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.
Original language | English |
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Pages (from-to) | 81-102 |
Number of pages | 22 |
Journal | Annals of Operations Research |
Volume | 269 |
Early online date | 17 Jun 2017 |
DOIs | |
Publication status | E-pub ahead of print - 17 Jun 2017 |
Externally published | Yes |
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Assoc. Prof. Dr Tatiana Gherman
- University of Northampton, Strategy and International Business - Associate Professor of AI for Business & Strategy
- Centre for Global Economic and Social Development
- Centre for Sustainable Business Practices
Person: Academic