-539c-48da-8bac-a32d80706554 on 27 January 2022.

--- Dataset description provided by original source is as follows ---

Financial institutions that have filed an exemption affidavit in 2021 pursuant to HB 2009.

--- Original source retains full ownership of the source dataset ---

Indonesia PT BPD Jawa Tengah: Foreclosed Assets data was reported at 7.543 IDR bn in May 2021. Indonesia PT BPD Jawa Tengah: Foreclosed Assets data is updated monthly, averaging 7.543 IDR bn from May 2021 (Median) to May 2021, with 1 observations. The data reached an all-time high of 7.543 IDR bn in May 2021 and a record low of 7.543 IDR bn in May 2021. Indonesia PT BPD Jawa Tengah: Foreclosed Assets data remains active status in CEIC and is reported by Indonesia Financial Services Authority. The data is categorized under Indonesia Premium Database’s Banking Sector – Table ID.KBK008: Regional Bank: Assets and Liabilities: PT BPD Jawa Tengah.

Thailand TTB: Assets: Properties Foreclosed: Net data was reported at 13,343,275.000 THB th in Mar 2025. This records an increase from the previous number of 13,195,353.000 THB th for Feb 2025. Thailand TTB: Assets: Properties Foreclosed: Net data is updated monthly, averaging 10,613,877.000 THB th from May 2021 (Median) to Mar 2025, with 47 observations. The data reached an all-time high of 13,372,163.000 THB th in Nov 2024 and a record low of 3,012,013.000 THB th in Jun 2021. Thailand TTB: Assets: Properties Foreclosed: Net data remains active status in CEIC and is reported by Bank of Thailand. The data is categorized under Global Database’s Thailand – Table TH.KB061: Balance Sheet: Thai Bank: TMBThanachart Bank.

PT Bank Syariah Indonesia: Assets: Foreclosed Assets data was reported at 74,594.000 IDR mn in May 2021. This stayed constant from the previous number of 74,594.000 IDR mn for Apr 2021. PT Bank Syariah Indonesia: Assets: Foreclosed Assets data is updated monthly, averaging 74,594.000 IDR mn from Feb 2021 (Median) to May 2021, with 4 observations. The data reached an all-time high of 74,594.000 IDR mn in May 2021 and a record low of 74,594.000 IDR mn in May 2021. PT Bank Syariah Indonesia: Assets: Foreclosed Assets data remains active status in CEIC and is reported by Indonesia Financial Services Authority. The data is categorized under Indonesia Premium Database’s Banking Sector – Table ID.KBM001: Islamic Banks: Assets and Liabilities: PT Bank Syariah Indonesia.

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.

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.

Abstract

Title: Cotality Smart Data Platform (SDP): Historical Property

Historical tax assessment data for all U.S. states, the U.S. Virgin Islands, Guam, and Washington, D.C. Each table represents a previous edition of Cotality's tax assessment data.

Formerly known as CoreLogic Smart Data Platform: Historical Property.

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, Cotality collects, cleans, and normalizes public records that they collect from U.S. County Assessor and Recorder offices. Cotality 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 Cotality'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 Cotality 2024 GitLab.

Usage

Each table contains an archived snapshot of the property data, roughly corresponding to the following assessed years:

• Historical Property 1 = 2022-2023
• Historical Property 2 = 2021-2022
• Historical Property 3 = 2020-2021
• Historical Property 4 = 2019-2020
• Historical Property 5 = 2018-2019
• Historical Property 6 = 2017-2018
• Historical Property 7 = 2016-2017
• Historical Property 8 = 2015-2016
• Historical Property 9 = 2014-2015
• Historical Property 10 = 2013-2014
• Historical Property 11 = 2012-2013
• Historical Property 12 = 2011-2012
• Historical Property 13 = 2010-2011
• Historical Property 14 = 2009-2010
• Historical Property 15 = 2008-2009

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Users can check theASSESSED_YEAR variable to confirm the year of assessment.

Roughly speaking, the tables use the following census geographies:

• 2020 Census Tract: Historical Property 1-2
• 2010 Census Tract: Historical Property 3 – 12
• 2000 Census Tract: Historical Property 13 – 15

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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.

For more information about included variables, please see **cotality_sdp_historical_property_data_dictionary_2024.txt **and Historical Property_v3.xlsx.

Under Supporting files, users can also find record counts per FIPS code for each edition of the Historical Property data.

For more information about how the Cotality Smart Data Platform: Historical Property data compares to legacy data, please see 2025_Legacy_Content_Mapping.pdf.

Bulk Data Access

Data access is required to view this section.

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 **** percent of current loans in forbearance.

PT Bank Syariah Indonesia: Assets: Non-productive: Foreclosed Assets在2021-05达74,594.000IDR mn，相较于2021-04的74,594.000IDR mn保持不变。PT Bank Syariah Indonesia: Assets: Non-productive: Foreclosed Assets数据按月度更新，2021-02至2021-05期间平均值为74,594.000IDR mn，共4份观测结果。该数据的历史最高值出现于2021-05，达74,594.000IDR mn，而历史最低值则出现于2021-05，为74,594.000IDR mn。CEIC提供的PT Bank Syariah Indonesia: Assets: Non-productive: Foreclosed Assets数据处于定期更新的状态，数据来源于Indonesia Financial Services Authority，数据归类于Indonesia Premium Database的Banking Sector – Table ID.KBM001: Islamic Banks: Assets and Liabilities: PT Bank Syariah Indonesia。