Satisficing data envelopment analysis: a Bayesian approach for peer mining in the banking sector
dc.contributor.author | Vincent, Charles | |
dc.contributor.author | Tsolas, I.E. | |
dc.contributor.author | Gherman, T. | |
dc.date.accessioned | 2019-12-15T12:20:42Z | |
dc.date.accessioned | 2019-12-16T14:33:18Z | |
dc.date.available | 2019-12-15T12:20:42Z | |
dc.date.available | 2019-12-16T14:33:18Z | |
dc.date.issued | 2018-10 | |
dc.identifier.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. | en_US |
dc.identifier.uri | http://hdl.handle.net/10454/17537 | |
dc.description | Yes | |
dc.description.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. | en_US |
dc.language.iso | en | en_US |
dc.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 | en_US |
dc.subject | Data envelopment analysis | |
dc.subject | Satisficing DEA | |
dc.subject | Mathematical programming | |
dc.subject | Banking | |
dc.subject | Peer mining | |
dc.subject | Bayesian predictive analytics | |
dc.title | Satisficing data envelopment analysis: a Bayesian approach for peer mining in the banking sector | en_US |
dc.status.refereed | Yes | |
dc.date.application | 17/06/2017 | |
dc.type | Article | |
dc.type.version | Accepted manuscript | |
dc.identifier.doi | https://doi.org/10.1007/s10479-017-2552-x | |
dc.date.updated | 2019-12-15T12:20:58Z | |
refterms.dateFOA | 2019-12-16T14:33:48Z | |
dc.openaccess.status | openAccess | |
dc.date.accepted | 2017 |