Federal Housing Finance Agency Print

Research

​Research

 

Our economists conduct research on a range of topics in housing finance, including analyzing data and uncovering emerging trends.  In addition to presenting their research to policy makers, they share their research at academic conferences and publish in journals and other scholarly outlets.  Our work enables those interested in housing finance to make decisions based on the best information available.

In particular, our researchers focused on housing trends in house prices, housing market conditions, and mortgage lending activity.  In addition, we analyze the risk and capital adequacy of the housing government-sponsored enterprises and publish papers aimed at improving public understanding of the mortgage finance system.

See FHFA's Copyright and Permissions Notice.

 Papers

 

 

Working Paper 22-04: Effects of Mortgage Interest Rates on House Price Appreciation: The Role of Payment Constraints38402<p>​Abstract&#58; This research examines the effects of mortgage interest rates on house prices in the 100 largest U.S. cities, with appreciation driven by both short-run dynamics and convergence towards long-run economic fundamentals.&#160; The nature of the long-run equilibrium depends on the elasticity of housing supply, and the speed of adjustment to this long-run equilibrium depends on the degree to which borrowers are near monthly debt service payment constraints. Accordingly, the pass-through of mortgage interest rates to house prices is location and time-varying. This has implications for our understanding of monetary policy transmission, systemic risk, and the role of household finances in the macroeconomy.<br></p>11/17/2022 10:01:58 PMHome / Policy, Programs & Research / Research / Working Paper 22-04: Effects of Mortgage Interest Rates on House Price Appreciation: The Role of Payment Constraints 1100https://www.fhfa.gov/PolicyProgramsResearch/Research/Pages/Forms/AllItems.aspxhtmlFalseaspx
Working Paper 22-01: Mortgage Appraisal Waivers and Prepayment Speeds38335<h4 style="font-size&#58;13px;font-style&#58;normal;">​​Abstract&#58;</h4><p style="font-style&#58;normal;"> <span style="line-height&#58;22px;">​This paper examines factors affecting the use of appraisal waivers for mortgages guaranteed by Fannie Mae and Freddie Mac and the effect of appraisal waivers on prepayment speeds. We find that the alignment of Freddie Mac’s eligibility criteria with those of Fannie Mae around the start of the COVID-19 pandemic was associated with an increase in the use of appraisal waivers. Conditional on satisfying the basic eligibility criteria, appraisal waivers are more common for refinance loans, loans serviced by nonbanks, and less risky borrowers. We also find that appraisal waivers were associated with higher conditional prepayment rates during 2020, but to a lesser extent in 2021 as refinancing activity slowed down. Much of this association can be explained by correlations between appraisal waivers and other observable determinants of prepayment speeds.​</span></p> ​<br>11/7/2022 3:00:24 PMHome / Policy, Programs & Research / Research / Working Paper 22-01: Mortgage Appraisal Waivers and Prepayment Speeds Joshua Bosshardt; William M. Doerner; Fan Xu 1010https://www.fhfa.gov/PolicyProgramsResearch/Research/Pages/Forms/AllItems.aspxhtmlFalseaspx
Working Paper 22-02: Housing Supply and Liquidity in the COVID-19 Era38334<h4 style="font-size&#58;13px;font-style&#58;normal;">​​Abstract&#58;</h4><p style="font-style&#58;normal;"> <span style="line-height&#58;22px;"> ​We document changes in national housing supply and liquidity during the COVID-19 era using a suite of monthly indices, ranging from summary statistics (mean and median time on the market, proportion of homes sold, etc.) to more advanced econometric indices that can address censoring and unobserved heterogeneity. Our results indicate a sharp structural break in most of the indices near the start of COVID-19 in March 2020,&#160;though each index’s most likely break date varies by a few months. Our findings suggest that the start of the pandemic saw a supply decrease, followed by an immediate and sustained price increase. Listings became more likely to be withdrawn, but those that sold did so faster relative to pre-COVID levels, indicating a change in the distribution of housing market liquidity. Finally, our results suggest that there were different types of structural breaks, specifically changes in the level, slope, and seasonality of the indices.​</span>​<br></p>11/7/2022 3:00:21 PMHome / Policy, Programs & Research / Research / Working Paper 22-02: Housing Supply and Liquidity in the COVID-19 Era We document changes in national housing supply and 851https://www.fhfa.gov/PolicyProgramsResearch/Research/Pages/Forms/AllItems.aspxhtmlFalseaspx
Working Paper 22-03: Applying Seasonal Adjustments to Housing Markets38332<h4 style="font-size&#58;13px;font-style&#58;normal;">​​Abstract&#58;</h4><p style="font-style&#58;normal;"> <span style="line-height&#58;22px;">​House price seasonality has been increasing over the last decade, but adjustments have remained largely unchanged in commonly used public data. This paper shows how seasonal adjustments work—both theoretically and applied to observed transactions—​when constructing house price indices (HPIs). In this paper, we find the seasonality in the housing market is not uniform across geographies. Evidence is provided about where adjustments are more necessary, how often they should be recalculated, and how the weather-related variables, social and industry characteristics impact difference between adjusted and non-adjusted HPI. Using the Federal Housing Finance Agency's (FHFA's) entire suite of public indices, we update adjustments that have been provided by the FHFA and offer new adjustments for over 400 metropolitan areas and other geographies, which haven't been provided before. We find the difference between previous and updated adjusted indices are relatively small, with slight improvement in recent years.​​</span>​<br></p>11/7/2022 3:00:18 PMHome / Policy, Programs & Research / Research / Working Paper 22-03: Applying Seasonal Adjustments to Housing Markets House price seasonality has been increasing over the last 888https://www.fhfa.gov/PolicyProgramsResearch/Research/Pages/Forms/AllItems.aspxhtmlFalseaspx
The Size of the Affordable Mortgage Market: 2022-2024 Enterprise Single-Family Housing Goals - December 202136648<p><span style="font-size&#58;13px;">In establishing benchmarks for the single-family home purchase and refinance goals for Fannie Mae and Freddie Mac (the Enterprises), the Federal Housing Finance Agency (FHFA) is required to measure the size of the affordable mortgage market.&#160; This FHFA technical report documents the statistical forecast models that the modeling team has developed as part of the process for establishing the affordable housing goal benchmark levels for the Enterprises for 2022 through 2024.​</span><br></p>12/22/2021 3:30:33 PMHome / Policy, Programs & Research / Research / The Size of the Affordable Mortgage Market: 2022-2024 Enterprise Single-Family Housing Goals - December 2021 2210https://www.fhfa.gov/PolicyProgramsResearch/Research/Pages/Forms/AllItems.aspxhtmlFalseaspx
Working Paper 21-03: The Riskiness of Outstanding Mortgages in the United States, 1999 – 201936688<p>​Abstract&#58; This paper introduces summary measures of credit risk for the stock of all outstanding mortgages in the United States for each quarter between 1999 and 2019. Mortgage terminations play a fundamental role in offsetting risk introduced by the flow of new originations because of refinance activity and the often dual nature of home buyers as concurrent sellers. To illustrate these concepts in a policy setting, I show the Home Affordable Refinance Program increased origination risk metrics but reduced overall risk due to the associated terminations of even riskier loans. Generally, book-level risk tends to lag behind originations&#58; while origination risk peaked in 2006, the risk of outstanding mortgages peaked in 2007, and while origination risk bottomed out in 2011 and has been rising since, book-level risk continued its downward trend in 2019. Other results highlight previously rarely-examined market segments, including credit unions, the Federal Home Loan Bank system, and loans guaranteed by the Farm Service Agency/Rural Housing Service.<br></p>11/1/2021 3:00:17 PMHome / Policy, Programs & Research / Research / Working Paper 21-03: The Riskiness of Outstanding Mortgages in the United States, 1999 – 2019 To illustrate these concepts in a 3036https://www.fhfa.gov/PolicyProgramsResearch/Research/Pages/Forms/AllItems.aspxhtmlFalseaspx
Working Paper 21-02: Borrower Expectations and Mortgage Performance: Evidence from the COVID-19 Pandemic35980<p>​We assess issues related to borrower beliefs and mortgage performance using new individual panel data that simultaneously cover borrower expectations, forbearance status during the COVID-19 pandemic, and a wide array of demographic characteristics. First, we establish the determinants of borrower expectations, with local experiences and those of social networks playing important roles. We then show that households who, at origination, were optimistic about future house price appreciation or pessimistic about the possibility of future unemployment were more likely to enter forbearance in 2020. However, by early&#160;2021, appreciation-optimistic borrowers who were in forbearance were likely to have cured or prepaid their loan, while those who expected unemployment were likely to still be in forbearance.&#160; We offer three channels by which expectations affect forbearance behavior&#58; choices of initial loan terms, associations with actual future events, and factors related to belief formation that are also plausibly associated with forbearance. Our findings highlight the crucial role borrower expectations play in both leverage choices and mortgage performance.<br></p>10/29/2021 6:00:12 PMHome / Policy, Programs & Research / Research / Working Paper 21-02: Borrower Expectations and Mortgage Performance: Evidence from the COVID-19 Pandemic 2802https://www.fhfa.gov/PolicyProgramsResearch/Research/Pages/Forms/AllItems.aspxhtmlFalseaspx
The Size of the Affordable Mortgage Market: 2022-2024 Enterprise Single Family Housing Goals36164<p>In establishing benchmarks for the single-family home purchase housing goals for Fannie Mae and Freddie Mac (the Enterprises), the Federal Housing Finance Agency (FHFA) is required to measure the size of the mortgage market. This FHFA technical report documents the statistical forecast models that the modeling team has developed as part of the process for establishing the affordable housing goal benchmark levels for Fannie Mae and Freddie Mac for 2022 through 2024.<br><br></p>8/18/2021 3:08:43 PMHome / Policy, Programs & Research / Research / The Size of the Affordable Mortgage Market: 2022-2024 Enterprise Single Family Housing Goals Ken Lam, Omena Ubogu, Jay Schultz 1975https://www.fhfa.gov/PolicyProgramsResearch/Research/Pages/Forms/AllItems.aspxhtmlFalseaspx
Working Paper 21-01: A Flexible Method of House Price Index Construction using Repeat-Sales Aggregates33182<h4 style="font-size&#58;13px;"><span class="ms-rteThemeForeColor-2-0" style="line-height&#58;22px;display&#58;none;"></span></h4><h4 style="font-size&#58;13px;font-style&#58;normal;"><span class="ms-rteThemeForeColor-2-0" style="font-style&#58;normal;line-height&#58;22px;"><span style="font-style&#58;normal;line-height&#58;22px;">*Revised June 2022</span></span></h4><span style="color&#58;#444444;font-style&#58;normal;">&#160;​</span><span style="color&#58;#444444;font-style&#58;normal;"></span><h2>​Abstract&#58;<br></h2><p>The major issue which we address in this paper is the one-size-fits-all nature of the typical city-level house price index. In this vein, we make two contributions. First, we develop a new algorithm to ensure feasible estimation of geographically granular repeat-sales house price indices in cases of low transactions counts. This facilitates the estimation of a balanced panel of 63,122 Census tract-level repeat-sales house price indices (2010 definitions) at an annual frequency between 1989 and 2021, which we release alongside this paper. Second, we use these indices to estimate city-level house price indices that are robust to heterogeneous submarket appreciation and non-random sampling, two issues that confound classic approaches. Numerical simulations show this algorithm uncovers population indices even when house prices, quantities, and transaction sampling vary across locations and over time. This approach can be used in a flexible manner to calculate canonical price indices such as Lowe and Laspeyres, and more tailored summary indices on a variety of topics, including collateral valuation, climate risk assessment, or tracking changes to minority housing wealth over time.​<br></p><p><span style="font-style&#58;normal;"><span style="font-style&#58;normal;">T</span><span style="font-style&#58;normal;">he supertract-based census tract HPI</span><span style="font-style&#58;normal;">s</span><span style="font-style&#58;normal;">&#160;</span><span style="font-style&#58;normal;">constructed in this staff workin</span><span style="font-style&#58;normal;">g paper are available&#160;below.&#160;</span></span><span style="font-style&#58;normal;">Our&#160;</span><a href="/PolicyProgramsResearch/Research/PaperDocuments/wp2101-FAQs.pdf" target="_blank" style="font-style&#58;normal;font-size&#58;14px;font-family&#58;&quot;source sans pro&quot;, sans-serif;">FA​​Qs</a><span style="font-style&#58;normal;">&#160;address common questions about the indices</span><span style="font-style&#58;normal;">.</span><span style="font-style&#58;normal;">&#160;P</span><span style="font-style&#58;normal;">lease cite this working paper when using the supertract&#160;HPIs. The data files can be downloaded in a&#160;compressed format&#160;saved in&#160;t​he following file types&#58;</span><br></p><ul><li><span style="font-style&#58;normal;"><span style="font-style&#58;normal;"></span><span style="font-style&#58;normal;"><a href="/PolicyProgramsResearch/Research/PaperDocuments/wp2101-data-tract-csv.zip" target="_blank">CSV</a> [29MB compressed, 229MB extracted]</span></span></li><li><span style="font-style&#58;normal;"><span style="font-style&#58;normal;"><a href="/PolicyProgramsResearch/Research/PaperDocuments/wp2101-data-tract-dta.zip" target="_blank">DTA</a> (</span><span style="font-style&#58;normal;">Stata)</span>​ [62MB compressed, 254MB extracted]</span></li></ul>6/23/2022 2:55:15 AMHome / Policy, Programs & Research / Research / Working Paper 21-01: A Flexible Method of House Price Index Construction using Repeat-Sales Aggregates In this vein, we make two 3758https://www.fhfa.gov/PolicyProgramsResearch/Research/Pages/Forms/AllItems.aspxhtmlFalseaspx
Working Paper 20-02: Nowcasting Unemployment Insurance Claims in the Time of COVID-1928208<font color="#000000" face="Times New Roman" size="3"> </font><h4>Abstract&#58; </h4><p>Near term forecasts, also called nowcasts, are most challenging but also most important when the economy experiences an abrupt change. In this paper, we explore the performance of models with different information sets and data structures in order to best nowcast US initial unemployment claims in spring of 2020 in the midst of the COVID-19 pandemic. We show that the best model, particularly near the structural break in claims, is a state-level panel model that includes dummy variables to capture the variation in timing of state-of-emergency declarations. Autoregressive models perform poorly at first but catch up relatively quickly. Models including Google Trends are outperformed by alternative models in nearly all periods. Our results suggest that in times of structural change there is a bias-variance tradeoff. Early on, simple approaches to exploit relevant information in the cross sectional dimension improve forecasts, but in later periods the efficiency of autoregressive models dominates.</p><font color="#000000" face="Times New Roman" size="3"> </font>8/6/2020 8:12:46 PMHome / Policy, Programs & Research / Research / Working Paper 20-02: Nowcasting Unemployment Insurance Claims in the Time of COVID-19 Near term forecasts, also called nowcasts 2759https://www.fhfa.gov/PolicyProgramsResearch/Research/Pages/Forms/AllItems.aspxhtmlFalseaspx

© 2022 Federal Housing Finance Agency