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

Authors

Pavlos Almanidis, Ernst & Young LLP
Mustafa U. Karakaplan, Governors State University
Levent Kutlu, The University of Texas Rio Grande ValleyFollow

Document Type

Article

Publication Date

10-24-2019

Abstract

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.

Comments

Original published version available at https://doi.org/10.1007/s11123-019-00565-6

Recommended Citation

Almanidis, Pavlos, Mustafa U. Karakaplan, and Levent Kutlu. “A Dynamic Stochastic Frontier Model with Threshold Effects: U.S. Bank Size and Efficiency.” Journal of Productivity Analysis 52, no. 1 (October 24, 2019): 69–84. https://doi.org/10.1007/s11123-019-00565-6.

Publication Title

Journal of Productivity Analysis

DOI

10.1007/s11123-019-00565-6