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    Satisficing data envelopment analysis: a Bayesian approach for peer mining in the banking sector

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    Publication date
    2018-10
    Author
    Vincent, Charles
    Tsolas, I.E.
    Gherman, T.
    Keyword
    Data envelopment analysis
    Satisficing DEA
    Mathematical programming
    Banking
    Peer mining
    Bayesian predictive analytics
    Rights
    © 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
    Peer-Reviewed
    Yes
    
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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.
    URI
    http://hdl.handle.net/10454/17537
    Version
    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.
    Link to publisher’s version
    https://doi.org/10.1007/s10479-017-2552-x
    Type
    Article
    Collections
    Management and Law Publications

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