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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.

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Working Paper 16-01: Local House Price Dynamics: New Indices and Stylized Facts19006<h4 style="font-size&#58;13px;font-style&#58;normal;font-variant&#58;normal;">​​Abstract&#58;</h4><p style="font-style&#58;normal;font-variant&#58;normal;">W<span style="line-height&#58;22px;">e construct the first large-scale panel of annual house price indices for cities, counties, 3-digit ZIP codes, and 5-digit ZIP codes in the United States from 1975 through 2015 using source data with nea</span><span style="line-height&#58;22px;">rly 100 million transactions. Appreciation rates decrease with distance from the central business district (CBD) in large cities, suggesting an overall increase in the desirability of housing units in CBD locations and a general steepening of the house price gradient. Real house prices are more likely to be non-stationary near the CBD than in the suburbs, a finding consistent with a higher elasticity of housing supply near the edge of the city. Sustained real price increases and high price volatility near the centers of large cities suggest a lower supply elasticity in these locations.&#160;</span></p><p style="font-style&#58;normal;font-variant&#58;normal;"> <span style="line-height&#58;22px;">The ZIP5 HPIs constructed in this staff working paper can be <a href="/DataTools/Downloads/Documents/HPI/HPI_AT_ZIP5.xlsx" target="_blank">downloaded</a> on the HPI Downloadable Data page and are viewable in an <a href="/DataTools/Tools/Pages/HPI-ZIP5-Map.aspx" target="_blank">interactive map</a> under the &quot;Data &amp; Tools&quot; page. Our <a href="/PolicyProgramsResearch/Research/PaperDocuments/wp1601_FAQs_ZIP5_HPIs.pdf" target="_blank">FAQs</a> address common questions.&#160;Please cite this working paper when using the dataset.</span></p>5/25/2016 12:30:51 PM3336http://www.fhfa.gov/PolicyProgramsResearch/Research/Pages/Forms/AllItems.aspxhtmlFalseaspx
The Size of the Affordable Mortgage Market: 2015-2017 Enterprise Single-Family Housing Goals18381<p><span style="line-height&#58;1.6;">I</span><span style="line-height&#58;1.6;">n establishing benchmarks for the 2015, 2016, and 2017 single-family mortgage 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 paper documents the methodology used to estimate the market size for the Low-Income Borrower Home Purchase Housing Goal (share of borrowers with incomes no greater than 80 percent of the area median income (AMI)), the Very Low-Income Borrower Home Purchase Housing Goal (share of borrowers with incomes no greater than 50 percent of AMI), the Low-Income Areas Home Purchase Housing Subgoal (share of borrowers living in low-income areas (where census tract median income is no greater than 80 percent of AMI) and of borrowers with incomes no greater than AMI living in high minority areas), and the Low-Income Borrower Refinance Housing Goal (share of borrowers with incomes no greater than 80 percent of AMI).</span></p>8/19/2015 5:00:34 PM1543http://www.fhfa.gov/PolicyProgramsResearch/Research/Pages/Forms/AllItems.aspxhtmlFalseaspx
Working Paper 15-3: Additional Market Risk Shocks: Prepayment Uncertainty and Option-Adjusted Spreads18211<p><span style="line-height&#58;150%;font-family&#58;&quot;times new roman&quot;,&quot;serif&quot;;font-size&#58;12pt;"><span><span></span></span></span>&#160;</p><h4 style="font-size&#58;13px;"></h4><span><span><h4 style="font-size&#58;13px;">​​Abstract&#58;</h4><p>Assessments of market risk for economic or regulatory capital typically involve calculating a portfolio’s sensitivity to key risk factor movements.&#160; Historically, practitioners have focused on two classical sources of risk, adverse changes in interest rates and volatility.&#160; As stress testing has evolved, additional risk factors have been identified, including several specific to fixed-income securities with embedded optionality.&#160; These include changes in prepayment rates or any of several other market risk factors, which affect option-adjusted spreads (OAS).&#160; We describe an empirical framework for generating shocks to prepayment rates and mortgage security OAS, which are consistent with simultaneous movements in other key risk factors, including the term structure of interest rates and implied volatility.&#160; Our prepayment rate shocks capture model misspecification and are calculated using historical performance data from multiple vendor prepayment models.&#160; These shocks are well defined, but capture only a portion of prepayment model error.&#160; Mortgage security OAS serves as a broader measure of model error, which encompasses both, model misspecification and forecasting errors as well as credit and liquidity risk.&#160; Our OAS shocks are calculated using historical six-month changes in spreads derived from multiple vendor quotes.​​</p></span></span><p>&#160;</p>7/22/2015 2:00:28 PM1127http://www.fhfa.gov/PolicyProgramsResearch/Research/Pages/Forms/AllItems.aspxhtmlFalseaspx
Working Paper 15-2: The Marginal Effect of First-Time Homebuyer Status on Mortgage Default and Prepayment18135<p> <strong>Abstract&#58;</strong></p><p> This paper examines the loan performance of Fannie Mae and Freddie Mac first-time homebuyer mortgages originated from 1996 to 2012. First-time homebuyer mortgages generally perform worse than repeat homebuyer mortgages. But first-time homebuyers are younger and have lower credit scores, home equity, and income than repeat home-buyers, and therefore are comparatively less likely to withstand financial stress or take advantage of financial innovations available in the market. The distributional make-up of first-time homebuyers is different than that of repeat homebuyers in terms of many borrower, loan, and property characteristics that can be determined at the time of loan origination. Once these distributional differences are accounted for in an econometric model, there is virtually no difference between the average first-time and repeat home-buyers in their probabilities of mortgage default. Hence, the difference between the first-time and repeat homebuyer mortgage defaults can be attributed to the difference in the distributional make-up of the two groups and not to the premise that first-time homebuyers are an inherently riskier group. However, there appears to be an inherent difference in the prepayment probabilities of first-time and repeat homebuyers holding borrower, loan, and property characteristics constant. First-time homebuyers are less likely to prepay their mortgages compared to repeat homebuyers even after accounting for the distributional make-up of the two groups using information known at the time of loan origination.</p><p>&#160;</p>7/9/2015 2:00:09 PM1843http://www.fhfa.gov/PolicyProgramsResearch/Research/Pages/Forms/AllItems.aspxhtmlFalseaspx
Working Paper 15-1: How Low Can House Prices Go? Estimating a Conservative Lower Bound17846<h4 style="font-size&#58;13px;">​​Abstract&#58;</h4><p>We develop a theoretically-based statistical technique to identify a conservative lower bound for house prices. &#160;Leveraging a model based upon consumer and investor incentives, we are able to explain the depth of housing market downturns at both the national and state level over a variety of market environments. &#160;This approach performs well in several historical back tests and has strong out-of-sample predictive ability. &#160;When back-tested, our estimation approach does not understate house price declines in any state over the 1987 to 2001 housing cycle and only understates declines in three states during the most recent financial crisis. &#160;This latter result is particularly noteworthy given that the post-2001 estimates are performed out-of-sample. Our measure of a conservative lower bound is attractive because it (1) provides a leading indicator of the severity of future downturns and (2) allows trough estimates to dynamically adjust as markets conditions change. &#160;This estimation technique could prove particularly helpful in measuring the credit risk associated with portfolios of mortgage assets as part of evaluating static stress tests or designing dynamic stress tests.​​</p><p>A revised version of this paper has been accepted for publication by the <em>Journal of Real Estate Finance</em> and Economics and can be accessed at <a href="http&#58;//dx.doi.org/10.1007/s11146-015-9538-8" target="_blank">http&#58;//dx.doi.org/10.1007/s11146-015-9538-8</a>. The research has been presented at the Federal Reserve Bank of Richmond, the American Real Estate Society annual meeting, and the American Real Estate and Urban Economics Association national conference​. Popular news coverage has included Calculated Risk, GARP, HousingWire, Inside Mortgage Finance, and RealtyTrac. It was also selected as best paper in 2015 in real estate cycles by the American Real Estate Society.<br></p>11/9/2015 2:30:57 PM7315http://www.fhfa.gov/PolicyProgramsResearch/Research/Pages/Forms/AllItems.aspxhtmlFalseaspx
FHFA Working Paper 14-3: The Relationship between Second Liens, First Mortgage Outcomes, and Borrower Credit: 1996-201014955<p>​Abstract&#58;</p><p>To help inform the ongoing policy debate concerning the risks associated with second mortgages, the paper rigorously evaluates the effect of second liens on the performance of first mortgages.&#160;&#160; Using a dataset that combines credit bureau information with mortgage performance data, the statistical analysis separately quantifies the extent to which piggyback and subsequent second liens impacted loan default and prepayment likelihoods for first liens.&#160; In a simple direct comparison of first-lien outcomes, piggyback second liens are shown to have substantially increased mortgage default rates, while decreasing mortgage prepayment likelihoods.&#160; The results differ significantly, however, when the relative comparison group is altered and the analysis looks for a “residual” relationship (i.e., the control variables are changed in the statistical analysis).&#160;&#160; When first-lien outcomes are compared for borrowers with identical at-origination total equity and debt servicing obligations, the residual outcome differences tend to be minimal.&#160; Where material differences do exist, piggyback second liens tended to be associated with marginally worse outcomes for loans originated during the housing boom and slightly better outcomes for later years.&#160;&#160; With respect to subsequent second liens, models that evaluate the direct relationship between second liens and first-lien outcomes find a pronounced time trend.&#160; In the late 1990s and early 2000s, the origination of a second lien generally signaled better subsequent performance for the associated first mortgage, most likely because only the most creditworthy borrowers were able to get such loans.&#160;&#160; By the mid-2000s, the overall signal associated with subsequent second liens became negative—i.e., the underlying first mortgages performed materially worse than others.&#160; An abrupt switch at the inception of the housing bust is then evident, however, as second-lien-burdened first mortgages then performed better again.&#160; Models that control for total net equity and borrower debt obligations, i.e., seek the residual relationship between outcomes and second liens, show a consistent positive relationship between outcomes and subsequent second liens, but also reveal an interesting evolution over time.&#160; The paper concludes with a comparison of time trends for various nonmortgage credit statistics—including nonmortgage loan balances, revolving credit utilization rates, and credit scores—for borrowers with and without second liens.</p>9/18/2014 5:33:43 PM1971http://www.fhfa.gov/PolicyProgramsResearch/Research/Pages/Forms/AllItems.aspxhtmlFalseaspx
FHFA Brief 14-2: First-Time Homebuyer Share and House Price Growth13760<h4>Abstract&#58;</h4><p>This Brief provides historical, state-by-state statistics on the share of purchase-money mortgages for primary homes obtained by first-time homebuyers from 1996 to 2013. It also examines the relationship between first-time homebuyer activity and trends in house prices across states. Economic intuition suggests that increasing house prices could motivate potential first-time homebuyers to enter the market. However, rising house prices also suggests decreasing affordability, which affects the ability of first-time homebuyers to purchase a house when they are often just getting started professionally and still saving for a down payment. The Brief shows a weak negative relationship between changes in the relative first-time homebuyer activity and house price growth. That is, the first-time homebuyer share decreases as house price growth increases, or first-time homebuyer share increases as house price growth decreases. This relationship is very strong for certain states that saw the greatest house price swings in the last two decades. In high price-volatility states like California, Nevada, and Florida, first-time homebuyers have tended to account for a diminished share of mortgage borrowing when house price appreciation has been very high. </p><p>&#160;</p><p><a href="/PolicyProgramsResearch/Research/PaperDocuments/FHFA%20State-Level%20First-Time%20Hombuyer%20Share%20Excel%20Data.xls">FHFA State-Level First-Time Homebuyer Share Excel Data</a>&#160;(Excel)</p>5/13/2015 2:08:42 PM3509http://www.fhfa.gov/PolicyProgramsResearch/Research/Pages/Forms/AllItems.aspxhtmlFalseaspx
FHFA MORTGAGE ANALYTICS PLATFORM13757<p><strong>Background &amp; Introduction</strong></p><font size="3"><p>The Federal Housing Finance Agency (FHFA) maintains a proprietary Mortgage Analytics Platform to support the Agency’s strategic plan. The objective of this white paper is to provide interested stakeholders with a detailed description of the platform, as it is one of the tools the FHFA uses in policy analysis. The distribution of this white paper is part of a larger effort to increase transparency on mortgage performance and the analytical tools used for policy analysis and evaluation within the FHFA. </p> <p>The motivation to build the FHFA Mortgage Analytics Platform derived from the Agency’s need for an independent empirical view on multiple policy initiatives. Academic empirical studies may suffer from a lack of high quality data, while empirical work from inside the industry typically represents a specific view. The FHFA maintains several vendor platforms from which an independent view is possible, yet these platforms tend to be inflexible and opaque. The unique role of the FHFA as regulator and conservator necessitated platform flexibility and transparency to carry out its responsibilities. </p> <p>The FHFA Mortgage Analytics Platform is maintained on a continuous basis; as such, the material herein represents the platform as of the publication date of this document. As resources permit, this document will be updated to reflect enhancements to the platform. </p></font>7/10/2014 7:59:04 PM5075http://www.fhfa.gov/PolicyProgramsResearch/Research/Pages/Forms/AllItems.aspxhtmlFalseaspx
Working Paper 14-2: The Effects of Monetary Policy on Mortgage Rates13844<h4>​Abstract&#58;</h4><p>Economic events over the past decade have changed central bank policies in the United States and around the world. The housing and financial markets experienced significant changes as the markets first surpassed historical highs and then underwent a recession grave enough to draw comparison with the Great Depression. To spur recovery, the Federal Reserve first lowered short-term interest rates to near-zero and eventually embarked on several phases of large-scale asset purchases (LSAPs) to lower long-term interest rates and mortgage rates. This paper describes the evolution of the LSAP program and analyzes how interest rates and mortgage rates changed during that time. Both the long-term interest rates and mortgage rates reached historical lows in the post crisis period, primarily due to the Federal Reserve Board's accommodative policies. Two econometric approaches—an event study and a time series model—estimate the market response during each phase of the LSAP program and provide projections of mortgage rates under different shock assumptions. Results suggest that early tapering announcements helped reset interest rates and mortgage rates upwards and any rise in long-term interest rates resulting from unanticipated events (whether related to tapering or not) could lead to further increases in mortgage rates.</p>12/30/2014 8:45:00 PM1307http://www.fhfa.gov/PolicyProgramsResearch/Research/Pages/Forms/AllItems.aspxhtmlFalseaspx
Working Paper 14-1: Countercyclical Capital Regime Revisited: Test of Robustness13843<p>This paper tests the robustness of key elements of the Smith and Weiher (2012) countercyclical capital regime.&#160;&#160; Such tests are now possible given that the recent house price cycle is nearing its end.&#160;&#160; The recent house price cycle allows for rigorous out-of-sample testing because it encompassed state-level house price cycles of significantly greater magnitude than those observable by Smith and Weiher during the design period of their stress test.&#160;&#160; The tests of robustness presented herein support the conclusion that the Smith and Weiher countercyclical capital regime should produce capital requirements sufficient to ensure an entity would remain solvent during severe house price cycles.&#160;&#160; This conclusion is strongly supported by a back-test of the countercyclical framework using Fannie Mae’s historical book of business.&#160; If the countercyclical capital requirement had been in place during the run-up to the recent house price bubble, Fannie Mae would have been sufficiently capitalized to withstand losses it sustained in the subsequent housing crisis.&#160; This result is particularly noteworthy given that key components of the Smith and Weiher stress test were designed based upon pre-2002 data.&#160; Individual examinations of the trend line, trough, and time path components of the Smith and Weiher countercyclical capital regime all indicate that the underlying methodology is stable and robust.&#160;&#160; We also find that the countercyclical-related patterns in capital requirements will not vary when the stress test is applied to different credit models, but the level of capital required may vary appreciably.&#160; This suggests that over-reliance on any one credit model may not be prudent.​</p><p>​A revised version of this paper has been accepted for publication by the Journal of Economics and Business and can be accessed at <a href="http&#58;//www.sciencedirect.com/science/article/pii/S014861951500065X" target="_blank">http&#58;//www.sciencedirect.com/science/article/pii/S014861951500065X</a>​.<br></p>3/24/2016 2:55:07 PM2523http://www.fhfa.gov/PolicyProgramsResearch/Research/Pages/Forms/AllItems.aspxhtmlFalseaspx

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