Property market dynamics depend on changes in long run equilibrium and on impediments to adjustment towards equilibrium. One of the most important aspects of property market dynamics is often attributed to the activities in the mortgage market. However, many impediment factors, such as changes in family status, education, neighborhood effects and job relocation, are often unobservable from micro household-level data. Since these omitted variables contribute to moving decisions and therefore to sale and default decisions, utility functions for sale and default are correlated through these unobservable variables; thus, the IIA assumption of the widely used Multinomial Logit Model (MNL) is violated. Under such circumstances, econometric theory suggests that the Nested Logit Model (NMNL) is a better choice, which obviates the limitation of MNL by allowing correlation in unobserved factors across alternatives. This paper empirically investigates the omitted household mobility characteristics problem in mortgage termination, and tests NMNL against MNL. Using loan level micro data, we find significant correlation between sale and default due to omitted borrower mobility characteristics. Our simulations find that NMNL out performs MNL in out-of-sample prediction.