Abstract
In many U.S. states, the law firms that represent lenders in foreclosure proceedings must hire auctioneers to carry out the foreclosure auctions. We empirically test whether processing times differ for law firms that integrate the mortgage foreclosure auction process compared with law firms that contract with independent auction companies. We find that independent firms are able initially to schedule auctions more quickly; however, when postponements occur, they are no faster to adapt. Since firms schedule the initial auction before contracting, independent auction companies have an incentive to conform to the law firms’ schedules in order to secure the contracts. We argue that this is evidence of a cost of integration that stems from poorly aligned incentives within the firm.
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Notes
See Lafontaine and Slade (2007) for a review of the make-or-buy literature. Notably, Baker and Hubbard (2003, 2004) and Woodruff (2002) also find support for the property rights argument. Forbes and Lederman (2009, 2010) also test whether integrated firms are better able to adapt, but they find that integrated firms do perform better than do independent firms in the airline industry.
We thank the numerous foreclosure attorneys and auctioneers in the Boston area who generously volunteered their time to explain to us the intricacies of the foreclosure process and scheduling procedures. We rely heavily on these discussions to supplement the information that is contained in Massachusetts General Law, Chapter 244: Foreclosure and Redemption of Mortgages.
Different from the mortgage holder, the servicer is an agent of the mortgage holder or group of investors who own mortgage-backed securities.
During much of our study period, Massachusetts required lenders to wait 90 days between sending the notice of default and accelerating payments for most borrowers.
Despite the presence of the courts in this process, this is different from judicial foreclosure, in which the court reviews the default itself.
Following various legal and public relations events, postponements have become more common. Rarely, attorney-driven postponements occur, such as when auctions are found to have been inadequately advertised.
Properties that are bought at foreclosure auctions sell at a discount partly due to the risk that buyers take on by purchasing a property as-is with no formal inspection; consequently, if the lender’s reservation price is at or above the perceived market value, a sale is extremely unlikely (Lambie-Hanson et al. 2015).
Our understanding of which party has control over scheduling is based on interviews with industry professionals. So, while we are confident that we are representing the typical practices, the precise scheduling procedures of any particular firm may differ, and some measurement error may then enter our data.
To our knowledge, no bonuses or other added compensation for prompt scheduling were offered to auctioneers in Massachusetts during our study period.
For 31 states, including Massachusetts, Fannie Mae also maintained a “Retained Attorney List” for the time period that is covered by our data, which was a list of attorneys who were eligible to receive referrals for foreclosures or bankruptcies relating to Fannie Mae loans. See Fannie Mae Announcement 08-19, at www.efanniemae.com/sf/guides/ssg/annltrs/pdf/2008/0819 (last accessed 8/18/2015) for more details on the payment schedule for and responsibilities of the law firms that processed Fannie Mae foreclosures, as well as for which states a “Retained Attorney List” was maintained.
The law firm initially pays the auctioneer’s fees and other expenses, to be reimbursed by the servicer after the foreclosure deed is filed (which is commonly three to 9 months after the auctioneer is compensated). Law firms compensate auctioneers if an auction is postponed or cancelled (at a lower rate). Since auctions are often postponed, occasionally in excess of five or six times, these fees may end up being significant.
Our results on the impact of integration on auction scheduling are robust to classifying exclusively contracted and in-house auctioneers separately.
Processing errors can include a variety of issues, such as failure to properly advertise a foreclosure sale, which can stall or invalidate a foreclosure.
Anecdotally, some auctioneers suggested that the per-foreclosure pay is lower for some in-house auction companies. We have no wage data to support this claim, but it is plausible that law firms could better guarantee auctions to conduct in exchange for lower per-foreclosure rates (compared to independent auction companies).
The initial sample of 5200 foreclosures includes numerous other types of properties, such as parking spaces, time shares, and commercial real estate. We exclude these from our analysis. Our sample includes the vast majority of residential parcels in the county and excludes just apartment buildings of four or more units. Since 2000, there have been only about 100 foreclosures on those types of properties.
Complaint information is not available for some cases because they are exempt from the military servicemember protection process, such as if the borrower is a corporation, rather than an individual.
See Masten (1993) for a thorough discussion of the pitfalls of estimating the impact of integration on performance.
Both of these measures are calculated using our data set of Suffolk County foreclosures. Because we observe GSE involvement only when properties are bought back by the mortgage holders at foreclosure auction, these calculations are based on the 89 % of our sample that experience a buyback.
The null hypothesis of the Sargan–Hansen test is that the instruments are valid. Essentially, it tests whether one of the instrumental variables is correlated with the residuals after estimating the equation using the other instrument. For our main model, the p value is 0.2122, so we do not reject this null hypothesis.
In Table 6 we display the models separately by time period. An alternative approach is to pool the auctions in one model and interact the auction time period with integration status. When doing so, we find that these interaction terms are statistically indistinguishable from each other and from zero (p = 0.52), which leads us to conclude that the effect of integration does not materially differ over our sample period. Finally, while our main specifications control for the year that the auction occurs, our results are very similar when we instead control for the month or quarter of the auction. These results are available upon request.
We also test the robustness of our results by redefining “integrated” as having in-house auctioneers only and pooling exclusively contracted auctioneers with independent ones, in case we misunderstand the incentives of the exclusively contracted auctioneers. (Neither our institutional understanding nor the data suggest that this is the case, however). When we pool all independent auctioneers together, our main result is still statistically significant at the 1 % level, with in-house auctioneers taking, on average, 45 days longer compared to all independent auctioneers (full results are available upon request).
Capozza and Thomson (2006) find that the time period from delinquency to foreclosure auction is four times longer for subprime than for prime borrowers. Our results are much smaller, but we do not include the pre-foreclosure time period (the time period when borrowers have begun to miss payments, but the servicer has not yet begun foreclosure proceedings) in our timeline. Also, Capozza and Thomson (2006) study loans in 2001, and it is unclear if their finding applies to the recent mortgage crisis.
See Ackerberg and Botticini (2002) for a discussion of how unobserved principle and agent characteristics may affect estimated coefficients if incentives exist for particular types of agents to contract with particular types of principles.
There are also industry-specific nuances at play. The broad geographic scope of a typical auctioneer’s business means that the scheduling of his auctions is not standardized. An auctioneer may rarely visit Nantucket to conduct auctions, for example, and this makes his scheduling constraints less transparent to the law firm.
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Acknowledgments
We thank the Boston-area auctioneers and foreclosure attorneys who helped us gain a better understanding of the mortgage foreclosure process in Massachusetts. We also thank Darlene Chisholm for helpful suggestions and guidance throughout the completion of this project, and we thank the editor for his many thoughtful comments. Our work also greatly benefited from conversations with Haldun Evrenk and Paul Willen.
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Lambie-Hanson, L., Lambie-Hanson, T. Agency and Incentives: Vertical Integration in the Mortgage Foreclosure Industry. Rev Ind Organ 51, 1–24 (2017). https://doi.org/10.1007/s11151-016-9538-8
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DOI: https://doi.org/10.1007/s11151-016-9538-8