Journal
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volume 200, Issue 2, Pages 568-581Publisher
ELSEVIER
DOI: 10.1016/j.ejor.2008.12.033
Keywords
Efficiency; Quantile regression; Banking
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We discuss quantile regression techniques as a robust and easy to implement alternative for estimating Farell technical efficiency scores. The quantile regression approach estimates the production process for benchmark banks located at top conditional quantiles. Monte Carlo simulations reveal that even when generating data according to the assumptions of the stochastic frontier model (SFA), efficiency estimates obtained from quantile regressions resemble SFA-efficiency estimates. We apply the SFA and the quantile regression approach to German bank data for three banking groups, commercial banks, savings banks and cooperative banks to estimate efficiency scores based on a simple value added function and a multiple-input-multiple-output cost function. The results reveal that the efficient (benchmark) banks have production and cost elasticities which differ considerably from elasticities obtained from conditional mean functions and stochastic frontier functions. (C) 2009 Elsevier B.V. All rights reserved.
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