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Satisficing data envelopment analysis: a Bayesian approach for peer mining in the banking sector
Vincent, Charles Tsolas, I.E. Gherman, T.
Vincent, Charles
Tsolas, I.E.
Gherman, T.
Publication Date
2018-10
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© Springer Science+Business Media New York 2017. Reproduced in accordance with the publisher's self-archiving policy.
The final publication is available at Springer via http://dx.doi.org/10.1007/s10479-017-2552-x
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openAccess
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2017
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Abstract
Over the past few decades, the banking sectors in Latin America have undergone rapid structural changes to improve the efficiency and resilience of their financial systems. The up-to-date literature shows that all the research studies conducted to analyze the above-mentioned efficiency are based on a deterministic data envelopment analysis (DEA) model or econometric frontier approach. Nevertheless, the deterministic DEA model suffers from a possible lack of statistical power, especially in a small sample. As such, the current research paper develops the technique of satisficing DEA to examine the still less explored case of Peru. We propose a Satisficing DEA model applied to 14 banks operating in Peru to evaluate the bank-level efficiency under a stochastic environment, which is free from any theoretical distributional assumption. The proposed model does not only report the bank efficiency, but also proposes a new framework for peer mining based on the Bayesian analysis and potential improvements with the bias-corrected and accelerated confidence interval. Our study is the first of its kind in the literature to perform a peer analysis based on a probabilistic approach.
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Accepted manuscript
Citation
Vincent C, Tsolas IE and Gherman T (2018) Satisficing data envelopment analysis: a Bayesian approach for peer mining in the banking sector. Annals of Operations Research. 269(1-2): 81-102.
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