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The Journal of Real Estate Finance and Economics

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09-08-2020

Mortgage Losses under Alternative Property Disposition Approaches: Deed-in-Lieu, Short Sales, and Foreclosure Sales

Authors: Arnab Biswas, Hamilton Fout, Anthony Pennington-Cross

Published in: The Journal of Real Estate Finance and Economics | Issue 3/2023

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Abstract

The loss on a distressed mortgage depends not only on economic and financial conditions but also on the value of the property and how it is transferred to a new owner. Using data from Fannie Mae, we investigate the differences in loss experience across alternative mechanisms for disposing of property (real estate owned or REO, deed in lieu, short sales, and foreclosure sales) from 2003 through 2017. In general, losses are lowest for short sales and foreclosure sales. But these lower losses depend on the overall distress level of the market. The more distressed the market is, the smaller the relative gains associated with these alternative approaches, as compared to traditional REO sales. In contrast, in markets with rapidly increasing distress short sales have lower losses relative to traditional REO sales. We use a variety of matching techniques to address selection issues associated with REO properties and find that the lower loss severities associated with non-REO sales remain.

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On June 16th, 2016, the Financial Accounting Standards Board (FASB) issued the Current Expected Credit Loss (CECL) impairment standard, which changes the calculation of the Allowance for Loan and Lease Losses (ALLL). These new rules were scheduled to take effect for all banks in 2022 and Security Exchange Commission (SEC) registrants in 2020. In March of 2020, FASB delayed the implementation of the CECL standard by 2 years and included a 3-year phase in of any capital requirements.

In this discussion, we use the term lender generally to refer to the credit guarantor of the loan.

A deficiency judgement is a court ruling that a borrower must cover the shortfall when property sale proceeds do not cover the outstanding debt. Deficiency judgements are typically only available in recourse states (see Ghent and Kudylak 2011 for more details).

Foreclosure laws vary by state. In judicial foreclosure states, lenders have to initiate legal action through the court system, while in non-judicial states, lenders do not have to use the court system to foreclose. See Mian, Sufi and Trebbi (2015) for more details.

For traditional REO and DIL-REO sales, we refer to this date as the disposition date; for foreclosure and short sales, it is referred to as the liquidation date.

Foreclosure timeline related property taxes (or HOA fees) are calculated as

property taxes (or HOA) *fcl_months/(fcl_months+disp_months), where fcl_months measures the number of months between the last paid installment date and the liquidation date, and disp_months represents the number of months between the liquidation date and the final property disposition date.

For market mortgage rates we use the 30-year fixed mortgage rate for 30-year, 25-year, and 40-year fixed mortgages. We use the 15-year fixed mortgage rate for 15-year, and 20-year fixed mortgages. We use the 5/1 adjustable rate mortgage (ARM) rate for 3/1, 5/1, 7/1, and 10/1 ARMs.

For traditional REO and DIL-REO sales, the holding period is calculated as the difference between last payment date and (REO) disposition date.

Disposition related property taxes (or HOA fees) is calculated as

property taxes (or HOA fees) *disp_months/(fcl_months +disp_months). However, this formula does not apply to either foreclosure sales or short sales.

Idiosyncratic determinants of losses such as issues like foreclosure moratoria, robo-signing scandals, and new servicing rules that may increase the liquidation time (Cordell and Lambie-Hansen, 2016; An and Cordell, 2019).

The spike in the distribution for negative loss rates (e.g. gains) is due to the category including all negative loss rates.

While our sample is based on Fannie loan data, other sources show a similar pattern for the broader industry. For example, Zhang (2019) presents evidence of a relative decline in the REO share of distressed sales and a relative increase in the short sale share of distressed sales from 2009 to 2014 using a comprehensive set of property transactions.

For more details on PSM, see for instance Ho et al. (2007); Iacus, King, and Porro (2011) or Imai, King, and Stuart (2007).

Mahalanobis distance between covariates for unit i and unit j is defined as:

$$ M\left({X}_i,{X}_j\right)=\sqrt{{\left({X}_i-{X}_j\right)}^T{S}^{-1}\left({X}_i-{X}_j\right)}, $$

where X_i, X_j = vectors of pre-treatment covariates for unit i and unit j, respectively, and S is the covariance matrix between X_i and X_j.

We use the ratio of Fannie’s REO properties over all properties in a particular state for the measure of distress. We include this measure in levels as well as growth rates over the 12 months prior to property disposition. See Table 2 for more details.

Since there are traditional cutoffs for DTIs in underwriting standard around 0.36 and 0.45, we test an alternative specification using spline coefficient estimates around those points of interest. Using the full sample, we find that the DTI-spline coefficient estimates do differ from one another(with a smaller negative effect on severity for the highest portion of the DTI spline above 0.45 versus the lowest portion below 0.36) but have no impact on the primary coefficient estimates of interest (disposition type impact).

In another test, we examine how DTI impacts various components of loss severities. The results (available from the authors upon request) indicate that DTI primarily reduces the losses associated with the sale of the property. The reason for this impact is unclear. But it is clear that DTI reveals something about the borrower or their interaction with the lender that leads to a better sale price of the distressed property. A discussion that breaks down loss severity into different components is provided later in the results section. We also run additional specifications that do not include DTI, which yield almost identical results for the effects on severity of alternative disposition types.

We provide a full set of coefficient estimates in Appendix 2.

It includes the regular primary mortgage insurance revenue as well as servicer payment due to mortgage insurance rescission.

Ambrose, B., & Capone, C. (1996). Cost-benefit analysis of single-family foreclosure alternatives. Journal of Real Estate Finance and Economics, 13, 105–120.CrossRef

Ambrose, B., & Capone, C. (1998). Modeling the conditional probability of foreclosure in the context of single-family mortgage default resolutions. Real Estate Economics, 26(3), 391–429.CrossRef

An, X., & Cordell, L. (2019). Mortgage loss severities: What keeps them so high. Federal Reserve Bank of Philadelphia, Working Papers, research department, WP 19-19, march 2019, https://doi.org/10.21799/frbp.wp.2019.19.

Andersson, F., & Mayock, T. (2014). Loss severities on residential real estate debt during the great recession. Journal of Banking and Finance, 46, 266–284.CrossRef

Anenberg, E., & Kung, E. (2014). Estimates of the size and sources of price declines due to nearby foreclosures. American Economic Review, 104(8), 2527–2551.CrossRef

Biswas, A. (2012). Housing submarkets and the impacts of foreclosures on property prices. Journal of Housing Economics, 21(3), 235–245.CrossRef

Calem, P., & LaCour-Little, M. (2004). Risk-based capital requirements for mortgage loans. Journal of Banking and Finance, 28(3), 647–672.CrossRef

Campbell, J., Giglio, S., & Pathak, P. (2011). Forced sales and house prices. American Economic Review, 101(5), 2108–2131.CrossRef

Campbell, J., & Cocco, J. (2015). A model of mortgage default. Journal of Finance, 70(4), 1495–1554.CrossRef

Clauretie, T., & Herzog, T. (1990). The effect of state foreclosure laws on loan losses: Evidence from the mortgage insurance industry. Journal of Money, Credit and Banking, 22(2), 221–233.CrossRef

Clauretie, T., & Daneshvary, T. (2011). The optimal choice for lenders facing defaults: Short sale, foreclosure, or REO. Journal of Real Estate Finance and Economics, 42, 217–231.CrossRef

Collins, J., Lam, K., & Herbert, C. (2011). State foreclosure policies and lender interventions; impacts on borrower behavior in default. Journal of Policy Analysis and Management, 30(2), 216–232.CrossRef

Cordell, L., & Lambie-Hansen, L. (2016). A cost-benefit analysis of judicial foreclosure delay and a preliminary look at new mortgage servicing rules. Journal of Economics and Business, 84, 30–49.CrossRef

Cordell, L., Geng, L., Goodman, L., & Yang, L. (2015). The cost of foreclosure delay. Real Estate Economics, 43(4), 916–956.CrossRef

Demiroglu, C., Dudley, E., & James, C. (2014). State foreclosure laws and the incidence of mortgage default. Journal of Law and Economics, 57(1), 225–280.CrossRef

Gerardi, K., Lambie-Hanson, L., & Willen, P. (2013). Do borrower rights improve borrower outcomes? Evidence from the foreclosure process. Journal of Urban Economics, 73, 1–17.CrossRef

Gerardi, K., Rosenblatt, E., Willen, P., & Yao, V. (2015). Foreclosure externalities: New evidence. Journal of Urban Economics, 87, 42–56.CrossRef

Ghent, A., & Kudlyak, M. (2011). Recourse and residential mortgage default: Evidence from U.S. states. Review of Financial Studies, 24(9), 3139–3186.CrossRef

Goodwin, K., & Johnson, K. (2017). The short sale stigma. Journal of Real Estate and Finance and Economics, 55, 416–434.CrossRef

Ho, D., Imai, K., King, G., & Stuart, E. (2007). Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Political Analysis, 15, 199–236.CrossRef

Iacus, S., King G., & Porroo, G. (2008). Matching for causal inference without balance checking. http://gking.harvard.edu/files/cem.pdf.

Iacus, S., King, G., & Porro, G. (2011). Multivariate matching methods that are monotonic imbalance bounding. Journal of the American Statistical Association, 106, 345–361.CrossRef

Immergluck, D., & Smith, J. (2006). The external costs of foreclosure: The impact of single-family mortgage foreclosures on property values. Housing Policy Debate, 17(1), 57–79.CrossRef

King, G., & Nielsen, R. (2019) Why propensity scores should not be used for matching. Political Analysis, 27(4), 1–20. Downloaded from http://j.mp/2ovYGsW

Le, B., & Pennington-Cross, A. (2018). Mortgage losses: Loss on sale and holding costs, working paper.

Mian, A., Sufi, A., & Trebbi, F. (2015). Foreclosures, house prices, and the real economy. Journal of Finance, 70(6), 2587–2634.CrossRef

Park, Y., & Bang, D. (2014). Loss given default of residential mortgages in a low LTV regime: Role of foreclosure auction process and housing market cycles. Journal of Banking and Finance, 39, 192–210.CrossRef

Qi, M., & Yang, X. (2009). Loss given default of high loan-to-value residential mortgages. Journal of Banking and Finance, 33(5), 788–799.CrossRef

Rosenbaum, P., & Rubin, D. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70, 41–55.CrossRef

Schuetz, J., Been, V., & Gould Ellen, I. (2008). Neighborhood effects of concentrated mortgage foreclosures. Journal of Housing Economics, 31(4), 455–480.

Zhang, Ca. (2019). A shortage of short sales: Explaining the underutilization of a foreclosure alternative. Federal Reserve Bank of Philadelphia Working Paper, WP 19-13.

Zhang, Y., Ji, L., & and Liu, F. (2010). Local Housing Market Cycle and Loss Given Default: Evidence from Sub-Prime Residential Mortgages. IMF Working Paper, WP/10/167 July.

Title: Mortgage Losses under Alternative Property Disposition Approaches: Deed-in-Lieu, Short Sales, and Foreclosure Sales
Authors: Arnab Biswas
Hamilton Fout
Anthony Pennington-Cross
Publication date: 09-08-2020
Publisher: Springer US
Published in: The Journal of Real Estate Finance and Economics / Issue 3/2023
Print ISSN: 0895-5638
Electronic ISSN: 1573-045X
DOI: https://doi.org/10.1007/s11146-020-09785-2

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