Abstract
This paper develops and estimates an instrumental variables strategy for identifying the causal effect of securitization on the incidence of mortgage modification and foreclosure based on the early payment default analysis performed by Piskorsi et al. (J Financ Econ 97:360–397, 2010). Estimation results show that securitized mortgages are more likely to be modified and less likely to be foreclosed on by servicers. These results are consistent with the interpretation in Adelino et al. (2009) that low modification rates are not the result of contract frictions inherent in the mortgage securitization process.
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Notes
Adelino et al. (2009) argue that until heavy government involvement in mortgage servicing in the fall of 2008, securitization had little or no effect on the likelihood of a modification.
Although prior research has portrayed this as a problem of moral hazard (for example Keys et al. (2010) and Mian and Sufi (2009)), strictly speaking, there is no moral hazard problem in underwriting loans. Since the lender has private information either about the quality of the loan or the effort expended in underwriting prior to contracting, adverse selection is the only potential problem.
The LPS dataset does not contain direct information on modifications. That is the servicers that provide the data on loan performance do not disclose whether they have given a mortgage borrower a modification.
A nice illustration of this issue can be seen in the comparison of judicial and power-of-sale foreclosure states. At any given point in time, there are large differences in foreclosure rates between the two types of states (Gerardi et al. 2013). However, Gerardi et al. (2013) find no differences in modification rates between the two states, and find that the gaps in foreclosure rates between the two types of states close over time, so that cumulative foreclosure rates over a period of several years are roughly comparable. If the PSV interpretation of differences in foreclosure rates is applied to this context, one would wrongly conclude that there are significant differences in the likelihood of renegotiation between the two types of states.
It is important to note that mortgage servicers and lenders have other options besides foreclosure and modification when it comes to dealing with delinquent mortgage borrowers. For example, a lender could agree to a short-sale or a deed-in-lieu of foreclosure with a delinquent borrower, which would force the borrower to move out of the property, but would avoid the lengthy delays that typically characterize foreclosure proceedings. While there is anecdotal evidence that short-sales have become more prevalent since the beginning of the foreclosure crisis, there is little empirical evidence on these the prevalence of these loss mitigation alternatives, and no evidence, to our knowledge, on whether there are important differences in the frequency of these alternatives across securitized and portfolio mortgages.
There are two types of early payment default (EPD) clauses, and it is important to distinguish between the two. EPD clauses were written into many of the loan sale agreements between mortgage originators and issuers of mortgage-backed-securities (MBS). In addition, EPD clauses were written into a small fraction of the Pooling and Servicing Agreements (PSAs) that govern the relationship between the issuer, servicer, and investors of MBS. An EPD clause in a loan sale agreement would require that the mortgage originator repurchase loans from the issuer if specific performance criteria were violated. On the other hand, an EPD clause in a PSA would require the issuer (or sponsor) of the securitization deal to buy back mortgages that became delinquent shortly after being securitized at the request of the investors. Although PSV refer throughout their paper to repurchased loans in the context of the relationship between the originator and the issuer, their analysis is concerned with the latter EPD clauses (those in PSAs) as they are the only EPD clause repurchases that are possible to identify in the LPS data. We will also refer to this type of EPD clause throughout our discussion.
PSV acknowledge in their paper that there is variation across deals in the exact timing of the EPD clauses (p. 383).
PSV find that the observable characteristics of mortgages in deals with EPD clauses are distinct at origination to those in deals that do not have such clauses (page 387), but that they have similar interest rates. While interest rates may in principle be a summary statistic for the riskiness of a loan (as PSV argue), the interest rate variable in this dataset is a very noisy measure of the true cost of a mortgage. So, even on observable characteristics, there seem to be differences between the two types of deals.
The LPS loan-level dataset covers approximately 40 million active first lien mortgages and 8 million active second lien mortgages.
For details on the specifics of the modification algorithm and it’s precision, see Adelino et al. (2009).
To define the securitization dummy, we use the reported securitization status of a loan at the end of the 12-month horizon for loans that survive for the entire horizon, and for loans that do not survive for the entire horizon, we use the securitization status of the loan in the last month that it was active.
In addition to controlling for the loan characteristics listed in Table 2, we also include year of origination fixed effects, MSA fixed effects, and quarter of serious delinquency fixed effects.
Note that in the context of a binary dependent variable and a binary endogenous regressor, the 2-stage probit, or IV Probit model as it is often called, yields inconsistent estimates.
We also estimated a simple probit model that does not address the potential endogeneity of the securitization decision for both foreclosure and modification outcomes. In both cases the marginal effects were the same sign and very similar in magnitude to the OLS results reported in columns (1)–(3) in Tables 3 and 4.
We used Stata code from Richard Chiburis’s website that was used in Chiburis et al. (2011) to estimate the ATEs for the bivariate probit model, and obtained standard errors via bootstrapping.
Our sample is made up of borrowers that miss a payment within 6 months of securitization. Since we only keep mortgages that are securitized within 3 months of origination, this implies that our sample is made up of borrowers that missed a payment within 9 months of origination.
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Acknowledgments
We thank Chris Cunningham, Chris Foote, Sam Kruger, and an anonymous referee for thoughtful comments.
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Adelino, M., Gerardi, K. & Willen, P. Identifying the Effect of Securitization on Foreclosure and Modification Rates Using Early Payment Defaults. J Real Estate Finan Econ 49, 352–378 (2014). https://doi.org/10.1007/s11146-013-9433-0
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DOI: https://doi.org/10.1007/s11146-013-9433-0