Date of Award


Degree Type


Degree Name

Doctor of Philosophy (PhD)


Real Estate

First Advisor

Dr. Jonathan A. Wiley, PhD

Second Advisor

Dr. Paul G. Gallimore, PhD

Third Advisor

Dr. Karen M. Gibler, PhD

Fourth Advisor

Dr. Alan J. Ziobrowski, PhD

Fifth Advisor

Dr. Len V. Zumpano, PhD


Commercial mortgage underwriters have traditionally relied upon a standard set of criteria for approving and pricing loans. The increased level of commercial mortgage loan defaults from 1% at the start of 2009 to 9.32% by the end of 2011 provides motivation for questioning underwriting standards which previously served the lending industry well. This dissertation investigates factors that affect the probability of Non-performance among commercial mortgage-backed security (CMBS) loans, proposes conditions under which the standard ratios may not apply, and tests additional criteria which may prove useful during economic periods previously not experienced by commercial mortgage underwriters. In this dissertation, Cap Rate Spread, the difference between the cap rate of a property and the Coupon Rate of the associated loan, is introduced to test whether the probability of Non-performance can be better predicted than by relying on traditional commercial mortgage underwriting criteria such as Loan to Value (LTV) and Debt Service Coverage Ratio (DSCR). Testing the research hypotheses with a probit model using a database of 47,883 U.S. CMBS loans from 1993 to 2011, Cap Rate Spread is found to have a significantly negative relationship with loan Non-performance. That is, as the Cap Rate Spread falls, the probability of Non-performance rises appreciably.

A numerical model suggests that among loans which would have passed the standard ratio tests requiring loans to have values of LTV less than .8 and DSCR greater than 1.25, a Cap Rate Spread criteria requiring loans to have a value greater than 1% would have prevented the origination of an additional 1,798 CMBS loans reducing the rate of Non-performance from 14.9% with only the LTV and DSCR criteria to just 11.6% by adding the Cap Rate Spread criteria. Of course, adding additional criteria will also lead to errors of rejecting loans which would have performed well. Back testing with the same sample of CMBS loans, this Type I error rate rises from 19% with only the LTV and DSCR criteria to 34% with the addition of the Cap Rate Spread.

Ultimately, CMBS loan underwriters must individually determine an acceptable level of Non-performance appropriate to their business model and tolerance for risk. Using intuition, experience, tools, and rules, each underwriter must choose a balance between the competing risks of rejecting potentially profitable loans and accepting loans which will fail. This research result is important because it helps deepen our understanding of the relationships between property income and loan performance and provides an additional tool that underwriters may employ in assessing CMBS loan risk.