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Abstract

Due to the rise in foreclosure filings, policymakers are increasingly concerned with helping families in financial distress keep their homes. This paper tests the extent to which distressed mortgage borrowers benefit from three types of state foreclo-sure polices: (1) judicial forecloforeclo-sure proceedings, (2) statutory rights of redemp-tion, and (3) statewide foreclosure-prevention initiatives. Based on an analysis of borrowers in default who reside in 22 cross-state metropolitan statistical area pairs, state policies generally have weak effects. Both judicial foreclosure proceed-ings and foreclosure prevention initiatives are associated with modest increases in loan modification rates. Using a matching procedure, a lender’s letter promoting mortgage default counseling was associated with increases in loan modifications, decreases in loan cures, and decreases in foreclosure starts. The effects of the let-ter were also stronger in states with judicial proceedings. © 2011 by the Association for Public Policy Analysis and Management.

BACKGROUND

According to the National Delinquency Survey released by the Mortgage Bankers Association (MBA), 4.57 percent of all mortgages across the nation were in some stage of the foreclosure process at the end of the second quarter of 2010, an increase of nearly 125 percent since the end of 2007. A total of 13.97 percent of all mortgages were at least one payment past due at the end of the second quarter of 2010. The percentage of mortgages at least one payment past due reached its high-est point ever at 15.02 percent at the end of 2009. Although the figures concerning delinquencies and foreclosures have declined slightly from their peak, the current figures are still far higher than historical averages. The spike in foreclosures has garnered considerable attention and has triggered the adoption of an array of pol-icy responses designed to mitigate the harms of foreclosure to borrowers, neighbor-hoods, and financial markets.

One of the most significant challenges for borrower-focused anti-foreclosure strategies is simply connecting borrowers to their lenders so they can work together and begin identifying potential solutions (Collins, 2007; Cutts & Merrill, 2008). Because the volume of mortgage delinquencies has increased so dramatically, state and local governments, the federal government, and the financial industry have sought to promote policies that give borrowers more time to explore alternatives to foreclosure. Some policy advocates contend that borrowers in states with longer foreclosure timelines and enhanced borrower protections will be less likely to lose

Policies & Lender

Interventions: Impacts on

Borrower Behavior in Default

Ken Lam

Christopher E. Herbert

Journal of Policy Analysis and Management, Vol. 30, No. 2, 216–232 (2011) © 2011 by the Association for Public Policy Analysis and Management

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their homes to foreclosure. Alternatively, excessive foreclosure protections may give delinquent borrowers an incentive to default and occupy their homes without mak-ing payments durmak-ing a lengthy foreclosure period. Meanwhile, substantial public and private resources have been aimed at efforts to offer telephone-based mortgage default counseling from third-party, nonprofit counseling agencies. One goal of these efforts is to connect borrowers with their lenders. Default counseling also provides an opportunity for borrowers to work through financial and budgeting problems, which may in turn improve their mortgage-repayment patterns. Nonetheless, few studies have evaluated the efficacy of default counseling, mortgage borrower protec-tion policies, or the interacprotec-tion between state policies and lenders’ outreach efforts. This paper tests the extent to which mortgage borrowers benefit from three types of state polices: (1) judicial foreclosure proceedings, (2) statutory rights of redemp-tion, and (3) statewide foreclosure-prevention initiatives. In addiredemp-tion, this paper analyzes the impact of lenders’ voluntary efforts to promote third-party default counseling and whether these efforts are more effective in states that have adopted each of the three types of policies tested. This study uses data from one national mortgage-lending institution to match the loan performance of 8,044 loans that were delinquent on January 1, 2007, to their status at the end of March 2008. This total includes 6,647 borrowers whose lender sent them a letter promoting default counseling through the national 888-HOPE hotline and a comparison group of 1,397 borrowers whose lender sent a similar letter offering assistance directly from the lender. The letters were not randomly assigned, and divisions of the lending institution that maintained a higher-risk portfolio of loans sent most of the letters that promoted third-party counseling through the 888-HOPE hotline. The letters that were sent to the comparison group, which again offered assistance directly from the lender, were mailed at approximately the same time by a division within the firm that managed a lower-risk pool of loans. All mortgages were at least 60 days delinquent on January 1, 2007, and the same set of outcomes was collected on March 31, 2008, across all of the loans. The data set encompasses loans from 22 metropolitan statistical areas (MSAs) that contain at least one state border pair in which state laws differ, providing relatively homogenous comparison groups in a quasi-experimental analysis.

State Laws and Anti-Foreclosure Initiatives

When consumers take out a mortgage, they enter into a contract to make payments under specific terms. If a borrower fails to make timely payments, the contract is violated and the loan is in default. The borrower remains in default until the loan is brought current or an arrangement is made with the lender concerning future payments and the terms for resolving the delinquency. Depending on the state’s and the borrower’s circumstances, when a loan is in default lenders may initiate the foreclosure process with the goal of selling the home to pay off the outstanding mortgage debt. The foreclosure process varies by state, but borrowers generally have at least 60 days from their first missed payment to take corrective action and avoid the start of foreclosure proceedings. The foreclosure process concludes when the borrower pays off the loan or signs the home over to the lender or when the property is sold at a foreclosure auction—in which case the lender itself typically purchases the home. Foreclosed homes usually sell for far below the value of the outstanding debt. In cases where the lender becomes the owner of a foreclosed property, the property can be expensive to maintain while awaiting a homebuyer. Given the high costs of foreclosure, lenders typically offer several of the following options to borrowers before initiating the foreclosure process:

• Forbearance: a period of suspended or reduced payments within the existing mortgage contract;

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• Repayment plan: adding past due amounts to future monthly payments within the existing mortgage contract;

• Loan modification: adding past due amounts to the principal balance, often in conjunction with extending the term of the loan or reducing the interest rate by formally revising the mortgage contract;

• Sales assistance: referring the borrower to a real estate agent and helping the borrower put the home on the market, with the understanding that the bor-rower will pay off the mortgage when the home sells;

• Preforeclosure sale (“short sale”): allowing the borrower to sell the property for less than is owed on the mortgage; and

• Deed in lieu of foreclosure: the property is returned to the investor, and the borrower walks away without a foreclosure mark on his or her credit history. Industry estimates suggest that of all the homes that enter the foreclosure process, at least one-half of borrowers avoid foreclosure by catching up on their mortgage payments or by taking advantage of a “workout” such as those described above (Apgar & Duda, 2004). Workouts are generally provided on a case-by-case basis. Lenders call or write borrowers and encourage them to speak with their loan servicer to explore potential solutions.1Despite the existence of alternatives to

fore-closure and lenders’ incentives to avoid forefore-closure, many borrowers fail to take advantage of the options their lenders present. Even borrowers experiencing job loss or problems at home often do not utilize default counseling or other services available to them. One reason for this lack of take-up is that a significant propor-tion of borrowers are unaware of the various oppropor-tions available to them (Collins, 2007; Cutts & Merrill, 2008).

The types of protections provided to borrowers facing foreclosure vary consider-ably across states. One important factor is whether foreclosure is carried out through a judicial or nonjudicial process. A judicial foreclosure process requires lenders to process foreclosure filings through the court system. Nonjudicial foreclo-sures are generally simpler, quicker, and less costly. The additional time associated with judicial foreclosure proceedings may give borrowers more opportunities to find solutions before a foreclosure sale. The added time of a judicial foreclosure also makes foreclosure more costly to lenders, which gives lenders a greater incen-tive to promote alternaincen-tives to foreclosure. Some states offer both judicial and non-judicial procedures, although in such states nonnon-judicial proceedings are usually used more frequently. In other states the judicial process is the only option, and all foreclosures in these states must proceed through the courts. A small number of states do not have a judicial foreclosure process and instead rely solely on nonjudi-cial proceedings.

Nearly one-half of states allow former homeowners to regain their foreclosed properties through a statutory right of redemption. A right of redemption allows individuals who lose their homes to foreclosure to redeem their properties for the foreclosure sale price plus foreclosure expenses up to one year after a foreclosure. In practice, borrowers rarely exercise statutory rights of redemption, especially in markets with weak home values. However, the existence of a right of redemption may chill demand for foreclosed properties, and lenders of properties in these states may face longer holding periods or may be forced to accept lower sales prices. Over-all, a right of redemption adds to the cost of foreclosure for lenders and may pro-vide a greater incentive for lenders to seek alternatives to foreclosure and to extend the default timeline to allow homeowners more time to explore potential solutions.

1Contacting borrowers in default is a significant challenge. One servicer sent defaulted borrowers a cell

phone with a note that the borrower could use the telephone at no charge (up to 500 minutes per month) as long as the first call was to the servicer to activate the telephone and discuss workout options. This initiative is indicative of the extent to which lenders struggle to initiate contact with borrowers in default.

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Since the 1980s, several states have launched anti-foreclosure initiatives in an effort to stem foreclosures. These initiatives include marketing or directly offering default counseling, providing incentives to lenders that restructure loans or lower borrowers’ payments, and creating special public loans or grants to help borrowers catch up on their payments. This study reviews judicial proceedings, statutory rights of redemption, and state-level anti-foreclosure initiatives from a variety of public sources, including RealtyTrac, a paper by Pence (2006), a report by the Pew Center on the States (2008), and the authors’ review of legislative summaries. In 2007, 20 states required all foreclosures to proceed through the courts, 22 states had statutory rights of redemption, and 19 states (nine of which offer public loans/grants) had laws or programs specifically designed to address the issues that borrowers in foreclosure face. In only two states, Illinois and New Jersey, had all three policies in place in 2007.

LITERATURE REVIEW

Multiple studies have concluded that both judicial proceedings and statutory rights of redemption do indeed lengthen the foreclosure process and increase lender costs. As expected, the foreclosure process is the longest in states with the strictest fore-closure processes (Hayre & Saraf, 2008). Forefore-closure timelines are about five months longer in states with judicial proceedings than in states with nonjudicial processes (Wood, 1997). Evidence from the mortgage insurance industry in the late 1980s provides some evidence that statutory rights of redemption also lengthen the foreclosure process (Clauretie, 1989; Clauretie & Herzog, 1990). Although little evi-dence has emerged on the impact of state-level foreclosure prevention initiatives, to the extent these initiatives enhance borrower protections, both the length and the cost of the foreclosure process presumably increase. Because judicial proceedings, rights of redemption, and state-level initiatives increase the costs of foreclosure to lenders, these policies may encourage lenders to work with borrowers to avoid fore-closure. By lengthening the foreclosure process, these policies are also designed to give borrowers and lenders more time to find alternatives to foreclosure.

On the other hand, foreclosure timelines that are too long may undermine bor-rowers’ incentives to reinstate their loans. Borrowers in states with lengthy foreclo-sure timelines may have an incentive to occupy their homes without making any payments during the foreclosure process. Of course, this line of reasoning assumes that borrowers are well informed about state foreclosure laws and that their incen-tives to live rent-free outweigh the nonpecuniary costs of foreclosure. Cutts and Merrill (2008) note that borrowers in states with foreclosure timelines that are too short would benefit from policies that lengthen the foreclosure process and thereby give borrowers and lenders more time to find alternatives to foreclosure. Ultimately, the authors conclude there is a “sweet spot” in the timeline of a foreclosure process (p. 39). The sweet spot is the point at which the foreclosure timeline is both short enough that borrowers do not have too strong of an incentive to occupy a home without making payments and long enough that borrowers have a realistic oppor-tunity to resolve financial problems, catch up on payments, or receive a workout.

Empirical research on the effects of state policies on foreclosure is quite scarce, and some of the past findings are inconsistent. One recent study finds nonjudicial foreclosure proceedings are associated with both an increased likelihood the home exits foreclosure through repossession by the lender and an increased likelihood the home exits foreclosure by curing (Pennington-Cross, 2010). Another study suggests that both foreclosure and loan cures are more likely in states with nonjudicial fore-closure proceedings (Phillips & VanderHoff, 2004). Capozza and Thomson (2006), however, find that borrowers in default are more likely to catch up on their pay-ments if they live in a state with a slow foreclosure process. Given that judicial processes are slower on average, these findings are inconsistent. Overall, a general

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theme in the literature seems to be that judicial procedures result in negative out-comes for lenders and borrowers, although the relative incidence of repossession (or real estate owned—REO—in industry jargon), repayment, cures, and continued delinquency are important to consider. The authors of these papers often suggest that states repeal judicial proceedings to speed the foreclosure process, yet they also recognize the problems raised by the endogeneity between state laws and housing market conditions.

A substantial percentage of delinquent borrowers fail to contact their lender or ser-vicer, which undercuts their ability to avoid foreclosure. Although servicers reach out to delinquent borrowers in a variety of ways, a significant proportion of borrow-ers never speak with their servicer when they find themselves unable to make their mortgage payments (Collins, 2007). Perhaps most alarmingly, Cutts and Merrill (2008) find that 52 percent of foreclosure sales lack reciprocal lender contact, which undermines borrowers’ ability to partner with their servicer to complete a workout. Because the likelihood of retaining one’s home decreases the longer delinquent bor-rowers delay contacting their lenders, connecting borbor-rowers and lenders as early as possible during the default period is critical to helping borrowers keep their homes (Cutts & Merrill, 2008). In the present study, a single lender mailed a letter to 8,044 borrowers who were behind on their payments. While 1,397 letters urged borrowers to contact their lender for assistance, 6,647 letters referred borrowers to a third-party default counseling hotline. The latter offer highlights the existence of legiti-mate alternatives to foreclosure, and it may signal that contacting sources of help will not put mortgages in further jeopardy. Unfortunately, we do not observe the actual take-up of counseling following the letter, but we hypothesize that the offer of counseling encouraged borrowers to take actions to avoid foreclosure.

Even though this study focuses on one lender’s efforts to promote nonprofit default counseling, an emerging literature evaluates the impact of default counseling on loan outcomes. The most relevant prior study was conducted by Ding, Quercia, and Ratcliffe (2008), who examine the association between telephone-based default counseling and the likelihood of curing a delinquency among loans made to low-income borrowers. A third-party nonprofit counseling agency attempted to contact borrowers who were at least 60 days delinquent to offer assistance in assessing their situations and to provide advice about how to work with their lender. The authors identified three groups of borrowers based on the success of the attempted telephone contacts: borrowers who were not reached (none), borrowers who were introduced to counseling but chose not to participate (contact), and borrowers who participated in counseling (counsel). The authors employ a two-stage model to account for selec-tion into counseling and find that the receipt of counseling is associated with higher rates of cured loans. A study by Collins (2007) and a preliminary evaluation of the National Foreclosure Mitigation Counseling Program (Mayer et al., 2009) also find positive impacts of default counseling on loan outcomes.

The present study differs from the previous literature in several important respects. First, this paper utilizes cross-border MSA pairs to control for local market factors, using borders as a discontinuity in the housing and labor markets. Second, this study examines how lenders’ efforts to promote third-party default counseling are related to the likelihood of positive loan outcomes. Third, this study examines the interaction between a lender’s outreach efforts and state laws. We explore whether policies that lengthen the foreclosure process and promote alternatives to foreclosure improve outcomes for borrowers, based on the assumption that longer timelines increase opportunities to explore alternatives to foreclosure. We focus on three key outcomes observable in the relatively short snapshot of available data: the probability that foreclosures are started (a legal filing is initiated), the probability the delinquency is cured (no longer behind on payments), and the probability a loan is modified (the term, rate, or balance in the mortgage contract is changed).

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It is important to reiterate that the counseling treatment is being sent a letter that highlights default counseling through the 888-HOPE hotline, not the actual receipt of counseling. Therefore, the analysis of the counseling offer is an intent-to-treat analysis. Lenders cannot force borrowers to participate in counseling. Promot-ing counselPromot-ing might have a direct effect in that borrowers receive help and improve their payment behaviors. Some borrowers who receive such a letter might not call the counseling hotline immediately but may seek help at a later time. The letter might motivate some borrowers to seek help from other sources. The offer of counseling through the 888-HOPE hotline could also serve as a signal that the bor-rower needs to take corrective action and manage the delinquency more effectively. Receiving the letter could also signal that the lender wants the borrower to succeed. The counseling letter could increase borrower–lender contact rates, which again is crucial in resolving a delinquency. Overall, we can only speculate about how the let-ter may influence borrowers’ behavior, and we cannot further refine the mecha-nisms through which the letter may affect borrowers. Instead, we simply suggest that any findings are associated with the two forms of lender outreach demon-strated in this particular circumstance.

DATA AND METHODS

In January 2007, a large national lender sent a letter to 8,044 owner-occupant borrowers with first-lien mortgages for purchase or refinance. All of the borrowers were at least two payments behind on their mortgages. Borrowers in Chapter 7 bankruptcy and those who were more than 120 days delinquent on January 1, 2007, were excluded from the mailing. We identify state laws in Table 1 based on a review of prior literature and the Web sites of state courts and real estate firms. We iden-tified 13 MSA cross-border pairs where at least one state has only judicial proceed-ings and one state has nonjudicial proceedproceed-ings. We found 14 MSA pairs where at least one state had a statutory right of redemption and one state did not. Finally, we found 11 cross-border MSA pairs where at least one state had adopted a foreclosure prevention initiative and one state had not. Previous studies have used similar spa-tial sampling techniques to estimate the effects of a variety of state policies (e.g., Holmes, 1998; Pence, 2006; Pennington-Cross & Ho, 2008). We use MSA indicator variables to estimate the intra-MSA effects of each respective policy.

Appendix I2displays the two letters, both of which had a similar length and tone.

The primary difference between the letters was the referral to a nonprofit counseling agency in the treatment letter. The lender did not knowingly distribute letters for a randomized experiment, nor is it precisely clear which types of borrowers received each letter. However, discussions with the lender revealed that the lender sent letters promoting third-party counseling to borrowers who were at a higher risk of foreclo-sure and who represented higher potential lender-incurred losses. For example, bor-rowers with older, more seasoned loans represented a lower risk; therefore, the lender was less likely to send the counseling letter to these borrowers. Likewise, borrowers with adjustable rate loans represented a higher risk, and the lender was therefore more likely to send the counseling letter to these borrowers. The loans included in the data set were organized by pools, some of which were sold to investors and some of which were held in the lender’s portfolio. Loans held in the lender’s portfolio repre-sented potential direct losses, and the lender was therefore more likely to send the counseling letter to borrowers with these loans. Alternatively, the lender was less likely to send the counseling letter to borrowers with government-insured loans because these loans represented a lower potential loss to the lender.

2All appendices are available at the end of this article as it appears in JPAM online. See the complete

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Table 1.State law summary.

Right of State Foreclosure

State Judicial Only Redemption Program

Alabama NO YES NO

Alaska NO YES NO

Arizona NO YES NO

Arkansas NO YES NO

California NO YES YES

Colorado NO NO YES

Connecticut YES NO YES

Delaware YES NO YES

DC NO NO NO

Florida YES NO NO

Georgia NO NO NO

Hawaii** NO NO YES

Idaho NO YES NO

Illinois YES YES YES

Indiana YES NO YES

Iowa* YES YES NO

Kansas YES YES NO

Kentucky YES YES NO

Louisiana YES NO NO

Maine YES YES NO

Maryland* YES NO YES

Massachusetts* YES NO YES

Michigan NO YES YES

Minnesota NO YES YES

Mississippi NO NO NO

Missouri NO YES YES

Montana NO NO NO

Nebraska* YES NO NO

Nevada NO NO YES

New Hampshire NO NO YES

New Jersey YES YES YES

New Mexico YES YES NO

New York* YES NO YES

North Carolina NO NO YES

North Dakota YES YES NO

Ohio YES NO YES

Oklahoma NO NO NO

Oregon NO YES NO

Pennsylvania YES NO YES

Rhode Island NO NO YES

South Carolina YES NO NO

South Dakota NO YES NO

Tennessee NO YES NO

Texas NO NO NO

Utah NO NO NO

Vermont YES YES NO

Virginia NO NO NO

Washington NO NO NO

West Virginia NO NO NO

Wisconsin* YES YES NO

Wyoming NO YES NO

Total 20 22 19

* state has both judicial and non-judicial processes; dominant process in practice is listed. ** Hawaii foreclosure program only for people age 65 or older.

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These general rules appear to predict which letter was sent to a particular bor-rower. Given the descriptive statistics in Table 2, there are clear differences between the two groups of borrowers—those who were sent the counseling letter and those who were sent the letter offering direct assistance from the lender. Again, borrow-ers with riskier loans were more likely to receive the counseling letter. We use a rel-atively new form of matching called Coarsened Exact Matching (CEM) to analyze the causal impact of the counseling letter.

Table 2.Descriptive statistics: Loan outcomes, state laws, and loan characteristics by letter type.

Counseling Lender

All Letter letter

Time 2 (March 2008) dependent variables

Foreclosure start 0.19 0.20 0.14

(0.39) (0.40) (0.35)

No longer delinquent (cure) 0.23 0.23 0.27

(0.42) (0.42) (0.44)

Loan modified at time 2 0.07 0.06 0.13

(0.25) (0.23) (0.34)

Policy variables

Judicial only state 0.63 0.63 0.65

(0.48) (0.48) (0.48)

State w/redemption 0.48 0.49 0.46

(0.50) (0.50) (0.50)

State w/foreclosure initiative 0.76 0.77 0.76

(0.42) (0.42) (0.43)

Time 1 baseline variables (Jan. 2007)

Adjustable rate mortgage (ARM) 0.33 0.35 0.23

(0.47) (0.48) (0.42)

Log loan balance 11.80 11.85 11.55

(0.66) (0.65) (0.69)

Year of origination 2003 2003 2001

(3.38) (3.01) (4.23)

FICO credit score 611.14 610.75 613.01

(57.39) (57.14) (58.55)

FHA/VA insured loan 0.28 0.25 0.40

(0.45) (0.44) (0.49)

Early indicator score (EIS) 335.34 332.41 349.24

(56.99) (57.39) (52.93)

Days delinquent (Days) 75.58 75.69 75.06

(12.61) (12.69) (12.20)

Subprime loan 0.88 0.88 0.87

(0.33) (0.32) (0.34)

Refinance loan 0.15 0.14 0.19

(0.36) (0.35) (0.39)

Loan to value ratio (LTV) 0.83 0.83 0.85

(0.15) (0.15) (0.16)

Low level of income documentation 0.12 0.13 0.07

(Low Doc) (0.33) (0.34) (0.26)

Observations 8,044 6,647 1,397

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Specifications

CEM belongs to a class of models using Monotonic Imbalance Bounding to match observations for causal analysis using a nonparametric estimate. The advantage of this method is that it relaxes the assumptions required in traditional propensity score balancing tests between the treated and comparison groups. CEM restricts data to a common support region and is also computationally efficient. Rather than determining a particular matching method (caliper, radius, and others), typically through trial and error on the part of the analyst, CEM “coarsens” observations into values of the treatment variable as assigned by covariates. After coarsening obser-vations based on observable characteristics, exact matching is applied by sorting the observations into strata. Then any strata containing only comparison or only treatment observations are discarded, and strata with both treated and comparison units are retained. This creates a counterfactual for estimation and automatically restricts the matched data to areas of common empirical support. Typical propen-sity score balancing tests rely on ex-post mean comparisons. Yet, as Iacus, King, and Porro show, means of individual variables may be balanced using these proce-dures without improving global multivariate imbalance (Blackwell et al., 2009; Iacus, King, & Porro, 2008, 2009a, 2009b). CEM eliminates extreme values that may result in satisfactory balancing of means while reducing overall balance. CEM weights are calculated as the proportion of units within each stratum that are treated, providing a weight of zero to observations in unmatched strata. Based on comparisons of a variety of statistical strategies used to establish causality, includ-ing optimized propensity score models, CEM models have a lower root mean squared error and are better balanced (Blackwell et al., 2009; Iacus, King, & Porro, 2008, 2009a, 2009b). Equation (1) displays the variables used to construct the CEM in this analysis, which are different from the dependent variables in the subsequent models and rely heavily on loan pool information that the lender used when assign-ing each loan to the counselassign-ing or non-counselassign-ing letter groups.

Pr(counseling letter) ⫽ a⫹b1(ARM)⫹b2(Year originated)

⫹b3(Pool)⫹b4(Government insured) (1) ⫹b5(Portfolio owned) ⫹e

Using the CEM routine, we identify 42 matched strata over 4,605 observations. Additional covariates were tested in the CEM model, as well as different levels of coarsening. The significance and magnitude of the results were stable across these variations and were similar to the more parsimonious final model that contains the covariates listed in Equation (1). For each observation, the proportion of treated observations to controls in the strata is used to create a CEM weight. This weight is then used in further causal estimates, which are discussed below. The matching models described in the paper were also run using a traditional propensity score matching weighted model displayed in Appendix Tables.3The traditional propensity

score weighted approach resulted in a larger number of observations than the CEM model, even imposing common support restrictions. The CEM method remains the preferred approach, but the more traditional model provides a test of the sensitiv-ity of the findings to the matching method used.

These data were provided by one lender and are thereby limited in scope. Often in the mortgage default literature, outcomes are observed over a longer time frame using a panel design where competing risks can be observed and modeled. In these

3All appendices are available at the end of this article as it appears in JPAM online. See the complete

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data, we do not observe the interim status of each loan. For example, a loan may have been delinquent in January 2007, cured, become delinquent again, and then entered the foreclosure process at the time of observation in March 2008. The data are therefore modeled using a two-period panel where all loans begin the panel in default but are not modified or in foreclosure. At the follow-up 15 months later, a loan can be modified or not, and each loan is also either still delinquent (but not in foreclosure), cured (not delinquent or in foreclosure), or delinquent and in foreclo-sure.

Three sets of models are used in this analysis. The first set of models estimates the effects of state laws and policies—judicial proceedings, statutory rights of redemption, and statewide foreclosure-intervention strategies—on the likelihood a loan is modified (a 0 to 1 binary variable that indicates whether the loan term, rate, or balance was formally modified). Aside from whether a loan was modified during the study period, a loan may have remained delinquent but not entered the foreclo-sure process, the loan may have been cured (paid off entirely or all past due pay-ments and fees repaid), or the lender may have initiated foreclosure proceedings while the loan remained delinquent. A multinomial logit model is used to analyze the relative incidence of these three outcomes. Loan modifications are independent of a loan’s delinquency or foreclosure status at follow-up and are therefore not part of this model. The multinomial dependent variable is coded 1, 2, or 3 for still delin-quent but not in foreclosure, cured, or foreclosure started, respectively. This analy-sis is conducted on the entire pool of loans and does not account for differences between the group of individuals who received the letter offering third-party coun-seling and the group who did not receive it. The second set of models assesses the effect of the lender letter offering counseling on the likelihood of the same out-comes using weights derived from the CEM estimator. The third set of models then tests the effects of the counseling letter in combination with each state policy. Each of these sets of models is described in greater detail below.

State Law Model

Each outcome, Y, is tested against state laws, L, using a series of dummy variables indicating whether or not a state, s, has a particular law, as well as a matrix of vari-ables, X, that control for loan-level, i, characteristics at the start of the study. Because unobservable market-level factors may also contribute to foreclosures, only MSAs with a cross-state border are included. MSA fixed effects, g, are used to control for these effects, isolating the effect of the state law indicators. The esti-mated model takes the following form:

Pr(Yi,s

Mar08)⫽a⫹b1XiJan07⫹b2LsLaw⫹b3gmsafixed effect⫹e (2)

whereYincludes the outcomes discussed and the matrix Xincludes the following baseline variables (as of January 2007): an indicator of whether the loan was an adjustable rate mortgage, log loan balance, year of origination, FICO credit score, an indicator of whether the loan is insured by the Federal Housing Administration or the Department of Veterans Affairs, an early indicator risk score (an industry scale of how likely the loan will result in a loss), the number of days delinquent, an indi-cator of whether the lender labels the loan as subprime, an indiindi-cator of a refinance (vs. a home purchase) loan, and an indicator for full income-documentation level. The matrix Lconsists of three indicator variables: whether the state had a judicial foreclosure process, a statutory right of redemption, or a foreclosure prevention pro-gram. MSAs included in the analysis may have all three laws in effect, generating concerns about multicollinearity. Thus, each state policy is run in isolation for the MSAs where at least one state has the law and one state does not. A total of 13 MSAs (3,991 observations) are used to estimate the effects of judicial procedures,

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14 MSAs (5,355 observations) for statutory rights of redemption, and 11 MSAs (6,439 observations) for foreclosure prevention initiatives. Appendix Table A24

dis-plays descriptive statistics concerning loan outcomes and the incidence of state laws by MSA.

Lender Letter Outcome Model

In Equation (3), the outcome, Y, is tested using a weighted regression-adjusted impact estimate (Orr, 1999). The estimated model takes the following form, where receiving a letter promoting third-party counseling is indicated by the dichotomous variable,D:

Pr(YiMar08)⫽ [a⫹b1DiLetter⫹b2YiJan07⫹e] *w (3)

Each borrower’s outcome is relative to his or her status in January 2007. These models are run using weights derived from CEM scores. The result is an estimate of the average treatment effect of the lender letter offering counseling compared to the lender letter offering an in-house loss mitigation program.

State Laws–Lender Letter Interaction Model

The third set of models combines the CEM weights with the policy models. This set of models includes an indicator the lender sent a counseling letter as well as an interaction between state laws and the lender letter:

Pr(Yi,sMar08)⫽[b1XiJan07⫹b2LsLaw⫹b3DiLetter⫹b4(LsLaw*DiLetter)⫹e] *w (4)

All models use robust standard errors to correct for heteroskedastic error terms (see Green, 2003). Logit models are used, with coefficients reported as exponential log-odds units, although marginal effects are discussed in the text (evaluated at the mean for each covariate). Loan modifications are estimated using a binomial logit, and loan status is estimated with a multinomial logit specification.

FINDINGS

Tables 3 and 4 display the results derived from the models discussed above. Table 3 shows the state law estimates using 22 cross-border MSAs. The first set of models, columns 1 to 3, shows the effects of the three state law indicators on loan modifi-cations. Columns 4 to 6 show the multinomial dependent variable of the loan being cured or having a foreclosure started, with loans still delinquent (but not in foreclo-sure) as the comparison. Sample sizes vary because only MSAs that have at least one state with the specified law and one state without the law are included. Covari-ates in these models generally perform as expected, as risk factors are typically associated with a higher likelihood of a foreclosure start, a lower likelihood of curing, and a lower likelihood of being modified. In terms of state laws, judicial procedures and state foreclosure prevention initiatives had modest effects on loan modifications. Judicial proceedings are associated with a 3 percent marginal increase in loan modifications compared to loans in the same MSA not subject to judicial proceedings. Anti-foreclosure initiatives are associated with a 2 percent marginal increase in loan modifications compared to other loans in the same MSA not subject to these laws (only at the 0.10 level of significance). However, as shown by the lack of any significant effects in the multinomial models in columns 4, 5, and 6,

4All appendices are available at the end of this article as it appears in JPAM online. See the complete

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T

able 3.

Loan ooutcomes by state foreclosure law: Logit estimates of modification; multinomial estimates of cure/foreclosure started.

(4) (5) (6) (1) (2) (3) No Longer No Longer No Longer Loan Loan Loan Delinquent Foreclosure Delinquent Foreclosure Delinquent Foreclosure Modified Modified Modified (cure) Start (cure) Start (cure)

Judicial only state

1.62* 1.18 1.24 (0.34) (0.13) (0.18) State w/redemption 0.86 1.02 1.05 (0.13) (0.08) (0.11) State w/foreclosure 1.34 ⫹ 0.93 initiative (0.23) (0.08) ARM 0.59** 0.68* 0.71** 1.26* 1.44** 1.13 1.41** 1.20** (0.09) (0.10) (0.09) (0.12) (0.16) (0.09) (0.13) (0.09)

Log loan balance

1.73** 1.72** 1.73** 0.85* 0.87 0.80** 0.91 0.75** (0.25) (0.22) (0.20) (0.07) (0.09) (0.05) (0.08) (0.05) Y ear origination 0.84** 0.86** 0.87** 1.00 1.12** 1.01 1.14** 1.01 (0.02) (0.02) (0.02) (0.01) (0.03) (0.01) (0.03) (0.01) FICO 0.72* 0.55** 0.63** 1.29** 1.67** 1.02 1.37** 1.14 ⫹ (0.11) (0.08) (0.08) (0.11) (0.19) (0.08) (0.13) (0.08) FHA/V A 1.34 ⫹ 1.42* 1.36* 1.13 0.83 1.05 0.80 ⫹ 0.97 (0.21) (0.23) (0.18) (0.12) (0.11) (0.10) (0.10) (0.08) EIS 0.81 0.93 1.05 1.05 0.66** 1.31** 0.68** 1.13 (0.11) (0.13) (0.13) (0.09) (0.06) (0.11) (0.06) (0.08) Days 1.16** 1.09* 1.13** 0.96 1.11** 0.99 1.18** 0.97 (0.05) (0.05) (0.04) (0.03) (0.04) (0.03) (0.03) (0.02) Subprime 1.68 1.02 1.02 1.18 1.14 0.96 1.05 1.01 (0.56) (0.30) (0.25) (0.19) (0.21) (0.12) (0.16) (0.12) Refinance 1.25 1.23 1.16 0.97 1.00 0.86 ⫹ 0.88 0.95 (0.21) (0.20) (0.17) (0.10) (0.13) (0.08) (0.10) (0.08) L T V 1.03** 1.04** 1.04** 0.99** 1.01 1.00 ⫹ 1.01** 0.99* (0.01) (0.01) (0.01) (0.00) (0.00) (0.00) (0.00) (0.00) Low doc 1.40 1.04 1.15 0.86 1.04 1.01 1.07 0.93 (0.38) (0.26) (0.24) (0.11) (0.15) (0.10) (0.12) (0.09) N 3,991 5,355 6,439 3,991 5,355 6,439 x 2 204.42** 298.99** 311.45** 235.17** 359.92** 402.13** Note:

Cross-border MSAs with at least one state with law in ef

fect and one not in ef

fect; beta estimates as exponentiated coef

ficient

s and robust standard errors

in parentheses. ⫹p ⬍ 0.10; * p ⬍ 0.05; ** p ⬍ 0.01.

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T

able 4.

CEM weighted logit estimates of lender letter ef

fects on modification and CEM weighted multinomial logit estimates cure/foreclo

started. (4) (5) (6) (1) (2) (3) No Longer No Longer No Longer Loan Loan Loan Delinquent Foreclosure Delinquent Foreclosure Delinquent Foreclosure Modified Modified Modified (cure) Start (cure) Start (cure) Start Sent letter 1.61* 3.15 ⫹ 0.93 0.78** 0.27** 0.37* 0.29* 0.55 0.97 (0.33) (2.04) (0.59) (0.07) (0.03) (0.17) (0.15) (0.23) (0.51) Letter ⫻ Judicial 0.50 3.67* 0.69 only state (0.45) (2.29) (0.47) Letter ⫻ State 1.20 1.17 0.27* w/foreclosure initiative (0.92) (0.55) (0.17)

Judicial only state

2.32 0.26* 2.30 (2.14) (0.16) (1.68) State w/foreclosure 1.28 0.84 2.76 initiative (0.95) (0.38) (1.61) ARM 0.62* 0.57 0.62 ⫹ 1.15 1.64** 1.23 1.70* 1.15 1.72** (0.15) (0.20) (0.18) (0.12) (0.18) (0.24) (0.40) (0.17) (0.28)

Log loan balance

1.99** 2.00* 1.83* 0.70** 1.31** 0.74 ⫹ 1.05 0.65** 1.01 (0.33) (0.59) (0.47) (0.05) (0.11) (0.12) (0.23) (0.09) (0.16) Y ear origination 0.73** 0.67** 0.72** 1.03 1.17** 1.04 1.24** 1.05 1.25** (0.03) (0.04) (0.04) (0.02) (0.03) (0.07) (0.09) (0.06) (0.08) FICO 0.55** 0.56 0.54* 1.09 2.08** 1.51* 2.33** 1.10 2.25** (0.11) (0.20) (0.16) (0.10) (0.22) (0.28) (0.54) (0.16) (0.44) FHA/V A 0.92 0.79 0.71 1.28* 1.62** 1.32 1.45 1.19 1.84* (0.21) (0.25) (0.24) (0.14) (0.20) (0.27) (0.40) (0.21) (0.49) EIS 0.52** 0.39** 0.52** 1.12 1.53** 1.29 1.60 1.21 1.48 (0.08) (0.13) (0.13) (0.09) (0.14) (0.26) (0.47) (0.20) (0.42) Days 1.15* 1.18 ⫹ 1.08 0.94 ⫹ 1.25** 0.94 1.18* 0.94 1.20** (0.07) (0.11) (0.09) (0.03) (0.04) (0.05) (0.08) (0.04) (0.06) Subprime 1.47 1.92 1.45 0.52** 1.68** 0.78 1.24 0.58* 1.16 (0.52) (1.38) (0.83) (0.08) (0.27) (0.24) (0.47) (0.14) (0.35) Refinance 1.92** 2.41* 2.55** 0.94 0.58** 0.80 0.57* 0.89 0.58** (0.40) (0.84) (0.78) (0.10) (0.08) (0.14) (0.14) (0.13) (0.12) L T V 1.02* 1.02 1.03* 1.00 1.04** 1.01 1.06** 1.01 1.04** (0.01) (0.02) (0.02) (0.00) (0.00) (0.01) (0.02) (0.01) (0.01) Low doc 3.14** 3.18* 3.48** 0.61** 0.90 0.43* 0.95 0.61* 0.60 (0.91) (1.64) (1.41) (0.09) (0.13) (0.15) (0.39) (0.13) (0.22) N 4,165 2,106 3,353 4,165 2,106 3,353 x 2 145.73** 102.00** 87.79** 850.78** 99.57** 179.50** Note:

Columns 1 and 4 are all observations with MSA fixed ef

fects; columns 2, 3, 5, and 6 are only cross-border MSAs with at least on

e state with law in ef

and one not in ef

fect; estimates as exponentiated coef

ficients and robust standard errors in parentheses.

p ⬍ 0.10; * p ⬍ 0.05; ** p ⬍ 0.01.

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the three types of state policies do not affect whether the loan is cured, remains delinquent (but not in foreclosure), or is in foreclosure.

Table 4 displays the causal estimates of the lender letter offering counseling as well as the interaction between each state policy and the lender letter. These mod-els include CEM weights and use a reduced sample size because the CEM approach matches only within 42 identified strata, discarding nearly 3,500 observations. The lender letter offering counseling is associated with a 2 percent marginal increase in the probability of a loan modification across the entire sample using MSA fixed effects (column 1). The letter is also associated with a 4 percent marginal decrease in loan cures and a 20 percent decrease in foreclosure starts using the multinomial model (column 4). These results are similar to those estimated using a traditional propensity score weighted model, as shown in Appendix Table A1.5The larger

num-ber of observations in the traditional propensity score model contributes to more robust statistical significance, although the consistency in the direction and magni-tude of the estimated effects across the two models is reassuring.

The models interacting judicial foreclosure policies or anti-foreclosure initia-tives with the counseling letter do not suggest statistically significant interaction effects on loan modifications (columns 2 and 3). The model showing the interac-tion of the lender letter offering counseling and judicial proceedings (column 5) shows borrowers receiving counseling letters in judicial states are more likely to cure relative to loans not receiving counseling letters located in states without judicial proceedings. All three covariates, including the letter, judicial foreclosure proceedings, and the interaction between these two variables, were statistically significant using the CEM model. However, the indicators for the counseling let-ter, judicial proceedings, and the interaction between these two variables were not significant using traditional propensity score matching, as shown in Appendix Table A1. Although the CEM method is in theory the more valid approach, the lim-ited sample size in this model suggests some caution may be called for when gen-eralizing these results.

Column 5 also shows that the effect of the letter is statistically significant in terms of a decrease in the probability of a loan starting foreclosure, but the interaction between state judicial proceedings and the letter on foreclosure starts is not statis-tically significant. The multinomial model interacting the lender letter and state anti-foreclosure policies (column 6) shows no significant effects on loan cures but a reduction in a loan starting foreclosure relative to a borrower in a state without such policies receiving the non-counseling letter. The propensity score model in Appendix Table A1 shows similar results with a reduction in foreclosure starts among borrowers receiving the counseling letter in states with anti-foreclosure ini-tiatives. The overall hypothesis that the letter offering counseling might have stronger effects in states with specific policies in place is weakly supported, although not across all of the models and outcomes examined. However, the main effect of the counseling letter relative to the non-counseling letter does appear to be robust, suggesting loan modifications are more likely, fewer foreclosures are started, and fewer loans are cured, which is consistent with loans remaining in default but lenders not initiating foreclosure proceedings.

DISCUSSION AND CONCLUSIONS

These results rely on three forms of estimates: first, an estimate of state law effects using intra-MSA estimates of variations in state laws; second, matching estimates of the effects of a lender letter promoting counseling; and finally, an interaction of

5All appendices are available at the end of this article as it appears in JPAM online. See the complete

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state laws and the lender letter. The effects of state laws such as judicial foreclosure procedures and rights of redemption are important to consider in light of past lit-erature suggesting that laws that slow down the foreclosure process may result in worse outcomes for borrowers and lenders. Judicial procedures are associated with a 3 percent marginal increase in loan modifications. State foreclosure-prevention initiatives alone are associated with a 2 percent marginal increase in mortgage modifications (at a lower level of statistical significance, however). These results are obtained using a cross-border identification strategy, obviating state-level endo-geneity between state laws and borrower outcomes. An increase in loan modifica-tions is a positive signal, but the results do not indicate that the probability a loan in default starts foreclosure or cures changes 15 months later at follow-up. Although the precise mechanisms are not observed, we can speculate how these policies impact loans. It seems possible the additional time of judicial proceedings offers borrowers more opportunities to obtain a modification. It is also possible that lenders perceive foreclosure in judicial states to be more costly. Therefore, lenders may be more likely to offer mortgage modifications in states with judicial proceedings. Together, these processes may lead to more modifications. State anti-foreclosure initiatives may increase borrower awareness of loan modification options, including support from state outreach and counseling programs.

Lender letters offering counseling are associated with a 2 percent marginal increase in loan modifications, a 20 percent marginal decrease in foreclosure starts, and a 4 percent marginal decrease in loan cures, using CEM matched weighting to estimate causal effects. The letter does not increase the probability that a delin-quent loan is cured; rather, it causes the lender to delay starting the foreclosure process and increases the likelihood of a loan modification. Interactions between state polices and the lender letter offering counseling provide weak evidence of added effects of the counseling letter in states with judicial foreclosure procedures or states with anti-foreclosure initiatives.

The results presented in this paper have several limitations. The data are derived from one lender during the initial phase of what is clearly one of the more challeng-ing periods in the history of the mortgage lendchalleng-ing industry. The period of analysis occurred prior to the collapse of several well-known subprime lenders and increased media, regulator, and investor scrutiny of servicing practices. State and federal polices and regulatory functions are evolving and may now differ from the period covered in this analysis. Also, this study is based on a relatively short period of analysis; loan cures and foreclosures may require longer than 15 months to ulti-mately be observed.

Overall, these results provide no evidence that state policies offering rights of redemption affect loan outcomes, which is consistent with several prior studies. Judicial procedures and anti-foreclosure policies may have modest short-run pos-itive impacts in terms of consumers receiving loan modifications, however. The finding regarding higher rates of loan modifications is highly relevant given the design of the federal Making Home Affordable initiative and the Home Afford-able Modification Program, which allocated nearly $50 billion in subsidies to lenders and borrowers to promote loan modifications. State foreclosure preven-tion programs may also have some positive associapreven-tions with improved borrower outcomes in the short run. Lender efforts to promote counseling also appear to improve borrower outcomes. This finding is again significant given the launch of the federal National Foreclosure Mitigation Counseling program, which provides over $400 million in subsidies for default counseling and numerous outreach efforts at the state, local, and national levels. To the extent policymakers seek to promote modifications or reduce the pace of foreclosure filings, state policies that offer additional time or promote counseling may benefit mortgage borrowers in default.

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J. MICHAEL COLLINS is Assistant Professor, University of Wisconsin–Madison, 1305 Linden Drive Madison, WI 53706.

KEN LAM is an Associate with Abt Associates Inc., 55 Wheeler Street, Cambridge, MA 02138.

CHRISTOPHER E. HERBERT is Research Director at the Joint Center for Housing Studies, Harvard University, 1033 Massachusetts Avenue, Cambridge, MA 02138. REFERENCES

Apgar, W., & Duda, M. (2004). Preserving homeownership: Community-development impli-cations of the new mortgage market. Chicago, IL: Neighborhood Housing Services of Chicago.

Blackwell, M., Iacus, S. M., King, G., & Porro, G. (2009). CEM: Coarsened exact matching in Stata. Stata Journal, 9, 524–546.

Capozza, D., & Thomson, T. (2006). Subprime transitions: Lingering or malingering in default? Journal of Real Estate Finance and Economics, 33, 241–258.

Clauretie, T. M. (1989). State foreclosure laws, risk shifting, and the private mortgage insur-ance industry. Journal of Risk and Insurinsur-ance, 56, 544–554.

Clauretie, T. M., & Herzog, T. (1990). The effect of state foreclosure laws on loan losses: Evi-dence from the mortgage insurance industry. Journal of Money, Credit and Banking, 22, 221–233.

Collins, J. M. (2007). Exploring the design of financial counseling for mortgage borrowers in default. Journal of Family and Economic Issues, 28, 207–226.

Cutts, A. C., & Merrill, W. (2008). Interventions in mortgage defaults: Problems and practices to prevent home loss and lower costs. In N. P. Retsinas & E. S. Belsky (Eds.), Borrowing to live: Consumer and mortgage credit revisited (pp. 203–254). Washington, DC: Brookings Institution Press.

Ding, L., Quercia, R. G., & Ratcliffe, J. (2008). Post-purchase counseling and default resolu-tions among low- and moderate-income borrowers. Journal of Real Estate Research, 30, 315–344.

Green, W. H. (2003). Econometric analysis, 5th ed. Upper Saddle River, NJ: Prentice Hall. Hayre, L. S., & Saraf, M. (2008). A loss severity model for residential mortgages. Journal of

Fixed Income, 18, 5–31.

Holmes, T. J. (1998). The effect of state policies on the location of manufacturing: Evidence from state borders. Journal of Political Economy, 106, 667–705.

Iacus, S. M., King, G., & Porro, G. (2008). Matching for causal inference without balance checking. Retrieved September 13, 2010, from http://ssrn.com/paper1152391.

Iacus, S. M., King, G., & Porro, G. (2009a). Causal inference without balance checking: Coarsened exact matching. Retrieved September 13, 2010, from http://gking.harvard.edu/ files/cem-plus.pdf.

Iacus, S. M., King, G., & Porro, G. (2009b). CEM: Coarsened exact matching software. Jour-nal of Statistical Software, 30, 1–27.

Mayer, N., Tatian, P. A., Temkin, K., & Calhoun, C. A. (2009). National foreclosure mitigation counseling program evaluation: Preliminary analysis of program effects Washington, DC: The Urban Institute.

Orr, L. L. (1999). Social experiments: Evaluating public programs with experimental meth-ods. Thousand Oaks, CA: Sage.

Pence, K. M. (2006). Foreclosing on opportunity: State laws and mortgage credit. Review of Economics and Statistics, 88, 177–182.

Pennington-Cross, A. (2010). The duration of foreclosures in the subprime mortgage market: A competing risks model with mixing. Journal of Real Estate Finance and Economics, 40, 109–129.

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Pennington-Cross, A., & Ho, G. (2008). Predatory lending laws and the cost of credit. Real Estate Economics, 36, 175–211.

Pew Center on the States. (2008). Defaulting on the dream: States respond to America’s fore-closure crisis. Retrieved October 12, 2008, from http://www.pewtrusts.org/uploadedFiles/ wwwpewtrustsorg/Reports/Subprime_mortgages/defaulting_on_the_dream.pdf.

Phillips, R. A., & VanderHoff, J. H. (2004). The conditional probability of foreclosure: An empirical analysis of conventional mortgage loan defaults. Real Estate Economics, 32, 571–587.

Wood, C. (1997). The impact of mortgage foreclosure laws on secondary market loan losses. Ithaca, NY: Cornell University.

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APPENDIX 1 Borrower Letters

Comparison Group Letter Dear______,

________ takes great pride in helping people achieve the dream of homeownership. It’s more than just our business; it’s our passion. We also endeavor to try to keep hard working people in their homes when they face a crisis that makes it difficult for them to make their payments.

Sometimes things occur beyond anyone’s control that makes it difficult, if not impossible, for homeowners to meet their obligations. The reasons for financial set-backs are varied. Whatever the cause, ________ is committed to working with home-owners to find solutions. There are ways to preserve the dream of homehome-ownership. If you are experiencing a hardship and are worried about making your monthly loan payments, we urge you to call 1-888-555-7777.________’s homeownership preservation team helps people to keep their homes. Our Homeownership Preser-vation counselors are eager to assist you and provide you with options 24 hours a day, seven days a week.

When a homeowner calls 1-888-555-7777, you will have a chance to talk to a Homeownership Preservation counselor about your situation. You won’t be judged about your problems, but you will get a chance to understand what you can do. Calling will not hurt your standing with ________.

We want to help you find the right solution. Delaying your call may limit the options available to you. ________ is eager to assist you in maintaining the dream of home-ownership and avoiding the nightmare of foreclosure. We look forward to hearing from you soon.

Counseling Group Letter

________ takes great pride in helping people achieve the dream of homeownership. It’s more than just our business; it’s our passion. We also endeavor to try to keep hard working people in their homes when they face a crisis that makes it difficult for them to make their payments.

Sometimes things occur beyond anyone’s control that makes it difficult, if not impossible, for homeowners to meet their obligations. The reasons for financial set-backs are varied. Whatever the cause, ________ is committed to working with home-owners to find solutions. There are ways to preserve the dream of homehome-ownership. If you are experiencing a hardship and are worried about making your monthly loan payments, we urge you to call 1-866-903-6218.The hotline is sponsored by the Homeownership Preservation Foundation, a non-profit organization dedicated to keeping more people in their homes. The advice and assistance they offer is free and is available 24 hours a day, seven days a week.

When a homeowner calls 1-866-903-6218,counselors are trained to set up a plan of action designed especially for you and your situation. You won’t be judged, you won’t pay a dime for advice or assistance, and most of all, you won’t be disappointed. We want to help you find the right solution. Delaying your call may limit the options available to you. Even if you feel like you are too far behind already, calling right now could be the difference between keeping your home and being forced out of it.

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T

able A1.

Propensity score weighted estimates of lender letter ef

fects on modification and cure/foreclosure started.

(4) (5) (6) (1) (2) (3) No Longer No Longer No Longer Loan Loan Loan Delinquent Foreclosure Delinquent Foreclosure Delinquent Foreclosure Modified Modified Modified (cure) Start (cure) Start (cure) Start Sent letter 2.29** 3.93** 1.61 0.83** 0.46** 1.01 0.88 0.60 1.31 (0.27) (1.78) (0.92) (0.04) (0.03) (0.38) (0.39) (0.27) (0.62) Letter ⫻ Judicial 0.54 0.69 0.37 ⫹ only state (0.35) (0.37) (0.22) Letter ⫻ State 1.10 1.25 0.37 w/foreclosure initiative (0.74) (0.64) (0.20)

Judicial only state

3.21 ⫹ 1.48 3.98* (2.16) (0.81) (2.60) State w/foreclosure 1.51 0.63 2.29 initiative (1.05) (0.32) (1.23) ARM 0.53** 0.49** 0.58** 1.50** 1.63** 1.41 1.53 1.42* 1.67** (0.07) (0.13) (0.12) (0.09) (0.10) (0.32) (0.41) (0.25) (0.30)

Log loan balance

2.23** 2.15** 2.20** 0.77** 1.45** 0.63* 1.13 0.73* 1.01 (0.23) (0.41) (0.39) (0.03) (0.08) (0.13) (0.30) (0.12) (0.21) Y ear origination 0.83** 0.81** 0.83** 1.01 1.13** 1.02 1.14* 1.04 1.19** (0.01) (0.03) (0.02) (0.01) (0.02) (0.04) (0.06) (0.03) (0.06) FICO 0.56** 0.50* 0.57* 1.38** 2.71** 1.91** 3.19** 1.23 2.65** (0.06) (0.13) (0.13) (0.08) (0.18) (0.40) (0.81) (0.21) (0.58) FHA/V A 1.36* 1.14 1.17 2.02** 2.14** 1.86* 1.81 ⫹ 1.93** 2.22** (0.19) (0.27) (0.28) (0.14) (0.18) (0.49) (0.58) (0.45) (0.67) EIS 0.67** 0.58* 0.74 1.03 1.73** 1.06 2.05* 1.15 1.90 (0.06) (0.14) (0.15) (0.05) (0.10) (0.24) (0.68) (0.21) (0.65) Days 1.22** 1.29** 1.23** 0.91** 1.20** 0.90 ⫹ 1.23* 0.90* 1.22** (0.04) (0.08) (0.08) (0.02) (0.03) (0.05) (0.10) (0.04) (0.08) Subprime 1.28 1.92 1.31 0.38** 2.54** 0.41 ⫹ 1.88 0.41** 1.56 (0.30) (1.08) (0.74) (0.04) (0.27) (0.19) (0.96) (0.13) (0.63) Refinance 1.90** 2.01* 2.11** 0.99 0.64** 1.02 0.52* 0.91 0.52** (0.24) (0.58) (0.60) (0.07) (0.05) (0.25) (0.14) (0.16) (0.10) L T V 1.02** 1.02* 1.03** 0.99** 1.03** 0.99 1.04** 1.00 1.03** (0.00) (0.01) (0.01) (0.00) (0.00) (0.01) (0.01) (0.01) (0.01) Low Doc 1.29 1.18 1.40 0.66** 1.07 0.82 1.29 0.68 0.57 (0.23) (0.38) (0.48) (0.05) (0.08) (0.32) (0.48) (0.18) (0.22) N 8,023 3,991 6,439 8,023 3,991 6,439 x 2 431.27** 168.55** 180.37** 2574.77** 126.29** 201.97** Note:

Cross-border MSAs with at least one state with law in ef

fect and one not in ef

fect; estimates as exponentiated coef

ficients and

robust standard errors in

parentheses. ⫹p ⬍ 0.10; * p ⬍ 0.05; ** p ⬍ 0.01.

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T

able A2.

Descriptive statistics: Loan outcomes and incidence of state laws by MSA.

March 2008 Loan Status

No Longer Judicial State w/ Foreclosure Delinquent Loan Only State w/ Foreclosure Cross-Border MSA Start (cure) Modified State Redemption Initiative Num. Obs. Augusta-Aiken 0.09 0.30 0.17 0.17 0.00 0.00 Boston-W orcester 0.18 0.22 0.07 0.88 0.01 0.99 Charlotte-Gaston 0.12 0.25 0.10 0.06 0.00 0.94 Chattanooga 0.13 0.30 0.06 0.00 0.69 0.00 Chicago 0.19 0.27 0.09 0.98 0.88 0.98 1,199 Cincinnati 0.22 0.25 0.10 1.00 0.22 0.78 Columbus, GA-AL 0.07 0.34 0.04 0.00 0.27 0.00 Davenport 0.23 0.32 0.10 0.36 1.00 0.36 Evansville 0.29 0.29 0.12 0.98 0.17 0.83 Johnson City 0.19 0.31 0.03 0.00 0.78 0.22 Kansas City 0.19 0.26 0.04 0.24 1.00 0.76 Las V egas 0.28 0.15 0.03 0.00 0.05 1.00 Louisville 0.21 0.28 0.05 1.00 0.71 0.30 Memphis 0.15 0.23 0.12 0.00 0.98 0.00 Minneapolis-St. Paul 0.35 0.17 0.04 0.00 1.00 0.96 New Y ork 0.18 0.23 0.04 1.00 0.37 0.64 1,287 Omaha, NE-IA 0.25 0.32 0.09 0.89 0.11 0.00 Philadelphia 0.16 0.23 0.07 1.00 0.29 0.71 Portland-Salem 0.08 0.21 0.09 0.00 0.80 0.00 Providence 0.26 0.17 0.11 0.19 0.00 1.00 St. Louis, MO-IL 0.19 0.26 0.05 0.13 1.00 1.00 W ashington-Baltimore 0.17 0.17 0.08 0.66 0.00 0.90 T otal 0.19 0.23 0.07 0.64 0.48 0.77 8,044 Note:

References

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