Efficiency in BRICS banking under data vagueness:a two-stage fuzzy approach

Abstract

This study analyzes the efficiency levels of the banking industry in the BRICS countries (Brazil, Russia, India, China, and South Africa) from 2010 to 2014, using an integrated two-stage fuzzy approach. Very often the reliability of data collected from BRICS is questionable. In this research, we first use fuzzy TOPSIS to capture vagueness in the relative efficiency of BRICS banking over time. In the second stage, we adopt fuzzy regressions based on different rule-based systems to enhance the power of significant socioeconomic, regulatory, and demographic variables to predict banking efficiency. These variables are previously identified by using bootstrapped truncated regressions with conditional α-levels, as proposed by Wanke, Barros, and Emrouznejad (2015a). The results reveal that efficiency in the banking industry is positively associated with country gross savings and the GINI index ratio, but negatively associated with relatively high inflation ratios. Fuzzy regressions proved far more accurate than bootstrapped truncated regressions with conditional α-levels. We derive policy implications.

Publication DOI: https://doi.org/10.1016/j.gfj.2017.05.001
Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
Additional Information: © 2017, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords: banking performance,BRICS,fuzzy TOPSIS,fuzzy regression,data reliability,Finance,Economics and Econometrics
Publication ISSN: 1873-5665
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2018-02-01
Published Online Date: 2017-05-27
Accepted Date: 2017-05-22
Submitted Date: 2016-12-28
Authors: Wanke, Peter
Kalam Azad, Abul
Emrouznejad, Ali (ORCID Profile 0000-0001-8094-4244)

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