Efficiency Estimation of U.S. Commercial Banking: A Stochastic Frontier Approach Using Gibbs Sampling

37 Pages Posted: 12 Feb 2003

See all articles by James M. Sfiridis

James M. Sfiridis

University of Connecticut - Department of Finance

Kenneth N. Daniels

Daniels Foundation for Impact Investments and Development

Abstract

Banking cost or X-efficiency is dependent upon the frontier analysis method used to measure the efficient frontier. Parametric methods require estimation of a composite error model where the bank's efficiency parameter is a portion of the bank's deviation from the cost frontier of the banking cost function. In this article Bayesian-based Markov chain Monte Carlo (MCMC) methods, specifically the Gibbs sampler supplemented by data augmentation, are used for the first time to estimate the cost efficiency of a sample of U.S. commercial banks. Sampling-based computational methods are shown to provide a straightforward and reasonable approach to determining bank cost efficiency. Additionally, such new analytical capabilities provide summary statistics for statistical testing previously beyond the scope of classical methods.

Keywords: Cost efficiency, X efficiency, stochastic frontier, Bayesian computation, Gibbs sampling

JEL Classification: G21, C11, C15

Suggested Citation

Sfiridis, James M. and Daniels, Kenneth N., Efficiency Estimation of U.S. Commercial Banking: A Stochastic Frontier Approach Using Gibbs Sampling. Available at SSRN: https://ssrn.com/abstract=363660 or http://dx.doi.org/10.2139/ssrn.363660

James M. Sfiridis (Contact Author)

University of Connecticut - Department of Finance ( email )

Unit 1041F
School of Business
Storrs, CT 06269-1041
United States
860-486-3040 (Phone)
860-486-0349 (Fax)

Kenneth N. Daniels

Daniels Foundation for Impact Investments and Development ( email )

New Jersey, NJ 07018
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
666
Abstract Views
2,794
rank
55,235
PlumX Metrics