Mortgage-backed securities market has recently become the largest capital market for investors in the U.S. Not surprisingly, a large volume of literature studies mortgage borrowers’ prepayment and default behavior and its impact on the pricing of mortgage backed securities. However, due to errors in variables or limited availability of borrower characteristics, most empirical studies find a substantial discrepancy between the theoretically derived optimal behavior and the observed decisions. (See, for example, Deng, Quigley and Van Order [1996] and Stanton [1996]). This paper attempts to reconcile the theoretical option-based models of mortgage terminations with the empirical experience of mortgage terminations by refinancing, sale and default.
From a theoretical perspective, we explicitly model the borrower’s costs associated with mortgage terminations and recognize that those costs vary across individuals and termination causes. Consistent with this approach, we empirically separate the three major causes of mortgage termination: refinancing, selling of the property, and default. Furthermore, since borrowers of similar characteristics (education, income, culture and ethnic background, etc.) tend to cluster together in neighborhoods, many of the omitted variables and measurement errors are spatially correlated. Recognizing this spatial correlation we empirically model the variability of the mortgage termination costs through the use of the physical location of the properties. This approach gives raise to a competing risks hazard framework with spatially correlated errors.