Essays on Commercial Banking: Survival, Performance, and Heterogeneous Technologies

In the first chapter, we focus on explaining the U.S. commercial banking failures during the recent financial crisis. We employ the semi-parametric mixture hazard model (MHM) with both continuous and discrete time specifications to first, distinguish between troubled and healthy banks and second, to estimate the probability and the timing of their failure. We combine the MHM with the stochastic frontier model (SFM) to explore the role of managerial inefficiency on a bank's longer term viability. We find that the discrete-time MHM which takes the managerial inefficiencies into account fits well and dominates other competing specifications by accurately predicting the timing of failures both in and out of the sample. The second chapter explores a new class of flexible cross-sectional parametric SFMs that impose an unobservable bound on the inefficiency term. We consider 11 doubly truncated normal, truncated half-normal, and truncated exponential distributions to model the inefficiencies. We extend the models to the panel data setting and specify a time-varying inefficiency bound. We apply these models to analyze the performance of the U.S. commercial banking industry during 1984-2009. In the third chapter, we address the issue of the "wrong" skewness of the least squares residuals that often arises in applied studies using the traditional SFM. Findings of "wrong" skewness imply that the SFM is misspecified and all firms are fully efficient. Based on doubly truncated normal distribution that displays both positive and negative skewness, we prove that "wrong" skewness does not necessarily imply that the SFM model is misspecified. The fourth chapter investigates the existence of heterogeneous technologies in the U.S. commercial banking industry through the threshold effects estimation techniques, modified to allow for time-varying effects. We employ the total assets as a threshold variable and determine seven distinct technology-groups. In the fifth chapter, we describe the commercial banking data that are extracted from the quarterly Consolidated Reports of Condition and Income (Call Reports). We detail the construction of the key variables used in this thesis, which mainly contain output quantities, input quantities and prices, bank-specific structural and geographical characteristics, as well as a number of measures of risk

A Dynamic Stochastic Frontier Model with Threshold Effects: U.S. Bank Size and Efficiency

Common/Single frontier methodologies that are used to analyze bank efficiency and performance can be misleading because of the homogeneous technology assumption. Using the U.S. banking data over 1984-2010, our dynamic methodology identifies a few data-driven thresholds and distinct size groups. Under common frontier assumption, the largest banks appear to be 22% less efficient on average than how they are in our model. Also, in the common frontier model, smaller banks seem to be relatively more efficient compared to their larger counterparts. Hence, common policies or regulations may not be well-balanced about controlling the banks of different sizes on the spectrum