The Federal National Mortgage Association, commonly known as Fannie Mae, was created by the U.S. congress in 1938, in order to maintain liquidity and stability in the domestic mortgage market. The company is a government-sponsored enterprise (GSE), meaning that while it was a publicly traded company for most of its history, it was still supported by the federal government. While there is no legally binding guarantee of shares in GSEs or their securities, it is generally acknowledged that the U.S. government is highly unlikely to let these enterprises fail. Due to these implicit guarantees, GSEs are able to access financing at a reduced cost of interest. Fannie Mae's main activity is the purchasing of mortgage loans from their originators (banks, mortgage brokers etc.) and packaging them into mortgage-backed securities (MBS) in order to ease the access of U.S. homebuyers to housing credit. The early 2000s U.S. mortgage finance boom During the early 2000s, Fannie Mae was swept up in the U.S. housing boom which eventually led to the financial crisis of 2007-2008. The association's stated goal of increasing access of lower income families to housing finance coalesced with the interests of private mortgage lenders and Wall Street investment banks, who had become heavily reliant on the housing market to drive profits. Private lenders had begun to offer riskier mortgage loans in the early 2000s due to low interest rates in the wake of the "Dot Com" crash and their need to maintain profits through increasing the volume of loans on their books. The securitized products created by these private lenders did not maintain the standards which had traditionally been upheld by GSEs. Due to their market share being eaten into by private firms, however, the GSEs involved in the mortgage markets began to also lower their standards, resulting in a 'race to the bottom'. The fall of Fannie Mae The lowering of lending standards was a key factor in creating the housing bubble, as mortgages were now being offered to borrowers with little or no ability to repay the loans. Combined with fraudulent practices from credit ratings agencies, who rated the junk securities created from these mortgage loans as being of the highest standard, this led directly to the financial panic that erupted on Wall Street beginning in 2007. As the U.S. economy slowed down in 2006, mortgage delinquency rates began to spike. Fannie Mae's losses in the mortgage security market in 2006 and 2007, along with the losses of the related GSE 'Freddie Mac', had caused its share value to plummet, stoking fears that it may collapse. On September 7th 2008, Fannie Mae was taken into government conservatorship along with Freddie Mac, with their stocks being delisted from stock exchanges in 2010. This act was seen as an unprecedented direct intervention into the economy by the U.S. government, and a symbol of how far the U.S. housing market had fallen.

Graph and download economic data for Government-Sponsored Enterprises; Acquired Property (Net) of Fannie Mae (Includes All GSEs Before 2000:Q4), Book Value, Level (BOGZ1FL405013113Q) from Q4 1945 to Q1 2025 about fannie mae, book, GSE, Net, and USA.

This dataset provides information about the number of properties, residents, and average property values for Fannie Mae Road cross streets in Camden, MS.

The FHFA House Price Index (FHFA HPI®) is the nation’s only collection of public, freely available house price indexes that measure changes in single-family home values based on data from all 50 states and over 400 American cities that extend back to the mid-1970s. The FHFA HPI incorporates tens of millions of home sales and offers insights about house price fluctuations at the national, census division, state, metro area, county, ZIP code, and census tract levels. FHFA uses a fully transparent methodology based upon a weighted, repeat-sales statistical technique to analyze house price transaction data. ​ What does the FHFA HPI represent? The FHFA HPI is a broad measure of the movement of single-family house prices. The FHFA HPI is a weighted, repeat-sales index, meaning that it measures average price changes in repeat sales or refinancings on the same properties. This information is obtained by reviewing repeat mortgage transactions on single-family properties whose mortgages have been purchased or securitized by Fannie Mae or Freddie Mac since January 1975.

The FHFA HPI serves as a timely, accurate indicator of house price trends at various geographic levels. Because of the breadth of the sample, it provides more information than is available in other house price indexes. It also provides housing economists with an improved analytical tool that is useful for estimating changes in the rates of mortgage defaults, prepayments and housing affordability in specific geographic areas.

U.S. Federal Housing Finance Agency, All-Transactions House Price Index for Connecticut [CTSTHPI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/CTSTHPI, August 2, 2023.

This dataset provides information about the number of properties, residents, and average property values for Fannie Mae Lane cross streets in Waynesville, NC.

United States - Government-Sponsored Enterprises; Acquired Property (Net) of Fannie Mae (Includes All GSEs Before 2000:Q4), Book Value, Transactions was -144.00000 Mil. of $ in January of 2025, according to the United States Federal Reserve. Historically, United States - Government-Sponsored Enterprises; Acquired Property (Net) of Fannie Mae (Includes All GSEs Before 2000:Q4), Book Value, Transactions reached a record high of 14276.00000 in July of 2010 and a record low of -6688.00000 in April of 2011. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Government-Sponsored Enterprises; Acquired Property (Net) of Fannie Mae (Includes All GSEs Before 2000:Q4), Book Value, Transactions - last updated from the United States Federal Reserve on July of 2025.

As stated by the source, these annual county indexes should be considered developmental. As with the standard FHFA HPIs, revisions to these indexes may reflect the impact of new data or technical adjustments. Indexes are calibrated using appraisal values and sales prices for mortgages bought or guaranteed by Fannie Mae and Freddie Mac. As discussed in the Working Paper 16-01, in cases where sample sizes are small for the county area, an index is either not reported if recording has not started or a missing value is reported with a period (.). Index values always reflect the native county index, i.e. they are not made with data from another area or year.

For tracking and feedback purposes, please cite Working Paper 16-01 when using these data. A suggested form is: Bogin, A., Doerner, W. and Larson, W. (2016). Local House Price Dynamics: New Indices and Stylized Facts. Federal Housing Finance Agency, Working Paper 16-01. The working paper is accessible at http://www.fhfa.gov/papers/wp1601.aspx.

description: The FHFA House Price Index (HPI) is a broad measure of the movement of single-family house prices. The HPI is a weighted, repeat-sales index, meaning that it measures average price changes in repeat sales or refinancings on the same properties. This information is obtained by reviewing repeat mortgage transactions on single-family properties whose mortgages have been purchased or securitized by Fannie Mae or Freddie Mac since January 1975.; abstract: The FHFA House Price Index (HPI) is a broad measure of the movement of single-family house prices. The HPI is a weighted, repeat-sales index, meaning that it measures average price changes in repeat sales or refinancings on the same properties. This information is obtained by reviewing repeat mortgage transactions on single-family properties whose mortgages have been purchased or securitized by Fannie Mae or Freddie Mac since January 1975.

FHFA House Price IndexThe FHFA House Price Index (FHFA HPI®) is a comprehensive​ collection of publicly available house price indexes that measure changes in single-family home values based on data that extend back to the mid-1970s from all 50 states and over 400 American cities. The FHFA HPI incorporates tens of millions of home sales and offers insights about house price fluctuations at the national, census division, state, metro area, county, ZIP code, and census tract levels. FHFA uses a fully transparent methodology based upon a weighted, repeat-sales statistical technique to analyze house price transaction data.What does the FHFA HPI represent?The FHFA HPI is a broad measure of the movement of single-family house prices. The FHFA HPI is a weighted, repeat-sales index, meaning that it measures average price changes in repeat sales or refinancings on the same properties. This information is obtained by reviewing repeat mortgage transactions on single-family properties whose mortgages have been purchased or securitized by Fannie Mae or Freddie Mac since January 1975.The FHFA HPI serves as a timely, accurate indicator of house price trends at various geographic levels. Because of the breadth of the sample, it provides more information than is available in other house price indexes. It also provides housing economists with an improved analytical tool that is useful for estimating changes in the rates of mortgage defaults, prepayments and housing affordability in specific geographic areas.

As stated by the source, these annual county indexes should be considered developmental. As with the standard FHFA HPIs, revisions to these indexes may reflect the impact of new data or technical adjustments. Indexes are calibrated using appraisal values and sales prices for mortgages bought or guaranteed by Fannie Mae and Freddie Mac. As discussed in the Working Paper 16-01, in cases where sample sizes are small for the county area, an index is either not reported if recording has not started or a missing value is reported with a period (.). Index values always reflect the native county index, i.e. they are not made with data from another area or year.

For tracking and feedback purposes, please cite Working Paper 16-01 when using these data. A suggested form is: Bogin, A., Doerner, W. and Larson, W. (2016). Local House Price Dynamics: New Indices and Stylized Facts. Federal Housing Finance Agency, Working Paper 16-01. The working paper is accessible at http://www.fhfa.gov/papers/wp1601.aspx.

During the Global Financial Crisis of 2007-2008, a number of systemically important financial institutions in the United States declared bankruptcy, sought takeovers to prevent financial failure, or turned to the U.S. government for bailouts. Two of these institutions, Fannie Mae and Freddie Mac, were government-sponsored enterprises (GSEs), meaning that they were set up by the federal government in order to steer credit towards lower income homebuyers through interventions in the secondary mortgage market. While both were chartered by the government, they were also publicly traded companies, with a majority of shares owned by private investors. The fall of Fannie Mae and Freddie Mac These GSEs' business model was based on buying mortgages from their originators (banks, mortgage brokers, etc.) and then packaging groups of these mortgages together as mortgage-backed securities (MBS), before selling these on again to private investors. While this allowed the expansion of mortgage credit, meaning that many Americans were able to buy houses who would not have in other cases, this also contributed to the growing speculation in the housing market and related financial derivatives, such as MBS. The lowering of mortgage lending standards by originators in the early 2000s, as well as the need for GSEs to compete with their private sector rivals, meant that Fannie Mae and Freddie Mac became caught up in the financial mania associated with the early 2000s U.S. housing bubble. As their losses mounted due to the bursting of the bubble in 2007, both companies came under increasing financial stress, finally being brought into government conservatorship in September 2008. Fannie Mae and Freddie Mac were eventually unlisted from stock exchanges in 2010.

As stated by the source, these annual county indexes should be considered developmental. As with the standard FHFA HPIs, revisions to these indexes may reflect the impact of new data or technical adjustments. Indexes are calibrated using appraisal values and sales prices for mortgages bought or guaranteed by Fannie Mae and Freddie Mac. As discussed in the Working Paper 16-01, in cases where sample sizes are small for the county area, an index is either not reported if recording has not started or a missing value is reported with a period (.). Index values always reflect the native county index, i.e. they are not made with data from another area or year.

For tracking and feedback purposes, please cite Working Paper 16-01 when using these data. A suggested form is: Bogin, A., Doerner, W. and Larson, W. (2016). Local House Price Dynamics: New Indices and Stylized Facts. Federal Housing Finance Agency, Working Paper 16-01. The working paper is accessible at http://www.fhfa.gov/papers/wp1601.aspx.

Section 215(b) of NAHA requires that the initial purchase price or after-rehabilitation value of homeownership units assisted with HOME funds not exceed 95 percent of the area median purchase price for single family housing, as determined by HUD. Historically, HUD used the FHA Single Family Mortgage Limit (known as the 203(b) limits) as a surrogate for 95 percent of area median purchase price. However, statutory changes require the 203(b) limits to be set at 125 percent of area median purchase price. Consequently, participating jurisdictions (PJs) can no longer use the 203(b) limits as the HOME Program homeownership value limits (i.e., initial purchase price or after rehabilitation value).In 2024, HUD made a major revision to the homeownership value limit methodology outlined in In Section 92.254(a)(2)(iii) of the Final Rule published on July 24, 2013, For existing housing, HUD will now be using the greater (rather than the lesser) of the state non-metropolitan and US non-metropolitan media sales values as the minimum value in which the limit is calculated. This change will substitute more local, state-level data for national-level data. This new methodology is effective September 1, 2024.Newly Constructed Housing: The HOME homeownership value limits for newly constructed HOME units is 95 percent of the median purchase price for the area based on Federal Housing Administration (FHA) single family mortgage program data for newly constructed housing. Nationwide, HUD established a minimum limit, or floor, based on 95 percent of the U.S. median purchase price for new construction for nonmetropolitan areas. HUD has used the greater of these two figures as their HOME homeownership value limits for newly constructed housing in each area. HUD has also decreased the minimum number of sales transactions from 10 to 5 for the calculation of a state-level non-metro median sales price.Existing Housing: The HOME homeownership value limits for existing HOME units is 95 percent of the median purchase price for the area based on Federal FHA single family mortgage program data for existing housing and other appropriate data (Federal Housing Finance Agency (FHFA) data on purchase mortgages securitized by Fannie Mae and Freddie Mac) that are available nationwide for sale of existing housing in standard condition. There are two states and the District of Columbia that have no non-metropolitan areas. HUD made a technical correction in 2024 to the rule that sets this minimum purchase prices as the greater of the state non-metro or the US non-metro median. HUD calculates for each state its non-metropolitan median purchase price as well as the US non-metropolitan median purchase price. The greater of these medians serves as the “state floor price” for maximum purchase price limits on existing homes. Note that this represents a change to the methods, as previous practice was to use the lesser of these medians.PJ Determined Limits: In lieu of the limits provided by HUD, a PJ may determine 95 percent of the median area purchase price for single family housing in the jurisdiction annually in accordance with procedures established at § 92.254(a)(2)(iii). The PJ must submit these limits as part of its Consolidated Plan/Annual Action Plan.The effective date of the 2024 Homeownership Value Limits is September 1, 2024. These limits remain in effect until HUD issues new limits.

As stated by the source, these annual county indexes should be considered developmental. As with the standard FHFA HPIs, revisions to these indexes may reflect the impact of new data or technical adjustments. Indexes are calibrated using appraisal values and sales prices for mortgages bought or guaranteed by Fannie Mae and Freddie Mac. As discussed in the Working Paper 16-01, in cases where sample sizes are small for the county area, an index is either not reported if recording has not started or a missing value is reported with a period (.). Index values always reflect the native county index, i.e. they are not made with data from another area or year.

For tracking and feedback purposes, please cite Working Paper 16-01 when using these data. A suggested form is: Bogin, A., Doerner, W. and Larson, W. (2016). Local House Price Dynamics: New Indices and Stylized Facts. Federal Housing Finance Agency, Working Paper 16-01. The working paper is accessible at http://www.fhfa.gov/papers/wp1601.aspx.

House Price Index MoM in the United States decreased to -0.40 percent in April from 0 percent in March of 2025. This dataset includes a chart with historical data for the United States FHFA House Price Index MoM.

Mortgage Backed Security Market Outlook

The global mortgage-backed security (MBS) market size was valued at approximately $2.1 trillion in 2023 and is projected to reach $3.5 trillion by 2032, growing at a CAGR of 5.5%. A key driver of this growth is the increasing demand for mortgage-backed securities due to their ability to provide liquidity and diversify investment portfolios. The growth is further stimulated by favorable government policies and increased homeownership rates, which collectively bolster the issuance of new MBS.

One of the primary growth factors for the MBS market is the low-interest-rate environment, which has persisted over recent years. This scenario has encouraged borrowing and refinancing activities, leading to a higher number of mortgages that can be securitized. Moreover, the stability and relatively lower risk associated with MBS compared to other investment vehicles make them an attractive option for institutional investors. Additionally, advancements in financial technology have streamlined the process of bundling and selling these securities, increasing market efficiency.

Another significant factor contributing to the expansion of the MBS market is the role of government-sponsored enterprises (GSEs) such as Fannie Mae, Freddie Mac, and Ginnie Mae. These GSEs guarantee a significant portion of the residential MBS, providing a safety net that minimizes risk for investors. The support from these entities ensures a continuous and reliable flow of investment into the housing sector, which in turn stimulates further securitization of mortgages. Moreover, government policies aimed at bolstering housing finance systems in emerging markets are expected to create additional opportunities for growth.

The diversification of mortgage products, including the rise in demand for commercial mortgage-backed securities (CMBS), is another driving force for the market. Commercial real estate has shown robust growth, and investors are increasingly looking towards CMBS as a way to gain exposure to this sector. The structured nature of these securities, offering tranches with varying risk and return profiles, allows investors to tailor their investment strategies according to their risk tolerance.

In the context of the MBS market, Lenders Mortgage Insurance (LMI) plays a crucial role in facilitating homeownership, especially for borrowers who are unable to provide a substantial down payment. LMI is a type of insurance that protects lenders against the risk of borrower default, allowing them to offer loans with lower down payment requirements. This insurance is particularly significant in markets where home prices are high, and saving for a large deposit is challenging for many potential homeowners. By mitigating the risk for lenders, LMI enables more individuals to enter the housing market, thereby supporting the overall growth of mortgage-backed securities. As a result, LMI not only aids in increasing homeownership rates but also contributes to the liquidity and stability of the housing finance system.

Type Analysis

The mortgage-backed security market is bifurcated into Residential MBS and Commercial MBS. Residential MBS (RMBS) dominate the market due to the larger volume of residential mortgages compared to commercial ones. RMBS are typically backed by residential loans, including home mortgages, and are considered less risky. They offer a steady income stream to investors through mortgage payments made by homeowners. The demand for RMBS is bolstered by the high rate of homeownership and the continuous flow of new mortgages.

On the other hand, Commercial MBS (CMBS) are seeing increased traction due to their attractive yields and the growth of the commercial real estate sector. CMBS are backed by loans on commercial properties such as office buildings, retail centers, and hotels. They offer investors exposure to the commercial property market, which is often less correlated with the residential real estate market, providing an additional layer of diversification. The complexity and higher risk associated with CMBS attract sophisticated investors looking for higher returns.

Within RMBS, the market is further segmented into agency RMBS and non-agency RMBS. Agency RMBS are guaranteed by GSEs, making them more secure and attractive to risk-averse investors. Non-agency RMBS, though not backed by GSEs, offer higher yields and are appealing to investors with a higher risk appetite. The interplay betw

As stated by the source, these annual county indexes should be considered developmental. As with the standard FHFA HPIs, revisions to these indexes may reflect the impact of new data or technical adjustments. Indexes are calibrated using appraisal values and sales prices for mortgages bought or guaranteed by Fannie Mae and Freddie Mac. As discussed in the Working Paper 16-01, in cases where sample sizes are small for the county area, an index is either not reported if recording has not started or a missing value is reported with a period (.). Index values always reflect the native county index, i.e. they are not made with data from another area or year.

For tracking and feedback purposes, please cite Working Paper 16-01 when using these data. A suggested form is: Bogin, A., Doerner, W. and Larson, W. (2016). Local House Price Dynamics: New Indices and Stylized Facts. Federal Housing Finance Agency, Working Paper 16-01. The working paper is accessible at http://www.fhfa.gov/papers/wp1601.aspx.

The Housing Trust Fund (HTF) statute, section 1338(c)(7)(B)(ii), requires housing for homeownership to have an initial purchase price that meets the requirements of section 215(b)(1) of the Cranston-Gonzalez National Affordable Housing Act (HOME statute). The HTF Interim Rule at 24 CFR 93.305(a) requires that the initial purchase price or after-rehabilitation value of homeownership units assisted with HTF funds meet the definition of modest housing and that the purchase price of HTF assisted single family housing cannot exceed 95 percent of the median purchase price for the area for newly constructed or standard housing. In 2024, HUD adjusted the methodology for calculating the homeownership value limits. For existing housing, HUD will now be using the greater (rather than the lesser) of the state non-metropolitan and US non-metropolitan media sales values as the minimum value in which the limit is calculated. This change will substitute more local, state-level data for national-level data. This new methodology is effective September 1, 2024.Newly Constructed Housing: The HTF homeownership value limits for newly constructed HTF units is 95 percent of the median purchase price for the area based on Federal Housing Administration (FHA) single family mortgage program data for newly constructed housing. Nationwide, HUD has established a minimum limit, or floor, based on 95 percent of the U.S. median purchase price for new construction for non- metropolitan areas. HUD has used the greater of these two figures as their HTF homeownership value limit for newly constructed housing in each area. HUD has also decreased the minimum number of sales transactions from 10 to 5 for the calculation of a state-level non-metro median sales price.Existing Housing: The HTF homeownership value limit for existing HTF units is 95 percent of the median purchase price for the area based on Federal FHA single family mortgage program data for existing housing and other appropriate data (Federal Housing Finance Agency (FHFA) data on purchase mortgages securitized by Fannie Mae and Freddie Mac) that are available nationwide for sale of existing housing in standard condition. There are two states and the District of Columbia that have no non-metropolitan areas. HUD made a technical correction in 2024 to the rule that sets this minimum purchase prices as the greater of the state non-metro or the US non-metro median. HUD calculates for each state its non-metropolitan median purchase price as well as the US non-metropolitan median purchase price. The greater of these medians serves as the “state floor price” for maximum purchase price limits on existing homes. Note that this represents a change to the methods, as previous practice was to use the lesser of these medians.Grantee Determined Limits: In lieu of the limits provided by HUD, an HTF grantee may determine 95 percent of the median area purchase price for single family housing in the jurisdiction annually in accordance with procedures established at § 93.305(a)(2).The grantee must submit these limits as part of its HTF allocation plan.The effective date of the 2024 Homeownership Value Limits is September 1, 2024. These limits remain in effect until HUD issues new limits.

As stated by the source, these annual county indexes should be considered developmental. As with the standard FHFA HPIs, revisions to these indexes may reflect the impact of new data or technical adjustments. Indexes are calibrated using appraisal values and sales prices for mortgages bought or guaranteed by Fannie Mae and Freddie Mac. As discussed in the Working Paper 16-01, in cases where sample sizes are small for the county area, an index is either not reported if recording has not started or a missing value is reported with a period (.). Index values always reflect the native county index, i.e. they are not made with data from another area or year.

For tracking and feedback purposes, please cite Working Paper 16-01 when using these data. A suggested form is: Bogin, A., Doerner, W. and Larson, W. (2016). Local House Price Dynamics: New Indices and Stylized Facts. Federal Housing Finance Agency, Working Paper 16-01. The working paper is accessible at http://www.fhfa.gov/papers/wp1601.aspx.

As stated by the source, these annual county indexes should be considered developmental. As with the standard FHFA HPIs, revisions to these indexes may reflect the impact of new data or technical adjustments. Indexes are calibrated using appraisal values and sales prices for mortgages bought or guaranteed by Fannie Mae and Freddie Mac. As discussed in the Working Paper 16-01, in cases where sample sizes are small for the county area, an index is either not reported if recording has not started or a missing value is reported with a period (.). Index values always reflect the native county index, i.e. they are not made with data from another area or year.

For tracking and feedback purposes, please cite Working Paper 16-01 when using these data. A suggested form is: Bogin, A., Doerner, W. and Larson, W. (2016). Local House Price Dynamics: New Indices and Stylized Facts. Federal Housing Finance Agency, Working Paper 16-01. The working paper is accessible at http://www.fhfa.gov/papers/wp1601.aspx.