Subprime Mortgage Crisis Introduction
The subprime mortgage crisis of 2007 was characterized by an unusually large fraction of subprime mortgages originated in 2006 being delinquent or in foreclosure only months later. The crisis spurred massive media attention; many different explanations of the crisis have been suggested. The goal of this paper is to answer the question: "What do the data tell us about the possible causes of the crisis?" To this end we use a loanlevel database containing information on about half of all U.S. subprime mortgages originated between 2001 and 2006.
The relatively poor performance of vintage 2006 loans is illustrated in Figure 1. At every mortgage loan age, loans originated in 2006 show a higher delinquency rate (left panel) and a higher foreclosure rate (right panel) than loans originated in earlier years at the same ages. Note that 2001 was a fairly bad vintage year as well, ranking second, both in terms of the delinquency and the foreclosure rates.
Figure 1: Actual Delinquency and Foreclosure Rate
The figure shows the age pattern in actual delinquency and foreclosure rates for the different vintage years. Delinquency is defined as being 60 days or more late with the monthly mortgage payment, in foreclosure, or realestate owned. Foreclosure is defined as being in foreclosure or realestate owned. Once a foreclosure procedure for a loan is finalized and/or the loan balance becomes zero, this loan is dropped from the analysis.
Actual Delinquency Rate (%)
Actual Foreclosure Rate (%)
181614121086420
2006 2005 2004 2003 2002 2001
Actual Delinquency Rate (%)
181614121086420
2006 2005 2004 2003 2002 2001
12 108642 01
2006 2005 2004 2003 2002 2001
Actual Foreclosure Rate (%)
12 108642 01
We document that the poor performance of the vintage 2006 loans was not confined to a particular segment of the subprime mortgage market. For example, fixedrate, adjustablerate, purchasemoney, cashout refinancing, lowdocumentation, and fulldocumentation loans originated in 2006 all showed substantially higher delinquency and foreclosure rates than loans made the prior five years. This contradicts a widely held belief that the subprime mortgage crisis was mostly confined to adjustablerate or lowdocumentation mortgages.
We explore to what extent the subprime mortgage crisis can be attributed to different loan characteristics, borrower characteristics, and subsequent house price appreciation. The subsequent house price appreciation is measured as the MSAlevel house price change between the period of origination and the period of loan performance evaluation. For the empirical analysis, we run logit regressions with the probability of either delinquency or foreclosure being a function of these factors.
We find that loan and borrower characteristics are very important in terms of explaining the crosssection of loan performance. However, because these characteristics were not sufficiently different in 2006 compared with the prior five years, they cannot explain the unusually weak performance of vintage 2006 loans. For example, a onestandarddeviation increase in the debttoincome ratio raises the probability of delinquency 12 months after origination by as much as 0.73 percentage points. However, because the average debttoincome ratio was only 0.15 standard deviations higher in 2006 than its level in previous years, it contributes very little to explain the inferior performance of vintage 2006 loans. The only variable in the considered logit regression model that contributed substantially to the crisis is the low subsequent house price appreciation for vintage 2006 loans, which can explain about a 1.1 percentage points higherthanaverage delinquency rate 12 months after origination.1 Due to geographical heterogeneity in house price changes, some areas have experienced largerthanaverage house price declines and therefore have a larger explained increase in delinquency and foreclosure rates.2
We analyze the quality of loans based on their performance, adjusted for differences in observed loan characteristics, borrower characteristics, and subsequent house price appreciation. For the analysis, we compute the prediction error as the difference between the actual delinquency or foreclosure rate and the estimated probability of delinquency or foreclosure based on the logit regression model. In Figure 2 we plot the adjusted delinquency (left panel) and adjusted foreclosure (right panel) rates, which are obtained by adding up the prediction errors and the weighted average actual rates. This ensures having the same weighted average for the actual (Figure 1) and adjusted (Figure 2) delinquency and foreclosure rates.
As shown in Figure 2, adjusted delinquency and foreclosure rates have been steadily rising for the past six years, with no particularly large jump from 2005 to 2006. In other words, loan quality—adjusted for
1 Other papers that research the relationship between house prices and mortgage financing include Genesove and Mayer (1997), Genesove and Mayer (2001), and Brunnermeier and Julliard (2007).
2Also, house price appreciation may differ in cities versus rural areas. See for example Glaeser and Gyourko (2005) and Gyourko and Sinai (2006).
observed characteristics and subsequent house price appreciation—deteriorated monotonically between 2001 and 2006. Interestingly, 2001 was among the worst vintage years in terms of actual delinquency and foreclosure rates, but is in fact the best vintage year in terms of the adjusted rates. High interest rates, low average FICO credit scores, and low house price appreciation created the "perfect storm" in 2001, resulting in a high actual delinquency rate; after adjusting for these unfavorable circumstances, however, the adjusted delinquency rates are low.
Figure 2: Adjusted Delinquency and Foreclosure Rate
The figure shows the age pattern in the delinquency rate (left panel) and foreclosure rate (right panel) for the different vintages, after adjusting for variation in FICO scores, loantovalue ratios, debttoincome ratios, missing debttoincome ratio dummies, cashout refinancing dummies, owneroccupation dummies, documentation levels, percentage of loans with prepayment penalties, mortgage rates, margins, house price appreciation since origination, composition of mortgage contract types, and origination amounts.
Adjusted Delinquency Rate (%)
Adjusted Foreclosure Rate (%)
Adjusted Delinquency Rate (%)
20 22 24
876 54321
Adjusted Foreclosure Rate (%)
876 54321
20 22 24
In addition to the monotonie deterioration of loan quality, we show that over time the average combined loantovalue ratio increased, the fraction of low documentation loans increased, and the subprimeprime rate spread decreased. The rapid rise and subsequent fall of the subprime mortgage market is therefore reminiscent of a classic lending boombust scenario.3 The origin of the subprime lending boom has often been attributed to the increased demand for socalled privatelabel mortgagebacked securities (MBSs) by both domestic and foreign investors. Our database does not allow us to directly test this hypothesis,
3Berger and Udell (2004) discuss the empirical stylized fact that during a monetary expansion lending volume typically increases and underwriting standards loosen. Loan performance is the worst for those loans underwritten toward the end of the cycle. DemirgucKunt and Detragiache (2002) and Gourinchas, Valdes, and Landerretche (2001) find that lending booms raise the probability of a banking crisis. Dell'Ariccia and Marquez (2006) show in a theoretical model that a change in information asymmetry across banks might cause a lending boom that features lower standards and lower profits. Ruckes (2004) shows that low screening activity may lead to intense price competition and lower standards.
but an increase in demand for subprime MBSs is consistent with our finding of lower spreads and higher volume. Mian and Sufi (2008) find evidence consistent with this view that increased demand for MBSs spurred the lending boom.
The logit regression specification used to compute the adjusted delinquency and foreclosure rates assumes that the regression coefficients on the different explanatory variables remain constant over time. We test the validity of this assumption for all variables and find that it was the most strongly rejected for the loantovalue (LTV) ratio. HighLTV borrowers in 2006 were riskier than those in 2001 in terms of the probability of delinquency or foreclosure, for given values of the other explanatory variables. In fact, the increases in the adjusted delinquency and foreclosure rates are almost exclusively caused by the worsening performance of loans with a combined LTV of 80 percent or more.
Were securitizers aware of the increasing riskiness of highLTV borrowers?4 To answer this question, we analyze the relationship between the mortgage rate and LTV ratio (along with the other loan and borrower characteristics). We perform a crosssectional ordinary least squares (OLS) regression, with the mortgage rate as the dependent variable, for each quarter from 2001Q1 to 2007Q2 for both fixedrate mortgages and 2/28 hybrid mortgages. Figure 3 shows that the coefficient on the firstlien LTV variable, scaled by the standard deviation of the firstlien LTV ratio, has been increasing over time. We thus find evidence that securitizers were aware of the increasing riskiness of highLTV borrowers, and adjusted mortgage rates accordingly.
We show that our main results are robust when allowing for interaction effects between different loan and borrower characteristics. This includes taking into account risklayering—the origination of loans that are risky in several dimensions, such as the combination of a high LTV ratio and a low FICO score. As an extension, we estimate our regression model using data just through yearend 2005 and again obtain the continual deterioration of loan quality since 2001. This means that the seeds for the crisis were sown long before 2007, but detecting them was complicated by high house price appreciation between 2003 and 2005—appreciation that masked the true riskiness of subprime mortgages. We also show that our results are robust to applying a different method for dealing with loan terminations (prepayments and defaults).
There is a large literature on the determinants of mortgage delinquencies and foreclosures, dating back to at least Von Furstenberg and Green (1974). Recent contributions include Cutts and Van Order
4For loans that are securitized (as are all loans in our database), the securitizer effectively dictates the mortgage rate charged by the originator.
Figure 3: Sensitivity of Mortgage Rate to FirstLien LoantoValue Ratio
The figure shows the effect of the firstlien loantovalue ratio on the mortgage rate for firstlien fixedrate and 2/28 hybrid mortgages. The effect is measured as the regression coefficient on the firstlien loantovalue ratio (scaled by the standard deviation) in an ordinary least squares regression with the mortgage rate as the dependent variable and the FICO score, firstlien loantovalue ratio, secondlien loantovalue ratio, debttoincome ratio, missing debttoincome ratio dummy, cashout refinancing dummy, owneroccupation dummy, prepayment penalty dummy, origination amount, term of the mortgage, prepayment term, and margin (only applicable to 2/28 hybrid) as independent variables. Each point corresponds to a separate regression, with a minimum of 13,281 observations.
(2005) and PenningtonCross and Chomsisengphet (2007).5 Our paper makes several novel contributions to this literature. First, we quantify how much different determinants have contributed to the observed high delinquency and foreclosure rates for vintage 2006 loans. Our data enables us to show that the effect of different loanlevel characteristics as well as low house price appreciation was quantitatively too small to explain the bad performance of 2006 loans. Second, we uncover a downward trend in loan quality, determined as loan performance adjusted for differences in loan and borrower characteristics as well as subsequent house price appreciation. We further show that there was a deterioration of lending standards and a decrease in the subprimeprime mortgage rate spread during the 20012006 period. Together these results provide evidence that the rise and fall of the subprime mortgage market follows a classic lending boombust scenario, in which unsustainable growth leads to the collapse of the market. Third, we show that continual deterioration of loan quality could have been detected long before the crisis by means of a simple statistical exercise. Fourth, securitizers were, to some extent, aware of this deterioration over time, as evidenced by changing determinants of mortgage rates.
5Deng, Quigley, and Van Order (2000) discuss the simultaneity of the mortgage prepayment and default option. Campbell and Cocco (2003) and Van Hemert (2007) discuss mortgage choice over the life cycle.
The structure of this paper is as follows. In Section 2 we show the descriptive statistics for the subprime mortgages in our database. In Section 3 we present the econometric results and discuss explanatory factors for delinquency and foreclosure. In Section 4 we discuss the increasing riskiness of highLTV borrowers, and the extent to which securitizers were aware of this risk. In Section 5 we analyze the subprimeprime rate spread and in Section 6 we provide robustness checks. In Section 7 we conclude.
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