Strategic Default on First and Second Lien Mortgages During the Financial Crisis

WORKING PAPER NO. 11-3

STRATEGIC DEFAULT ON FIRST AND SECOND LIEN

MORTGAGES DURING THE FINANCIAL CRISIS

Julapa Jagtiani

Federal Reserve Bank of Philadelphia

William W. Lang

Federal Reserve Bank of Philadelphia

December 9, 2010

Strategic Default on First and Second Lien Mortgages

During the Financial Crisis

Julapa Jagtiani

Special Advisor

Supervision, Regulation and Credit

Federal Reserve Bank of Philadelphia

William W. Lang

SVP and Chief Examinations Officer

Supervision, Regulation and Credit

Federal Reserve Bank of Philadelphia

December 9, 2010

Abstract

Strategic default behavior suggests that the default process is not only a matter of inability to

pay. Economic costs and benefits affect the incidence and timing of defaults. As with prior research,

we find that people default strategically as their home value falls below the mortgage value (exercise

the put option to default on their first mortgage). While some of these homeowners default on both

first mortgages and second lien home equity lines, a large portion of the delinquent borrowers have

kept their second lien current during the recent financial crisis. These second liens, which are current

but stand behind a seriously delinquent first mortgage, are subject to a high risk of default. On the

other hand, relatively few borrowers default on their second liens while remaining current on their first.

This paper explores the strategic factors that may affect borrower decisions to default on first vs. second

lien mortgages. We find that borrowers are more likely to remain current on their second lien if it is a

home equity line of credit (HELOC) as compared to a closed-end home equity loan. Moreover, the size

of the unused line of credit is an important factor. Interestingly, we find evidence that the various

mortgage loss mitigation programs also play a role in providing incentives for homeowners to default on

their first mortgages.

JEL Classification Codes: G28, G21, G18, G01

Key Words: Mortgage, Home Equity Loan, Default Behavior, Strategic Default, Loan Modification,

Financial Crisis

------------------------

The authors thank Mitch Berlin, Larry Cordell, Kris Gerardi, Chris Henderson, Bob Hunt, Sougata

Kerr, Andreas Lehnert, Leonard Nakamura, and participants at the Federal Reserve System

Committee Conference for their comments. Special thanks to Kris Gerardi for his extensive and

helpful comments, Joanne Chow for her dedicated research assistance, and to Bob Hunt for data

access and support for this project. The views expressed here are those of the authors and do not

necessarily represent the views of the Federal Reserve Bank of Philadelphia or the Federal Reserve

System. This paper is available free of charge at www.philadelphiafed.org/research-and-

data/publications/working-papers/. Please direct correspondence to Julapa Jagtiani, Federal

Reserve Bank of Philadelphia, Ten Independence Mall, Philadelphia, PA 19106, Tel: 215-574-7284,

e-mail: Julapa.Jagtiani@phil.frb.org.

Strategic Default on First and Second Lien Mortgages

During the Financial Crisis

Julapa Jagtiani and William W. Lang

I. Introduction

The housing and mortgage crisis dramatically changed the consumer credit landscape. The

sequence of a major housing price boom followed by a collapse of housing prices was accompanied by a

major shift in default behavior as many households began defaulting on mortgage debt while remaining

current on other forms of consumer debt (e.g., credit cards and car loans).

While the change in priority of defaults between mortgage and non-mortgage debt has received

a good bit of attention (see Edmans (2010), Guiso, Sapienza, and Zingales (2009), and Sapienza and

Zingales (2010)), this paper focuses on an issue that has not received much attention: priority of default

between first mortgages and second lien mortgages on the same home. Second lien mortgages are

home equity loans that are either closed-end home equity loans (HELOANs) or home equity lines of

credit (HELOCs). At first glance, it might appear that consumers (as opposed to creditors) should make

no distinction between the lien positions of their mortgages, since lenders have the right to foreclose in

either case. If default on either mortgage obligation results in the same eventual outcome (foreclosure),

why would a consumer default on one mortgage obligation without defaulting on the other? This paper

explores several hypotheses to explain actual household behavior where borrowers may strategically

default on one mortgage obligation while remaining current on another.

Why might households default on their first mortgage but not default on their home equity

loans? One explanation for this behavior is that households do not act strategically but rather default

because they are unable to make loan payments – the “inability to pay” hypothesis. Since first mortgage

payments are typically much higher than payments on home equity loans, a household may be able to

make the home equity payment but not the payment on the first mortgage.

An alternative explanation suggests a more strategic approach to default. Some households

that anticipate ultimately going to foreclosure may wish to stop paying their largest debt payment,

which is typically their first mortgage payment. However, since foreclosure can be a slow process, these

borrowers may decide that they are better off continuing to make their home equity payments to allow

them to maintain some access to credit (e.g., unused HELOCs, unused credit card lines, additional credit

card or card loans).

This explanation would suggest that consumers with high unused HELOCs would be

less likely to default on their home equity loans, even though they have defaulted on their first

mortgage.

What about borrowers who might default on their home equity loans but remain current on

their first mortgage? In some cases, particularly for mortgage borrowers whose combined mortgage

debt exceeds the value of the home, this would seem like a rational strategy. In order to force a

borrower into foreclosure, the second lien lender must acquire the first lien. In other words, the home

equity lender must take on the entire mortgage debt on the home. This is rarely a profit-maximizing

strategy by the home equity lender when the household has negative equity, since the home equity

lender will usually not receive any recoveries in the foreclosure process on its original second lien

position.

By taking over the first lien, home equity lenders would only expose themselves to additional

downside risk.

Given the large number of current homeowners with negative equity, there are likely a large

number of borrowers who could default on their home equity loans without being forced into

foreclosure if they continue to pay their first mortgage. This situation would be more likely to occur if

Default behavior/incentive may also be affected by the foreclosure process, which varies across geographic

regions. We expect less of this type of strategic default in states where the foreclosure process is shorter.

This is because the home equity loan is generally small compared with the first lien. If the combined mortgage

debt is less than the value of the house, then typically there is very little or no equity support for the home equity

loan, and any equity support will be outweighed by costs associated with the foreclosure process. If the home

equity loan is large relative to the first mortgage, then it’s possible that the home equity lender can see some

recoveries even when the homeowner has negative equity.

the borrower has negative equity based on the current combined loan-to-value (CLTV) ratio and little or

no equity after eliminating the home equity loan.

The data indicate, however, that borrowers rarely

engage in this strategy even though it appears to be viable. The last two columns of Table 1, from

Goodman, Ashworth, Landy, and Yin (2010), show the degree of homes that are underwater when

considering just the first lien (current LTV more than 100 percent) and when the first and second liens

are combined (current CLTV more than 100 percent), respectively. Given the degree of second liens that

have been underwater during the current mortgage crisis and given that second lien holders are not

likely to foreclose on many of these underwater second liens, it is surprising to find that the default rate

for first lien mortgages far exceeds the default rate on the second lien mortgage for the same property.

This paper investigates the factors underlying the pattern of defaults between first and second

lien mortgages and, in particular, why many borrowers remain current on their second lien while in

default on the first mortgage. The rest of the paper is organized as follows. Section II provides a

literature review on mortgage default models and consumer strategic default behavior. Sections III

describes the data used for our analysis. Empirical results are presented and discussed in Section IV,

which is divided into several sub-sections. We present some evidence of consumer default behavior

across financial products in Section IV.1, then focus on the default behavior for mortgage products (first

vs. second liens) in Section IV.2, and present some evidence of the impact from loan modification in

Section IV.3. Section IV.4 presents mortgage default models for first mortgage and second liens (also

HELOC vs. HELOAN among second liens). Finally, we investigate accounts with first mortgage default

more closely and track the borrower behavior regarding their default behavior and credit score (in

Section IV.5) and track any changes in the borrowers’ credit line limit and utilization (in Section IV.6).

Conclusions and policy implications are discussed in Section V.

Note that while homeowners could default on their second lien mortgages, lower their monthly mortgage

payment, and stay in the home, the loan contract stays valid and unpaid interest payments would keep

accumulating. Should the house be sold in the future, the second lien creditor would be eligible for the recovery

after the first lien creditor is paid in full.

II. Literature and Our Contribution

Mortgage Default Literature:

There has been extensive research explaining mortgage defaults. This research has substantially

increased in recent years as interest has been stirred by the mortgage crisis and researchers have gained

access to large loan-level data sets on residential mortgages. Previous research has found several

factors to be important in determining mortgage default.

FICO Score: Elul (2009) finds that low FICO scores have a greater impact on subprime low-doc

delinquency rates than they do on similar full-doc loans. We include FICO score at origination, the

refreshed risk score from the credit bureau, as well as indicator variables for subprime and alt-A

mortgage loans.

Loan-to-Value (LTV) and Combined LTV (CLTV): The role of house prices and LTV ratio in

mortgage default has been studied quite extensively; see, for example, Archer, Elmer, Harrison, and Ling

(2002), Downing, Stanton, and Wallace (2005), Bajari, Chu, and Park (2008), Krainer, LeRoy, and

Munpyung (2009). Downing, Stanton, and Wallace (2005) use a two-factor structural mortgage pricing

model in which rational mortgage holders endogenously choose when to prepay and/or to default,

subject to explicit frictions such as transaction costs. They find that house prices play an important role

in the default decision, being both statistically and economically significant.

Bajari, Chu, and Park (2008) focus on subprime mortgages, and they find that negative equity

(due to the nationwide decrease in home prices) was an important driver behind subprime borrowers’

decision to default during the financial crisis. Sherlund (2008) and Mayer, Pence, and Sherlund (2009)

find that a combination of negative equity (LTV > 100%) and a high combined loan-to-value (CLTV) ratio

together lead to more defaults. When controlling for CLTV, borrowers with piggyback second liens tend

to default at a higher rate than otherwise – for example, a borrower with a 95 percent LTV on the first

lien would be less likely to default than another borrower with a 95 percent CLTV (85 percent LTV on the

first lien and 10 percent LTV on the piggyback second lien). We include both LTV and CLTV in our

analysis. In addition, we control for the ratio of the second lien balance to the first mortgage monthly

payment.

Correlation Between LTV and Other Risk Factors: Elul, Souleles, Chomsisengphet, Glennon, and

Hunt (2010) use credit card utilization rates as a measure of liquidity and conclude that both negative

equity and illiquidity are significant in determining mortgage default and that the effect of illiquidity and

negative equity are correlated. On the contrary, Krainer, LeRoy, and Munpyung (2009) find that the

effect of LTV on mortgage default (using more recent data) does not interact to a major extent with

other risk factors.

Income and Payment-to-Income Ratio: Herzog and Earley (1970) find that borrowers with

greater income variability (e.g., self-employed borrowers and salespeople) at the time of loan

origination are more likely to default on their mortgages than other professionals whose income is less

variable (e.g., executives). Williams, Beranek, and Kenkel (1974) find that borrowers with an initial

payment-to-income ratio higher than 30 percent were significantly more likely to default. More recent

studies, such as Bajari, Chu, and Park (2008), also find that higher payment-to-income ratios elevate

default rates in the subprime market. In addition, Johnson and Li (2010) find that the payment-to-

income ratio is a true measure of liquidity and that it is an indicator of borrowing constraints.

Households with higher payment-to-income ratios are significantly more likely to be turned down for

credit than other households. We include the log of the first mortgage monthly payment as a proxy for

the borrower’s ability to make his monthly mortgage payment.

Location and Mortgage Issuer: Von Furstenberg and Green (1974) find that location of the

property plays a role in mortgage default, since loans made in suburban locations are less risky.

Williams, Beranek, and Kenkel (1974) find that the local unemployment rate plays a role. Titman and

Tsyplakov (2010) find that mortgages that are originated by institutions with large negative stock returns

in the quarters prior to the origination date tend to have higher credit spreads and are more likely to

default than other mortgages with similar characteristics.

Fixed-Rate Mortgage (FRM) vs. Adjustable-Rate Mortgage ( ARM): Zorn and Lea (1989) examine

mortgage default for FRMs vs. ARMs and find that the default risk of ARMs is higher than that of FRMs

and that ARMs (by design) have the potential for higher real mortgage interest rates. Further,

Cunningham and Capone (1990) examine mortgage termination behavior under various specific ARM

adjustment periods and conclude that ARMs overall have a greater default risk than FRMs. Krainer,

LeRoy, and Munpyung (2009) also find that high-LTV ARMs are much more prone to default than FRMs

with the same LTV and that the yield premium on high-LTV ARMs is much higher than that of similar

FRMs.

Strategic Default Literature:

Guiso, Sapienza, and Zingales (2009) estimate that 26 percent of existing mortgage defaults are

strategic. Moral and social considerations appear to be an important barrier to strategic default. Guiso,

Sapienza, and Zingales (2009) find that people who consider it immoral to default are 77 percent less

likely to do so, and people who know someone who strategically defaulted are 82 percent more likely to

default. This type of contagion results in a nonlinear increasing relationship between willingness to

default and foreclosures in the same ZIP code. Moreover, as default behavior becomes more common

and widely known, this could reduce the social stigma associated with strategic default.

Jackson and Kesserman (1980) find support for the net-equity maximization model of default.

Foster and Van Order (1984) investigate an option-based mortgage default model in which default is a

put option. Borrowers would exercise the put option (i.e., default) when the value of the house plus any

costs of exercising the option falls below the mortgage value.

Some borrowers, however, do not default on their mortgage even with negative equity.

Epperson, Kau, Keenan, and Muller (1985) argue that borrowers may be better off not defaulting now

even with negative equity because, by defaulting now, the borrowers would forfeit the option to

exercise their put (to default) in the future. When incorporating an estimate of LTV over time into the

option-based default model, Foster and Van Order (1984) find that the model works very well in

predicting mortgage default. In addition, other (transaction) costs, such as moving costs and the

deterioration of the borrower’s credit rating, may also play a role in the cost-benefit analysis of

mortgage default. Rational borrowers would default only when the value of the collateral falls below

the mortgage value by an amount equal to the net transaction costs.

Unlike previous studies, this study concentrates on consumer strategic default behavior for their

first mortgages vs. their second liens. The existing literature often refers to strategic default being an

extreme case in which a homeowner’s income is well above what is required to comfortably make

payments but chooses to default because the home is a bad investment. In reality, the majority of

homeowners who default are those whose income is sufficiently low so that mortgage payments are

difficult but not impossible. Elul, Souleles, Chomsisengphet, Glennon, and Hunt (2010) find that

mortgage borrowers default even when they have sufficient liquidity to continue paying. While these

homeowners may have access to sufficient liquid assets, they may decide to default as they determine

that continuing to pay the mortgage will deplete their wealth without sufficient compensation (such as

avoiding bankruptcy costs or moving costs and social stigma).

III. The Data

Our primary source of data comes from a large random sample of individual credit records

drawn at the end of each quarter from Equifax, Inc., one of the national credit bureaus. The same

anonymous credit records are selected by Equifax each quarter and provided to us with sequence

See Quigley and Van Order (1991), Crawford and Rosenblatt (1995), and Deng, Quigley, and Van Order (2000) for

more on the role of transaction costs in the option-based model for mortgage default. Also, see Quercia and

Stegman (1992) for other related issues, such as factors that determine prepayment, lender’s decision to foreclose,

and delinquency decision (decision to delay mortgage payment).

number and no personal identifying information. The consistent unique sequence numbers allow us to

track individual credit experience over time. These data cover from the first quarter of 1999 through

the first quarter of 2010 and include summary information on the credit accounts each individual

maintains. The data contain balance, credit limit or loan amount, and delinquency status for first

mortgages, home equity loans and lines, bank cards, auto loans, student loans, and other loan types.

This study includes only consumers who have only one first mortgage and at least one second lien home

equity over the period 2004:Q4 to 2010:Q2.

Using information from the FRB Consumer Credit Panel Data (Equifax database), we calculate

additional credit characteristics: combined loan-to-value (CLTV) ratio, aggregate card utilization, HELOC

line utilization, etc. When the property is jointly owned by two or more owners, we calculate total

available line of credit and their usage based on the combined balances for all the joint owners, and the

credit score used is the highest score of all the joint owners.

We then merge the Equifax data with another database (loan-level data, updated monthly) from

LPS Applied Analytics (McDash), which consists of all mortgage loans issued by nine of the top ten

mortgage servicers in the U.S., covering approximately 75 percent of outstanding mortgage loans as of

year-end 2009. We use a 5 percent random sample of all the loan observations, excluding loans that

were originated before 2000 or have missing FICO scores at origination. The merged data sets allow us

to obtain additional credit information about the borrowers and characteristics of the first mortgage

loans, which are not available from the Equifax database, such as the original FICO score, original loan-

to-value (LTV) ratio or down payment, original debt-to-income (DTI) ratio, and other characteristics of

the loan.

Following the merging approach used in Elul, Souleles, Chomsisengphet, Glennon, and Hunt

(2010) and Henderson and Jagtiani (2010), we merge the LPS and Equifax data based on the following

characteristics of first mortgage loans: ZIP code, open date, and initial balance. To ensure correct

identification of the associated property for the purpose of calculating CLTV, we exclude borrowers with

more than one first mortgage loan and those with no HELOC. By focusing on customers with only one

first mortgage, we generally avoid the issue of customers defaulting on a first mortgage on one property

(e.g., a vacation home) while remaining current on a second mortgage for another property (e.g., a

primary residence).

In this study, we focus on the issue of borrowers defaulting on one of their

mortgages for their primary residence while remaining current on the other.

Our data cover the period from December 2004 to June 2010, thus including both the boom

(pre-crisis) and bust (post-crisis) periods. Our economic data include (state-level) home-price index

(HPI) data from the Federal Housing Finance Agency (FHFA), formerly the Office of Federal Housing

Enterprise Oversight (OFHEO). The HPI is a weighted repeat-sales index based on mortgage

transactions on single-family properties (purchased or securitized by Fannie Mae or Freddie Mac) and

within the conforming amount limits. Other economic factors are from the Haver Analytics database.

IV. The Empirical Results

1. Default Behavior Across Financial Products

To get an overview of how default behavior has changed for different consumer products, we

examine the incidence of consumer defaults in our sample across four major financial products: first

mortgage, second lien home equity (HELOCs and HELOANs), credit cards, and auto loans.

Our sample

for this analysis includes only those customers from the merged LPS and Equifax data who have all four

financial products. We observe the default information as of December 31 of each year from 2004 to

2009 across these four products.

A small number of households finance a property solely with a HELOC, so it is possible that a small number of

households in our sample will have first and second mortgages on different properties.

Lee and Tracy (2010) find that second lien originations peaked at $100 billion per quarter in 2006 and then

declined to about $10 billion as of the first quarter of 2010.

Default is defined as being at least 90 days past due as of observation dates (December 31 of

each year). Default on second lien home equity, credit cards, and auto loans is based on information

from the Equifax database. Default information on first lien mortgages (for the same loan) is not always

consistent between what was reported in the LPS and Equifax databases (probably due to different time

lags, since the McDash database is updated monthly, while we receive the Equifax data quarterly). Thus,

we measure first lien default in two ways: one based on McDash LPS default information and another

based on the Equifax database.

Figure 1 exhibits default rates for the various financial products based on data about consumers

who have all four financial products: first lien mortgage, second lien mortgage of the same property

(HELOAN and/or HELOC), credit cards, and automobile loan. Figure 1 demonstrates the different

default rates for the same customers across the four financial products. First mortgage default based on

the McDash LPS is labeled in RED, and the first mortgage default based on the Equifax database is

labeled in YELLOW. The difference in the first mortgage default rates from these two sources is not

large enough to change the defaulting sequence.

It is evident that credit cards have the highest default rate overall, both before and during the

financial crisis. Prior to the financial crisis, default rates on auto, first lien, and second lien mortgages

were minimal in 2004-2005, although the default rate on first lien mortgages seemed to be slightly

lower than that of second lien mortgages prior to 2006. Default rates on both first and second lien

mortgages increased significantly in 2006-2007 and rose dramatically after year-end 2007. For the

period 2007-2009, borrowers were most frequently defaulting in the following order: credit cards, first

lien mortgage (prime and subprime), second lien home equity (HELOC & HELOAN), and auto loans.

Focusing on mortgage defaults, our results indicate that the default rate for first mortgages far

exceeded those of the second lien mortgages during the financial crisis. This behavior was not observed

in the pre-financial crisis period (i.e., the booming period of 2004-2006). In addition, Figure 2 shows that

among all second liens, the default rate is substantially lower for HELOCs than for (closed-end)

HELOANs.

2. Default Behavior on Mortgage Products

The analysis in this section includes all the customers from the merged LPS and Equifax database

who have only one first lien mortgage and at least one second lien home equity loan; these customers

total 90,855. We observe the delinquency status of these customers during the period 2004 to 2009.

To ensure consistency in default information, default data on both first and second liens were collected

from the Equifax database.

As shown in Table2, Panel A, about one-third of those borrowers who defaulted on their first

lien mortgage kept their second lien mortgages current. Surprisingly, about 20 percent of borrowers in

the process of foreclosure due to defaults on the first mortgage actually kept their second lien mortgage

current. Among those who defaulted on their second lien mortgages, about 80 percent also defaulted

on their first lien mortgage. These data seem to contradict the hypothesis that consumers would

strategically default on a second lien and keep their first lien current (to reduce their monthly payment

without a foreclosure). Instead, a far larger number of households do the opposite; that is, they default

on their first lien (thus risking a foreclosure of their home) while keeping their underwater second lien

mortgages current.

The bottom two rows of Table 2, Panel A show that, given that the borrowers have defaulted on

their first lien, homeowners are more likely to keep their second lien HELOC current (34.16 percent)

compared to the current rate on closed-end HELOANs (24.39 percent). This evidence is consistent with

a hypothesis that borrowers have incentives to keep their second lien current (after having stopped

paying their first mortgage) in order to maintain their access to credit line through HELOC. We further

investigate this issue below.

3. Impact of Loan Modification Programs on Mortgage Defaults

We examine whether there is any significant difference in default behavior among borrowers

with vs. without the loan modification. Several Treasury-sponsored housing programs have been

introduced during the recent crisis, including the Home Affordable Modification Program (HAMP). It is

yet to be seen how successful the HAMP program is in the long run, although the outcomes so far have

not been encouraging. We examine mortgage default rates separately for homeowners with vs.

without loan modification, as presented in Table 2, Panels B and C.

Data used for Table 2, Panel B (with loan modification) and Panel C (without loan modification)

do not include 2004 observations, since there was no information on loan modification until 2005.

The

results suggest a positive correlation between first mortgage default and the loan modification program.

For borrowers associated with loan modification, about 42 percent of those who defaulted on their first

mortgages kept their second liens current. For this group of borrowers, more than 95 percent of those

who defaulted on their second liens also defaulted on their first mortgage; that is, less than 5 percent

kept their first lien mortgage current. Overall, we find a significant difference in default rate among

borrowers with and without the mortgage loss mitigation programs.

Loan modification programs may provide incentives for homeowners to default as homeowners

are not likely to be approved for a modification unless they have missed their mortgage payments. In

some cases, borrowers may need to be as late as 90 DPD for their accounts to be handed over to the

modification department so that their loans could be renegotiated. Since most loan modifications are

modifications of the first mortgage, the availability of a loan modification may provide incentives for

borrowers to stop paying on their first mortgage while staying current on their second.

When the loan modification status is marked as “unknown” in the LPS database, we assume that there is no loan

modification. The majority of loan modification in our sample occurred in 2008 and 2009 – 2.4percent in 2005, 3.7

percent in 2006, 9.3 percent in 2007, 26.7 percent in 2008, and 57.8 percent in 2009.

We investigate the role of loan modification further by examining default behavior both before

and after (re-default) the modification. Focusing on modified loans only, we find that, on average, about

half of these modified loans were delinquent (at least 60 DPD) prior to the start of the modification and

most of them returned to the current status after the completion of modification. However, a large

portion of these loans actually re-defaulted within six quarters after the modification – specifically, 47

percent of these loans became at least 60 DPD and 38 percent became at least 90 DPD within six

quarters following the modification.

From the supervisory viewpoint, predicting mortgage losses has become more difficult with the

increase in strategic default behavior and the increase in loan modifications. Future losses will be highly

dependent on whether these loan modifications are sustainable or they simply delay eventual defaults.

This uncertainty is increased by the potential for strategic default behavior by the large number of

borrowers with negative equity. A large portion of first mortgages with estimated LTV ratios greater

than 100 percent is still current, but the continued willingness and ability of these homeowners to make

their mortgage payments is subject to great uncertainty. In a recent SEC filing, J.P. Morgan Chase has

noted the bank’s concern about the rising tide of strategic default related to first mortgages. Similarly,

losses in the home equity portfolio are closely tied to the eventual performance of first lien mortgages.

If the first mortgages terminate in foreclosure, borrowers will default on the associated second lien in

the vast majority of cases.

4. Important Factors That Determine Mortgage Defaults

This section investigates the relationship between the characteristics of the borrowers, the

characteristics of their debts, and the pattern of their strategic default decisions. Our basic empirical

model is a logistic model of mortgage default as written in equation (1) below:

Due to our data limitation, we are not able to observe the delinquency status for some modified loans after the

sample period has ended – e.g. for loan modification that occurred around the end of 2009.

Prob = F (Borrower’s Characteristics, Loan Characteristics, Economic Factors) ----------– (1)

where Prob is the probability of default (or foreclosure). The various risk factors that represent

characteristics of the borrowers, the loan contract, and the economic environment are listed below:

First mortgage monthly payment -- Ln (Monthly 1

Paymt) – Larger monthly payment is

expected to be associated with increasing delinquency rate on first mortgages.

Ratio of second lien monthly payment relative to first lien monthly payment -- % 2

Bal to 1

Paymt -- The larger the ratio (greater payment burden), the less likely that the second lien

mortgage would be current.

Log of dollar amount of credit line available (unused) from HELOC -- Ln (HELOC Line Avail) –

Borrowers may have incentives to continue payments on their HELOC even after first mortgage

became delinquent in order to retain their access to the credit line.

Dummy variable indicating whether first lien mortgage is prime (base case), Alt-A (as indicated

by D_AltA) or subprime (as indicated by D_Subprime).

Ratio of credit card utilization – as a measure of the borrower’s liquidity position -- % Card

Utilization –This is measured as a ratio of combined card balances to combined total credit lines

of all the joint owners of the property. Larger credit card utilization is associated with less

access to liquidity and probably less ability to make mortgage payments.

Credit score based on Equifax’s refreshed credit score -- Updated Risk Score. The risk score is

expected to be highly related to delinquency status of the borrower.

Effective loan to value (ELTV) ratio – using the original LTV ratio adjusted with home price index

(HPI) at the state level. To indicate the degree of underwater for a first mortgage, an indicator

variable is created, where D_ELTV >90 is equal to one if the ELTV ratio is greater than 90

percent, and zero otherwise.

Effective combined loan to value (ECLTV) ratio – measures the degree of underwater for second

lien mortgages as the loan amount is calculated based on first lien and second lien combined.

An indicator variable is created, where D_ECLTV >90 is equal to one if the ECLTV ratio is greater

than 90 percent, and zero otherwise.

Other dummy indicators include whether the loan is associated with the loss mitigation

programs (D_Loan Modification), whether it is a jumbo loan (D_Jumbo 1

Mortgage), whether it

is an option ARM (D_Option Arm 1

Mort), whether it is a closed-end second lien (D_HELOAN)

rather than a line of credit, and year dummies with 2004 being the base year (D_2005, D_2006,

D_2007, D_2008, and D_2009).

First Mortgage Default: Columns 1 and 2 of Table 3 show that the four most important factors

that determine whether a first mortgage would be delinquent and/or foreclosed are the monthly

mortgage payment amount (positive coefficient), updated risk score (negative coefficient), whether it is

underwater (positive coefficient on D_ELTV>90), and whether it is associated with loan modification or

other loss mitigation programs (positive coefficient). As expected, a larger monthly payment, in

conjunction with negative equity, provides a real incentive for homeowners to default on the mortgage.

The risk score is negatively associated with delinquency status, as expected.

It is interesting to find that first mortgage default is highly associated with the loss mitigation

program such as the loan modification, even after controlling for all the relevant risk factors. This

finding provides support for our earlier results that the default rate for first mortgages is significantly

higher for borrowers with loan modification, as shown in Panels B and C of Table 2.

Surprisingly, the liquidity measure (as proxied by credit card utilization) has a significantly

negative coefficient, indicating that borrowers with more access to credit (i.e., with a larger unutilized

credit line) are more likely to default on their first mortgage, controlling for other risk factors. This

result is consistent with the strategic default vs. inability to pay hypothesis.

Finally, the significant and positive coefficients for the 2007, 2008, and 2009 year dummies

suggest that the default rate for first lien mortgages was rising during the financial crisis, even after

accounting for the negative equity, loan modification, and other risk factors – implying that other factors

not included in the analysis (e.g., rising unemployment during the financial crisis) also play a role in rising

mortgage defaults.

Second Lien Default: Second mortgage default (both HELOC and HELOAN) is affected by some

of the same factors related to first lien default, particularly credit score and negative equity. From

columns 3 and 4 of Table 3, homeowners are more likely to default on their second lien mortgages (both

HELOC and HELOAN) when the effective CLTV is greater than 90 percent. In addition to negative equity,

borrowers with lower credit scores are more likely to default. Our findings are consistent with the

literature that finds that negative equity is a necessary but not sufficient condition for mortgage default

(or foreclosure) -- see Foote, Gerardi, Goette, and Willen (2008). Moreover, loan modification seems to

increase the default rate on closed-end home equity loans (HELOANs) but has no significant impact on

home equity lines of credit (HELOCs).

Borrowers with more access to liquidity (smaller card utilization ratio) are more likely to default

on their second liens (both HELOC and HELOAN) payments; this is inconsistent with the ability to pay

hypothesis. Moreover, borrowers with a smaller second lien balance (relative to first lien payment) are

more likely to default. For HELOCs (column 3), we also find that homeowners with larger credit lines

available (unused) through a HELOC are less likely to default on their HELOC payments, as they are

probably motivated to maintain their access to the credit line. These findings are, again, consistent with

our strategic default (rather than ability to pay) hypothesis.

First Mortgage Default & Second Lien Current: To further investigate consumers’ mortgage

default patterns during the financial crisis, we examine factors that influence homeowners’ decision to

default on their first lien while keeping their second lien mortgage current. The results from Table 4,

column 1 show that borrowers who default on their first lien mortgage but keep their second lien

current tend to have the following characteristics: larger first lien monthly payment, smaller second lien

balance relative to first lien payment, negative equity, lower risk score, are subprime borrowers, and are

more liquid (have more access to credit due to smaller card utilization ratio). The coefficient of the

HELOAN dummy is significantly negative, indicating that this pattern of default (first lien default while

keeping second lien current) is more common among borrowers with HELOCs, rather than HELOANs.

In addition to the joint default decision based on the entire sample reported in column 1, we

also examine important factors that determine homeowners’ decision to keep their second lien

payments current, given that they have already defaulted on the first mortgage (where default is

defined as being at least 90 days past due). The results are reported in column 2 of Table 4. Again, we

find that borrowers who decide to keep their second lien payments current are likely to have second

lien HELOCs rather than HELOANs, as indicated by the significant negative coefficient of the HELOAN

dummy indicator, controlling for all other relevant risk factors.

5. Post-First Mortgage Default – Tracking Consumers’ Default and Their Risk Score:

This section investigates the default behavior on other financial products for borrowers who

have defaulted on their first mortgages. In addition, we investigate whether the risk score for defaulted

borrowers is updated on a timely basis to reflect their delinquency status on first mortgage. Our

analysis is based on information from the quarterly Equifax database. Our sample includes all borrowers

with only one first lien and at least one second lien (HELOC and/or HELOAN). We track the risk score

and default rate up to three quarters after the borrowers default (60+ DPD and 90+ DPD) on their first

mortgage during the period 2004:Q4 to 2010:Q2. The results are presented in Table 5.

From Panel A of Table 5, more than two-thirds of the loans that became 60+ DPD remained at

60+ DPD in the following quarters, i.e., 79 percent, 70 percent, and 63 percent in the first, second, and

third quarter, respectively. The rest dropped out due to refinancing, became less than 60 DPD, or due to

lack of information (since we could not track performance beyond 2010:Q2).

Second Lien Mortgages and Other Financial Products: Of the remaining loan observations in

each quarter following the default on first mortgages, we find that 45 percent of the borrowers remain

current on their second liens in the first quarter. Will these borrowers continue keep current on their

second lien, or do they default on their second liens with a lag? We follow these borrowers through

time, and the results indicate that the ratio of current second liens does not decline. About half of

borrowers who default on their first mortgages continue to keep their second lien current at least three

quarters later. In addition, an even larger percentage of these borrowers keep their credit card

payments (58 percent) and auto loans (76 percent) current.

The default behavior observed after the

borrowers became 90+ DPD on their first mortgages shows similar results, as presented in Panel B of

Table 5.

Risk Score: Interestingly, we find that only about half of the borrowers who defaulted on their

first mortgages had their risk score downgraded in the quarters following the default, while the other

half actually had their risk score upgraded. This raises a potential question of how accurate and timely

the credit risk score gets updated and reported. This is a concern particularly in the recent financial

crisis period where default rates increase rapidly.

6. Post-First Mortgage Default: Tracking Banks’ Line Management and Utilization

We found (in the previous section) that borrowers with higher unused HELOC lines were more

likely to remain current on their second liens after they had defaulted on the first mortgage. We

hypothesized that this behavior was due to borrowers’ wishing to maintain the line of credit. The

objective of this section is to investigate whether defaulted borrowers were able to maintain access to

Note that the number of observations for cards and auto is slightly smaller than that for first and second

mortgages because some people do not have credit cards and/or auto loans.

their HELOC lines after they had defaulted on their first mortgage. In other words, does bank

management either cut a borrower’s line of credit or curtail access to the unused HELOC line once the

borrower has defaulted on the first mortgage? Based on the same data used in the previous section,

Table 6 reports the changes in HELOC lines and the HELOC utilization up to three quarters following first

mortgage default.

HELOC Credit Line Limit: Most of the HELOC lines were not increased or decreased after the

borrowers defaulted on their first mortgages. About 90 percent of the lines remain unchanged even

after three quarters following first mortgage default. It appears that bank managers infrequently reduce

HELOC lines in response to a borrower’s default on a first mortgage. Interestingly, a small percentage (3

to 6 percent) of these borrowers had their HELOC lines increased (rather than decreased). For those few

borrowers whose HELOC line was increased, the average dollar amount of the HELOC line was raised by

about 20 percent; specifically, 21 percent, 17 percent, and 23 percent increased in the first, second, and

third quarter after the borrowers became 60 DPD on their first mortgages, respectively. And for those

few whose HELOC lines were reduced, the dollar amount of their HELOC line was reduced by 30 percent,

28 percent, and 24 percent in the first, second, and third quarter following default on their first

mortgages, respectively. These statistics for 90 DPD on first mortgages are reported in Panel B of Table

6, with similar results.

HELOC Line Utilization: We now focus on those borrowers whose HELOC lines were unchanged

(not increased or decreased), which account for at least 90 percent of the population. Do bank

managers restrict access to these lines of credit for borrowers who defaulted on their first mortgages?

If not, do borrowers quickly ramp up use of their HELOC line? We find that the average utilization ratio

for these borrowers is about 90 percent at the time of first mortgage default, and the ratio does not

change very much even three quarters later. In terms of the percentage of borrowers who increase or

decrease their utilization rates, we find that a substantial number (20 to 30 percent) of HELOC

borrowers continue to raise their utilization rates after having defaulted on their first mortgage. This

suggests that a significant number of banks do not cut off access to lines for borrowers who have

defaulted on their first mortgages. This may be due to the lack of timely information (e.g., updated risk

score) or poor risk management practice.

The data suggest heterogeneous behavior among borrowers. Approximately 27 percent of the

borrowers increased their HELOC utilization ratio one quarter after being delinquent (60 DPD), followed

by 23 and 24 percent of the remaining population increasing their HELOC utilization ratio in the second

and third quarter, respectively. The increase in the dollar amount of HELOC utilization is, however, quite

small, just under 4 percent on average. A slightly larger number of borrowers (29 percent to 34 percent)

decreased their HELOC utilization ratio in the quarters following first mortgage default. The rest (about

40 percent) of the borrowers whose HELOC lines were unchanged kept their utilization ratio constant at

around 91 percent to 92 percent. We find similar results for the alternative default definition (90 DPD),

as presented in Panel B.

V. Conclusions and Policy Implications

Strategic default behavior suggests that the default process is not only a matter of inability to

pay. Consumers make economic decisions that can affect the timing of defaults and which loans they

repay or do not repay. Our analysis of first and second lien mortgage default behavior is consistent with

strategic default behavior by some borrowers. In particular, in addition to the negative equity factor,

the availability of open lines of credit seems to be an important factor in second lien default behavior.

Interestingly, there is little evidence that many borrowers have decided to strategically default

on second liens while maintaining payments on first mortgages. Instead, our results indicate a

significant declining trend (for 2008-2009) for defaulting on the second lien while keeping the first lien

current, controlling for risk characteristics of the borrowers and loan types.

We also find that negative equity, proxied by LTV and/or CLTV exceeding 90 percent, has been

the primary reason for homeowners to default on their mortgages overall. Negative equity is a

necessary but not sufficient condition for strategic mortgage default. While some of these homeowners

default on both first mortgages and second lien home equity lines, a large portion of the delinquent

borrowers actually keep their second lien current. This behavior is generally more common with people

who have HELOCs (rather than HELOANs) and is more common when there is a larger unused line of

credit. These second liens that are current, but behind a seriously delinquent first mortgage, are subject

to a high risk of default if the default on the first mortgage results in a foreclosure.

Our results overall suggest that people default strategically as their home value falls below the

mortgage value; they exercise the put option to default on their first mortgage. However, they tend to

keep their HELOCs current in order to maintain the credit line available to them, particularly for those

who have already used their credit card lines. Credit quality as reflected in the types of mortgages

(prime, alt-A, or subprime) does not seem to play a significant role in determining this behavior. In

addition, we find that loan modifications may increase borrowers’ incentives to default on their first

mortgage while remaining current on their second mortgage. Overall, our empirical findings provide a

better understanding of consumer strategic default behavior and implies that current loan modification

programs may have unintended consequences for consumer behavior.

References

Archer, W., P. Elmer, D. Harrison, and D. Ling (2002) “Determinants of Multifamily Mortgage Default,”

Real Estate Economics 30, 445-473.

Bajari, P., C.S. Chu, and M. Park (2008) “An Empirical Model of Subprime Mortgage Default From 2000

to 2007,” NBER Working Paper #14625, December.

Crawford, G. and E. Rosenblatt (1995) “Efficient Mortgage Default Option Exercise: Evidence from Loss

Severity,” Journal of Real Estate Research, Volume 10, Number 5, 543-555.

Cunningham, D. and C. Capone (1990) “The Relative Termination Experience of Adjustable to Fixed-Rate

Mortgages,” Journal of Finance 45, Number 5, 1687-1703.

Deng, Y., J.M. Quigley, and R. Van Order (2000) “Mortgage Termination, Heterogeneity, and the

Exercise of Mortgage Options,” Econometrica 2, 275-307.

Downing, C., R. Stanton, and N. Wallace (2005) “An Empirical Test of a Two-Factor Mortgage Valuation

Model: How Much Do House Prices Matter?” Real Estate Economics, Volume 33, Number 3.

Edmans, A. (2010) “The Responsible Homeowner Reward: An Incentive-Based Solution to Strategic

Mortgage Default,” The Wharton School, University of Pennsylvania, Working Paper, July.

Elul, R. (2009) “Securitization and Mortgage Default: Reputation vs. Adverse Selection,” Federal

Reserve bank of Philadelphia, Working Paper #09-21, September.

Elul, R., N. Souleles, S. Chomsisengphet, D. Glennon, and R. Hunt (2010) “What ‘Triggers’ Mortgage

Default,” Federal Reserve Bank of Philadelphia, Working paper No. 10-13, April.

Epperson, J., J. Kau, D. Keenan, and W. Muller (1985) “Pricing Default Risk in Mortgages,” AREUEA

Journal 13, Number 3, 152-167.

Foote, C., K, Gerardi, L. Goette, and P. Willen (2008) “Negative Equity and Foreclosure: Theory and

Evidence,” Journal of Urban Economics 64, Number 2, 234-245.

Foster, C. and R. Van Order (1984) “An Option Based Model of Mortgage Default,” Housing and

Finance Review 3, Number 4, 351-372.

Goodman, L., R. Ashworth, B. Landy, and K. Yin (2010) “Second Liens: How Important?” The Journal of

Fixed Income 20, Number 2, Fall, 19-30.

Guiso, L., P. Sapienza, and L. Zingales (2009) “Moral and Social Constraints to Strategic Default on

Mortgages,” University of Chicago and Northwestern University, Working Paper, July.

Henderson, C. and J. Jagtiani (2010) “Can Banks Circumvent Minimum Capital Requirements? The Case

of Mortgage Portfolios Under Basel II,” Federal Reserve Bank of Philadelphia, Working paper # 10-17,

May.

Herzog, J.P. and J.S. Earley (1970) “Home Mortgage Delinquency and Foreclosure,” NBER Working

Paper.

Jackson, J. and D. Kesserman (1980) “Default Risk on Home Mortgage Loans: A Test of Competing

Hypotheses,” Journal of Risk and Insurance 3, Number 3, 678-690.

Johnson, K.W. and G. Li (2010) “The Debt-Payment-to-Income Ratio as an Indicator of Borrowing

Constraints: Evidence from Two Household Surveys,” Journal of Money, Credit, and Banking 42, Number

7, October, 1373-1390.

Krainer, J., S. LeRoy, and O. Munpyung (2009) “Mortgage Default and Mortgage Valuation,” Federal

Reserve Bank of San Francisco, Working Paper, November.

Lee, D. and J. Tracy (2010) “Taking a First Look at Seconds,” Federal Reserve Bank of New York,

Presentation, June 10.

Mayer, C., K. Pence, and S. Sherlund (2009) “The Rise in Mortgage Defaults,” Journal of Economic

Perspectives, Volume 23, Number 1, Winter, 27-50.

Posner, E. and L. Zingales (2009) “A Loan Modification Approach to the Housing Crisis,” American Law

and Economics Review 11, 575-607.

Quercia, R. and M. Stegman (1992) “Residential Mortgage Default: A Review of the Literature,” Journal

of Housing Research, Volume 3, Number 2, 341-379.

Quigley, J.M. and R. Van Order (1991) “Defaults on Mortgage Obligations and Capital Requirements for

U.S. Savings Institutions: A Policy Perspective,” Journal of Public Economics 44, Number 3, 353-370.

Sapienza, P. and L. Zingales (2010) “Financial Trust Index: The Results - Wave VI,” University of Chicago

Booth School of Business and Northwestern University Kellogg School of Business.

Sherlund, S. (2008) “The Past, Present, and Future of Subprime Mortgages,” Finance and Economic

Discussion Series 2008-63, Federal Reserve Board.

Titman, S. and S. Tsyplakov (2010) “Originator Performance, CMBS Structures, and the Risk of

Commercial Mortgages,” The Review of Financial Studies 23, Number 9, 3558-3594.

Von Furstenberg, G. and R.J. Green (1974) “Home Mortgages Delinquency: A Cohort Analysis,” Journal

of Finance 29, December, 1545-1548.

Williams, A.O., W. Beranek, and J. Kenkel (1974) “Default Risk in Urban Mortgages: A Pittsburgh

Prototype Analysis,” AREUEA Journal 2, Number 2, 101-102.

Zorn, P. and M. Lea (1989) “Mortgage Borrower Repayment Behavior: A Microeconomic Analysis with

Canadian Adjustable Rate Mortgage Data,” AREUEA Journal 17, Number 1, 118-136.

Table 1

Rising Current LTV and Contribution of Second Liens to Current CLTV Exceeding 100%

Product

Lien Type

Original

LTV (%)

Current

LTV (%)

Current

CLTV (%)

Prime

Single Lien

Second Lien Paid Off

Simultaneous Second Lien

Single Lien with Subsequent Higher Lien

Simultaneous Second with Subsequent Higher Lien

Single Lien & Subsequent Lien Data Missing

Simultaneous Second & Subsequent Lien Data Missing

105

124

109

123

Alt A

Single Lien

Second Lien Paid Off

Simultaneous Second Lien

Single Lien with Subsequent Higher Lien

Simultaneous Second with Subsequent Higher Lien

Single Lien & Subsequent Lien Data Missing

Simultaneous Second & Subsequent Lien Data Missing

106

121

109

113

106

147

129

145

Option ARM

Single Lien

Second Lien Paid Off

Simultaneous Second Lien

Single Lien with Subsequent Higher Lien

Simultaneous Second with Subsequent Higher Lien

Single Lien & Subsequent Lien Data Missing

Simultaneous Second & Subsequent Lien Data Missing

140

129

148

127

137

129

138

140

129

169

153

165

Subprime

Single Lien

Second Lien Paid Off

Simultaneous Second Lien

Single Lien with Subsequent Higher Lien

Simultaneous Second with Subsequent Higher Lien

Single Lien & Subsequent Lien Data Missing

Simultaneous Second & Subsequent Lien Data Missing

121

116

125

112

116

106

119

121

116

155

142

157

Source: Goodman, Ashworth, Landy, and Yin (2010)

Table 2:

Default Frequency — Comparing First Lien vs. Second Lien Defaults

Date Period: 2004 to 2009

Note: Information for both first lien default and second lien default comes from the Equifax

database. Sample includes customers with only one first mortgage and at least one second lien

mortgage (either HELOC or HELOAN).

Panel A: Both With and Without Loan Modification – Total 93,198 Borrowers.

Defaulted on First Liens:

Default Defined as 90+ DPD

Default Defined as 60+ DPD

Observation

Number

2,548

33,14

Second Lien

Current

30.97%

34.76%

Second Lien

Not Current

(30+ DPD)

69.03%

65.24%

Defaulted on Second Liens:

Default Defined as 90+ DPD

Default Defined as 60+ DPD

Observation

Number

2,040

2,542

First Lien

Current

20.20%

20.26%

First Lien

Not Current

(30+ DPD)

79.80%

79.74%

Property Under Foreclosure:

Observation

Number

927

Second Lien

Current

19.96%

Second Lien

Not Current

(30+ DPD)

80.04%

Defaulted on First Liens:

Default Defined as 90+ DPD

Default Defined as 60+ DPD

Observation

Number

1,168

1,498

HELOC

Current

34.16%

37.98%

HELOC

Not Current

(30+ DPD)

65.84%

62.02%

Defaulted on First Liens:

Default Defined as 90+ DPD

Default Defined as 60+ DPD

Observation

Number

1,181

1,557

HELOAN

Current

24.39%

27.94%

HELOAN

Not Current

(30+ DPD)

75.61%

72.06%

Table 2 (Continued)

Default Frequency — Comparing First Lien vs. Second Lien Defaults

Impact of Loan Modification Programs

Data Period: 2005 to 2009

Panel B: Borrowers With Loan Modification Only (2005-2009) – Total 816 Borrowers.

Defaulted on First Liens:

Default Defined as 90+ DPD

Default Defined as 60+ DPD

Observation

Number

339

405

Second Lien

Current

41.30%

42.47%

Second Lien Not

Current

(30+ DPD)

58.70%

57.53%

Defaulted on Second Liens:

Default Defined as 90+ DPD

Default Defined as 60+ DPD

Observation

Number

183

221

First Lien

Current

3.83%

4.52%

First Lien Not

Current

(30+ DPD)

96.17%

95.48%

Property Under Foreclosure:

Observation

Number

Second Lien

Current

22.22%

Second Lien Not

Current

(30+ DPD)

77.78%

Panel C: Borrowers Without Loan Modification Only (2005-2009) – Total 82,574 Borrowers. Note

that this includes all loans with unknown modification status.

Defaulted on First Liens:

Default Defined as 90+ DPD

Default Defined as 60+ DPD

Observation

Number

2,187

2,868

Second Lien

Current

29.26%

33.37%

Second Lien Not

Current

(30+ DPD)

70.74%

66.63%

Defaulted on Second Liens:

Default Defined as 90+ DPD

Default Defined as 60+ DPD

Observation

Number

1,822

2,278

First Lien

Current

21.08%

20.98%

First Lien Not

Current

(30+ DPD)

78.92%

79.02%

Property Under Foreclosure:

Observation

Number

817

Second Lien

Current

19.22%

Second Lien Not

Current

(30+ DPD)

80.78%

Table 3: Important Factors That Determine Mortgage Defaults

Data period 2004-2009. Both first lien default and second lien default are from the Equifax database. P-values are

presented in parentheses. ***, **, and * represents significance at the 1%, 5%, and 10% level, respectively.

Full Sample

(1)

Full Sample

(2)

Borrowers With

and HELOC

(3)

Borrowers With

and HELOAN

(4)

Prob(1

Lien

90+ DPD)

Prob(1

Lien

Foreclosed)

Prob(2

HELOC 90+)

Prob(2

HELOAN 90+)

Intercept

Ln (Monthly 1

Paymt)

% 2

Bal to 1

Paymt

Ln (HELOC Line Avail)

D_AltA

D_Subprime

% Card_Utilization

Updated Risk Score

D_ELTV >90

D_ECLTV >90

D_Loan Modification

D_Jumbo 1

Mortgage

D_Option Arm 1

Mort

D_2005

D_2006

D_2007

D_2008

D_2009

2.5247***

(0.0001)

0.7657***

(0.0001)

-0.1438**

(0.0271)

-0.2071**

(0.0249)

-0.0055***

(0.0001)

-0.0207***

(0.0001)

0.8926***

(0.0001)

1.9398***

(0.0001)

-0.0229

(0.8090)

-0.5454***

(0.0001)

-0.1562

(0.5618)

0.3634

(0.1415)

0.7092***

(0.0030)

1.2094***

(0.0001)

2.1787***

(0.0001)

3.4940***

(0.0001)

0.2765***

(0.0002)

-0.0773

(0.4213)

-0.3008**

(0.0298)

-0.0059***

(0.0001)

-0.0177***

(0.0001)

0.8617***

(0.0001)

0.7829***

(0.0001)

0.3694***

(0.0055)

-0.3836***

(0.0001)

-0.4048

(0.2775)

0.5097

(0.1117)

0.7020**

(0.0242)

0.7714**

(0.0125)

1.1727***

(0.0001)

7.9713***

(0.0001)

-0.0037***

(0.0034)

-0.1238***

(0.0001)

-0.1997**

(0.0273)

-0.6416***

(0.0002)

-0.0092***

(0.0001)

-0.0197***

(0.0001)

0.5005***

(0.0001)

0.0447

(0.8234)

-0.2254

(0.5052)

0.2657

(0.3970)

0.7320**

(0.0137)

1.2026***

(0.0001)

2.0235***

(0.0001)

6.5120***

(0.0001)

-0.0083***

(0.0001)

-0.1315

(0.1919)

-0.1252

(0.3048)

-0.0057***

(0.0001)

-0.0175***

(0.0001)

0.6913***

(0.0001)

0.7953***

(0.0001)

0.0764

(0.7878)

-0.0029

(0.9911)

0.3400

(0.1892)

0.7243***

(0.0047)

1.2822***

(0.0001)

Observation (N)

Concordant

Discordant

201,824

98.6%

1.1%

201,824

97.0%

1.5%

144,955

97.5%

1.3%

47,419

96%

3.6%

Table 4: Important Factors in Keeping Second Lien Current After First Lien Is

Delinquent (90+ DPD)

Data period 2004-2009. Second liens include both HELOCs and HELOANs. Both first lien default and second lien

default are from the Equifax database. P-values are presented in parentheses. ***, **, and * represents

significance at the 1%, 5%, and 10% level, respectively.

Full Sample

Include Borrowers Who

Default on 1st Lien ONLY

Prob(2nd Lien Current,

1st Lien 90+ DPD)

(1)

Prob(2nd Lien Current)

(2)

Intercept

Ln (Monthly 1

Paymt)

% 2

Bal to 1

Paymt

Ln (HELOC Line Avail)

D_AltA

D_Subprime

% Card_Utilization

Updated Risk Score

D_ELTV >90

D_ECLTV >90

D_HELOAN

D_2005

D_2006

D_2007

D_2008

D_2009

1.1213*

(0.0683)

0.3110***

(0.0001)

-0.0052***

(0.0004)

-0.0297***

(0.0031)

-0.0079

(0.9285)

0.3510***

(0.0046)

-0.0034***

(0.0090)

-0.0146***

(0.0001)

0.3039***

(0.0003)

-0.5746***

(0.0001)

-0.0222

(0.9510)

0.2753

(0.4168)

0.4693

(0.1511)

1.2354***

(0.0001)

2.3922***

(0.0001)

-5.1114***

(0.0001)

-0.0019

(0.2272)

0.0177

(0.1841)

0.1793

(0.1132)

0.8626***

(0.0001)

0.0036***

(0.0082)

0.0109***

(0.0001)

-0.6928***

(0.0001)

-0.5088***

(0.0001)

-0.1339

(0.8074)

-0.8332*

(0.0988)

-0.9857**

(0.0427)

-0.8307*

(0.0815)

-0.4953

(0.2973)

Observation (N)

Concordant

Discordant

201,824

96.5%

2.1%

2,383

74.2%

25.5%

Table 5: Consumer Default Across Financial Products After the First Mortgage

Delinquency. Quarterly Data Period 2004:Q4 to 2010:Q2

Panel A: First Mortgage 60 Days Past Due

Mortgage

Becoming

60 DPD

+1Q

150 DPD

+2Q

240 DPD

+3Q

330 DPD

First Mortgage (N)

% Loans That Remain 60+ DPD

8406

100%

5765

79%

4145

70%

3049

63%

Second Lien (N)

% Current (For Remaining Loans)

Credit Cards (N)

% Current (For Remaining Loans)

Automobile (N)

% Current (For Remaining Loans)

8406

45%

7644

58%

5078

76%

5765

46%

5177

56%

3368

77%

4145

51%

3642

56%

2393

77%

3049

53%

2637

57%

1757

75%

Risk Score (Change From Previous

Quarter):

% Increase

% Decrease

% Unchanged

8406

5765

41%

57%

3962

54%

44%

2897

54%

43%

Panel B: First Mortgage 90 Days Past Due

Mortgage

Becoming

90 DPD

+1Q

180 DPD

+2Q

270 DPD

+3Q

360 DPD

First Mortgage (N)

% Loans That Remain 90+ DPD

6938

100%

4484

82%

3061

70%

2101

65%

Second Lien (N)

% Current (For Remaining Loans)

Card (N)

% Current (For Remaining Loans)

Auto (N)

% Current (For Remaining Loans)

6938

38%

6232

56%

4106

75%

4484

42%

3955

54%

2554

76%

3061

47%

2644

55%

1716

75%

2101

50%

1787

56%

1171

75%

Risk Score (Change From Previous

Quarter):

% Increase

% Decrease

% Unchanged

6938

4484

47%

51%

2900

56%

41%

2016

55%

41%

Table 6: HELOC Line Management and HELOC Utilization After Default on First

Mortgages -- Quarterly Data (2004:Q4 to 2010:Q2)

Panel A: First Mortgages 60 Days Past Due

Mortgage

Becoming

60 DPD

+1Q

150 DPD

+2Q

240 DPD

+3Q

330 DPD

% Loans That Remain 60+ DPD

8406

100%

5765

79%

4145

70%

3049

63%

HELOC Line:

% Increase

% Decrease

% Unchanged

4772

3320

-4%

92%

2322

-5%

90%

1688

-4%

92%

HELOC Line:

% $ Increase

% $ Decrease

4772

3320

21%

-30%

2322

17%

-28%

1688

23%

-24%

HELOC Line UNCHANGED (N):

Average Utilization Ratio

% Utilization Up

% Utilization Down

% $ Increased (Utilization Up)

% $ Decreased (Utilization Down)

4772

90%

3066

91%

27%

-29%

2.6%

-3.6%

2085

89%

23%

-34%

2.7%

-2.9%

1558

87%

24%

-33%

3.9%

-4.3%

Panel B: First Mortgages 90 Days Past Due

Mortgage

Becoming

90 DPD

+1Q

180 DPD

+2Q

270 DPD

+3Q

360 DPD

% Loans That Remain 90+ DPD

6938

100%

4484

82%

3061

70%

2101

65%

HELOC Line:

% Increase

% Decrease

% Unchanged

3947

2617

-6%

90%

1725

-6%

89%

1203

-4%

91%

HELOC Line:

% $ Increase

% $ Decrease

3947

2617

14%

-28%

1725

18%

-26%

1203

25%

-34%

HELOC Line UNCHANGED (N):

Average Utilization Ratio

% Utilization Up

% Utilization Down

% $ Increased (Utilization Up)

% $ Decreased (Utilization Down)

3947

91%

2347

90%

26%

-28%

2.6%

-4.2%

1532

89%

21%

-32%

4.2%

-4.1%

1099

88%

23%

-32%

3.2%

-2.5%

0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%

7.00%

2004

2005

2006

2007

2008

2009

Figure 1: Default Rate Across Financial Products

Default Defined as 90+ Days Past Due

Auto 90 days+

2nd Lien 90 days+

1st Lien 90 days

1st Lien 90 days+ (McDash)

Card 90 days +

0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%

2006

2007

2008

2009

Figure 2: Second Lien Default (90+ DPD)

HELOAN vs. HELOC

HELoan

HELOC