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«Larry Cordell Federal Reserve Bank of Philadelphia Liang Geng Federal Reserve Bank of Philadelphia Laurie Goodman Amherst Securities Group, LP Lidan ...»

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Larry Cordell

Federal Reserve Bank of Philadelphia

Liang Geng

Federal Reserve Bank of Philadelphia

Laurie Goodman

Amherst Securities Group, LP

Lidan Yang

Amherst Securities Group, LP

April 24, 2013

The Cost of Delay

Larry Cordell

Federal Reserve Bank of Philadelphia

Liang Geng

Federal Reserve Bank of Philadelphia

Laurie Goodman

Amherst Securities Group, LP

Lidan Yang

Amherst Securities Group, LP April 24, 2013 * The opinions expressed in this paper are those of the authors and not necessarily those of the Federal Reserve Bank of Philadelphia or Amherst Securities Group, LP. We wish to thank Vidya Shenoy for valuable research assistance and Rob Dittmar for valuable advice on the econometrics and members of the Research Department at the Federal Reserve Bank of Philadelphia for helpful comments on earlier drafts. This paper is available free of charge at www.philadelphiafed.org/research-and- data/publications/working-papers/.

Abstract In this study, we make use of a massive database of mortgage defaults to estimate REO liquidation timelines and time-related costs resulting from the recent post-crisis interventions in the mortgage market and the freezing of foreclosures due to “robo-signing” revelations. The cost of delay, estimated by comparing today’s time-related costs to those before the start of the financial crisis, is eight percentage points, with enormous variation among states. While costs are estimated to be four percentage points higher in statutory foreclosure states, they are estimated to be 13 percentage points higher in judicial foreclosure states and 19 percentage points higher in the highest-cost state, New York. We discuss the policy implications of these extraordinary increases in time-related costs, including recent actions by the GSEs to raise their guarantee fees 15-30 basis points in five high-cost judicial states. Combined with evidence that foreclosure delays do not improve outcomes for borrowers and that increased delays can have large negative externalities in neighborhoods, the weight of the evidence is that current foreclosure practices merit the urgent attention of policymakers.

Page 1 of 27

1. Introduction The myriad of state foreclosure laws and different remedies to the recent foreclosure crisis by U.S., state, and local governments gives us a unique opportunity to measure and assess the costs of different policies to combat the foreclosure crisis. What has proved most problematic with this task has been the availability of data and complications with measuring foreclosure-related costs. In this study, we make use of a massive database of some 3 million real estate owned (REO) liquidations and 1.3 million defaulted loans to estimate foreclosure timelines and the cost of delay. Our sample spans nearly 16 years, starting in 1998 and extending through September 2012. Using a loan-level database, we are able to compare liquidation performance under different foreclosure laws and policies across states, controlling for geography down to the zip code; present analysis across all major types of mortgages and investors;

and control for a large array of borrower, property, and loan characteristics to get estimates of direct timerelated costs. The combination of data used in our study represents the most comprehensive database ever developed to empirically examine the cost of delay.

This paper is organized as follows. In Section 2 we review the literature. In Section 3 we describe our data and three samples we use to estimate REO liquidation timelines and the cost of delay. In Section 4 we describe our method for computing REO timelines for our large sample of uncensored observations from 1998 to September 2012. With this long sweep of history, we show how significantly timelines have been affected by the extraordinary government interventions in the foreclosure process, the freezing of foreclosures after the improper practices at servicers had been uncovered (the “robo-signing” scandal) and, preliminarily, the aftermath of the attorneys general (AG) settlement and resulting actions at the major servicers. In Section 5 we include in our sample the large number of loans defaulted in September 2012 but not yet liquidated and estimate a survival model to get an unbiased estimate of these timelines.

What we show is that timelines in judicial foreclosure states have increased by 18 months pre-crisis to today, from an average of 26 months to 44 months. In statutory foreclosure states, timelines have increased by 6 months, from 16 months to 22 months. In Section 6 we describe our model used to estimate time-related costs and measure how much costs have risen. Comparisons of today’s estimated costs to those pre-crisis represent the increased costs of delay. Pre-crisis, average time-related costs were estimated at 11% across the U.S.; today those costs are estimated at 19%, an eight-percentage-point increase. While costs have only gone up four percentage points in statutory states (from 8% to 12%), they have gone up 13 percentage points (from 17% to 30%) in judicial foreclosure states. In the highest-cost state, New York, costs have gone up by 19 percentage points. In Section 7, we discuss the policy implications of these extraordinary increases in the cost of delay, including recent actions by the GSEs to raise their guarantee fees in five judicial states with the largest increases in time-related costs.

2. Previous Literature

While the literature on mortgage default is extensive, the literature on foreclosure timelines is quite limited. This is unfortunate because the myriad of state foreclosure laws and recent experiments with different foreclosure alternative programs provide opportunities to empirically examine a broad array of different laws and programs. We believe a major impediment has been the lack of information on losses outside the private-label MBS market and the complexities of gathering, cleaning, and compiling large amounts of data, which we describe below. In some of the very first studies of variation of timelines by states, Clauretie (1989) and Clauretie and Herzog (1990) looked at losses to primary mortgage insurance Page 2 of 27 (PMI) companies in the 1980s. They found that states with judicial foreclosure laws, laws that require judicial proceedings to execute foreclosure, lengthen the foreclosure process by some five months relative to statutory foreclosure states that do not require judicial intervention. Since they were using PMI data, they were limited largely to high loan to value (LTV) loans insured by Freddie Mac and Fannie Mae, the two government-sponsored enterprises (GSEs). Wood (1997) documented that states with judicial foreclosure proceedings took an average five months longer than the average foreclosure process in nonjudicial states, and Wilson (1995) found that the judicial foreclosure process greatly increased costs to investors, implying the 5-month delay in judicial states raises time-dependent costs by 5% of the loan balance. Pennington-Cross (2003) found that houses in judicial foreclosure states sold for 4% less than those in statutory foreclosure states, driven in part by greater home price depreciation during the longer foreclosure process for judicial states. Pence (2006) investigated the costs of different state foreclosure laws on the availability of mortgage credit. She found that loan sizes are 3%-7% smaller in “defaulterfriendly” states, mainly judicial states, imposing material costs on borrowers at time of origination. These last two studies focused mainly on their effects on mortgage originations, not on the liquidation process.

More recently, the effects of the housing financial crisis have focused attention on timelines and costs of foreclosure. Hayre and Sharif (2008) used data on private-label securitizations to estimate differences in timelines and severities. They found that states that have a statutory, or “power-of-sale,” foreclosure process take, on average, 11 months, while states requiring judicial foreclosure proceedings take, on average, 14 months. Their data are limited to the private-label mortgage-backed securities (MBS) market.

Using data gathered at Freddie Mac, Cutts and Merrill (2008) find that the average foreclosure timeline nationwide, from last interest paid date to foreclosure sale, is 355 days, with substantial variation across states. They are most interested in finding an optimal foreclosure timeline policy to institute nationwide.

They conclude that an optimal foreclosure timeline is 270 days, composed of 120 days in foreclosure and 150 days for pre-foreclosure referral loss mitigation activities.

In all of the above-mentioned studies, researchers were limited to a particular sector of the mortgage market at a particular point in time. Our study will draw from a very large representative sample from the largest mortgage servicers over a very long time period. Most important, we can examine the effects of delays caused by moratoria instituted since the onset of the financial crisis in 2007 and delays caused by the “robo-signing” revelations.

Another line of research related to foreclosure timelines has examined the factors that lead borrowers to cure mortgage defaults rather than lose their properties to foreclosure, focusing as we do on measuring variations in state foreclosure laws. 1 Since one type of cure is a loan modification, some recent papers in this literature also address important policy questions about the effects of differences in foreclosure timelines on borrowers’ ability to have their loans modified. 2 This line of research can be interpreted broadly as attempting to assess the potential benefits associated with delaying foreclosures due to varying state foreclosure laws and various post-crisis foreclosure prevention programs. This literature generally agrees that borrowers are more likely to default the longer they are delinquent, the less equity they have in their properties, or if their loans are less seasoned. However, the evidence is mixed on whether and how mortgage outcomes differ with different state foreclosure laws or moratoria. In all but the Gerardi, 1 See Phillips and Rosenblatt (1997) and Phillips and VanderHoff (2004).

2 See Pennington-Cross (2010); Collins, Lam, and Herbert (2011); Mian, Sufi, and Trebbi (2011); and Gerardi, Lambie-Hanson, and Willen (2011).

Page 3 of 27 Lambie-Hanson, and Willen (2011) study (henceforth GLW (2011)), however, researchers were limited to investigating behavior in one sector of the mortgage market, often at a particular point in time. GLW (2011) draw from the same large sample we do and conclude that the longer timelines associated with judicial intervention in the foreclosure process or with one moratorium law implemented in Massachusetts did not lead to either more cures or more modifications. However, they did lead to more persistently delinquent borrowers, as we will also show.

In contrast to all of these studies, we use our large national panel of mortgage loan data to estimate the direct costs associated with delays in the foreclosure process across the entire U.S. In this area, empirical work in the academic and trade literature is especially limited. Calomiris and Higgins (2010) examine the macroeconomic effects of the cost of delay, citing four potential costs. But since they do not have the data to estimate these costs directly, they instead cite a number of studies that estimate various parts of these costs. They conclude that the sum total of these costs is substantial, but they do not attempt to estimate what they are. Our study is the first to directly estimate these time-related costs of foreclosures across the entire U.S. mortgage market pre- and post-crisis. In so doing, we are able to assess costs across all manner of state foreclosure practices and a wide range of interventions in the mortgage market.

If one accepts the proposition in GLW (2011) that the benefits of delay are negligible, then our study in combination with theirs constitutes a full cost-benefit analysis of differing state foreclosure laws and various crisis-related interventions in the foreclosure process. These interventions include the national moratorium first implemented by Freddie Mac and Fannie Mae in November 2008; the Home Affordable Refinance Program (HAMP) in March 2009; delays caused by the “robo-signing” scandal; and, finally, the effects of the recent state attorneys general (AG) settlement that emanated from the flaws uncovered.

Prospectively, we examine recent evidence to suggest what the cost of delay is likely to be with full implementation of new policies either in place or proposed.

3. Data and Sample Design

We use three samples of data from two sources in our analysis. For computing timelines for our first two samples, we use data from Lender Processor Services, Inc. (LPS), a loan-level database that covers approximately 60% of mortgages in the U.S. from the largest seller/servicers over a very long time period from 1992 to September 2012. This database contains over 140 million unique mortgage loans with around 4.9 billion records of monthly performance history through 2012. Since LPS includes the largest servicers, the database includes loans from all parts of the mortgage market, including those from Freddie Mac and Fannie Mae, the two government-sponsored enterprises (GSEs); government loans in, and out of, securities of the Government National Mortgage Association (GNMA); private label securities (including subprime, alt A, and prime jumbo loans); and portfolio loans.

Our first sample covers the period 1998-September 2012, where we examine the long history of timelines in the U.S., but only for the loans that have gone through REO liquidation. 3 In part, this is done to illustrate just how extraordinary recent history is.

3 We did not go back even further only because sample sizes are much smaller before 1998. But results are still qualitatively similar for months with enough observations.

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