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Why fully efficient banks matter? A nonparametric stochastic frontier approach in the presence of fully efficient banks

  • Kien C. Tran
  • Mike G. Tsionas
  • Emmanuel Mamatzakis
Article
  • 18 Downloads

Abstract

A common assumption in the banking stochastic performance literature refers to the non-existence of fully efficient banks. This paper relaxes this strong assumption and proposes an alternative semiparametric zero-inefficiency stochastic frontier model. Specifically, we consider a nonparametric specification of the frontier whilst maintaining the parametric specification of the probability of fully efficient bank. We propose an iterative local maximum likelihood procedure that achieves the optimal convergence rates of both nonparametric frontier and the parameters contained in the probability of fully efficient bank. In an empirical application, we apply the proposed model and the estimation procedure to a global banking data set to derive new corrected measures of bank performance and productivity growth across the world. The results show that there is variability across regions, and the probability of fully efficient bank is mostly affected by bank-specific variables that are related to bank’s risk-taking attitude, whereas country-specific variables, such as inflation, also have an effect.

Keywords

Backfitting local maximum likelihood Mixture models Probability of fully efficient banks Global banking 

JEL Classification

C13 C14 G20 G21 

Notes

Acknowledgements

We would like to express our gratitude to the Editor, the Associate Editor and two anonymous referees for invaluable comments and suggestions that led to substantial improvement of the paper. We also appreciate the help of Marwan Izzeldin and the GOLCER centre at Lancaster University for their generous assistance in terms of computational support. The usual caveats apply.

Compliance with ethical standards

Conflict of interest

We declare that there is no conflict of interest of any kind.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Kien C. Tran
    • 1
  • Mike G. Tsionas
    • 2
  • Emmanuel Mamatzakis
    • 3
  1. 1.Department of EconomicsUniversity of LethbridgeLethbridgeCanada
  2. 2.Lancaster University Management SchoolLancasterUK
  3. 3.University of Sussex Business SchoolBrightonUK

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