COMMERCIAL MORTGAGE DEFAULTS - PROPORTIONAL HAZARDS ESTIMATION USING INDIVIDUAL LOAN HISTORIES

This paper examines the theory of commercial mortgage default and test s it using a data sec of 2,899 loan histories provided by a major mult i-line insurance company. A default model is estimated which relates s ubsequent default incidence and timing to contemporaneous loan term, b orrower, property and economic/market conditions. Maximum likelihood e stimation is used to estimate a hazard function predicting conditional probability of default over rime. Results confirm many expected defau lt relationships, in particular the dominance of loan terms and proper ty value trends over time in affecting default. The effectiveness of t he model in discriminating between ''good'' and ''bad'' loans is explo red. Implications for underwriting practice and credit risk diversific ation are noted. Finally, suggestions are made for extending these res ults in pricing applications.