finding suggests that it is possible for commercial mortgage loan servicers to distinguish amongthe potential outcomes of delinquent loans.5. Conclusion <strong>and</strong> ExtensionsAn innovation in this paper is to consider the models for delinquency <strong>and</strong> delinquencyoutcome separately. This is justified since the outcome of delinquency is not foregone –reinstatement is a more frequent resolution than foreclosure. The empirical models are estimatedusing a database from a single lender, with particularly accurate values for the loan-to-value ratio<strong>and</strong> the debt coverage ratio.The results of the empirical estimations have implications for lenders’ monitoringfunctions. Lenders should use the critical variables of loan-to-value ratio, debt coverage ratio <strong>and</strong>guarantee to identify expected delinquent loans. Within this pool of delinquent loans, these samecharacteristics can be used to predict the outcome, which could be reinstatement or foreclosure.An important contribution of this paper is to demonstrate that the loan-to-value ratio, debtcoverage ratio <strong>and</strong> guarantee differ in a statistically significant way across these outcomes.This paper is also the first to examine the guarantee variable, <strong>and</strong> despite issues related toendogeneity <strong>and</strong> difficulty in realization on the guarantee, it was found to be consistentlystatistically significant, both in prediction of delinquency <strong>and</strong> in distinguishing among thereinstatement <strong>and</strong> foreclosure outcomes of delinquency.Planned extensions of this paper include the formalization of the two-stage conceptualmodel of the default process, as well as robustness checks for the results in light of restructuringmodifications, post-renewal defaults <strong>and</strong> prepayments.13
ReferencesAmbrose, Brent W., Buttimer, Richard J., Embedded Options in the <strong>Mortgage</strong> Contract, Journalof Real Estate Finance <strong>and</strong> Economics, 21(2), 2000, pages 95-111.Ambrose, Brent, Capone, Charles, Modeling the Conditional Probability of <strong>Foreclosure</strong> in theContext of Single-Family <strong>Mortgage</strong> Default Resolutions, Real Estate Economics, 1998,26(3), pages 391-429.Ambrose, Brent, Capone, Charles, Cost-Benefit Analysis of Single Family <strong>Foreclosure</strong>Alternatives, Journal of Real Estate Finance <strong>and</strong> Economics, 13, 1996, pages 105-120.Ambrose, Brent; S<strong>and</strong>ers, Anthony, <strong>Commercial</strong> <strong>Mortgage</strong>-backed Securities: Prepayment <strong>and</strong>Default, working paper, 2001.Archer, Wayne et al., Determinants of Multifamily <strong>Mortgage</strong> Default. Real Estate Economics,30(3), 2002, pages 445-473.Childs, Paul D.; Ott, Steven H.; Riddiough, Timothy J., The Pricing of Multi-Class <strong>Commercial</strong><strong>Mortgage</strong> Backed Securities, Journal of Financial <strong>and</strong> Quantitative Analysis; 31(4),December 1996, pages 581-603.Chun, Jun; Deng, Yongheng, <strong>Commercial</strong> <strong>Mortgage</strong> Workout Strategy <strong>and</strong> Conditional DefaultProbability: Evidence from Special Serviced CMBS Loans, working paper, 2002.Ciochetti, Brian A., Loss Characteristics of <strong>Commercial</strong> <strong>Mortgage</strong> <strong>Foreclosure</strong>s, Real EstateFinance, Spring 1997, pages 53-69.Ciochetti, Brian A. et al., The Termination of <strong>Commercial</strong> <strong>Mortgage</strong> Contracts throughprepayment <strong>and</strong> Default: A Proportional Hazard Approach with Competing Risks, RealEstate Economics, 30(4), 2002, pages 595-633.Foster, C., Van Order, R.; FHA Terminations,: A Prelude to Rational <strong>Mortgage</strong> Pricing, Journalof the American Real Estate <strong>and</strong> Urban Economics Association, 1985, 13(3), pages 292-316.14
- Page 1 and 2: Commercial Mortgage Delinquency, Fo
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- Page 37 and 38: ReferencesBlack, Fischer; Jenson, M
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