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

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  • Wanke, Peter
  • Azad, Abul Kalam
  • Emrouznejad, Ali

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.

Suggested Citation

  • Wanke, Peter & Azad, Abul Kalam & Emrouznejad, Ali, 2018. "Efficiency in BRICS banking under data vagueness: A two-stage fuzzy approach," Global Finance Journal, Elsevier, vol. 35(C), pages 58-71.
    • Handle: RePEc:eee:glofin:v:35:y:2018:i:c:p:58-71
    DOI: 10.1016/j.gfj.2017.05.001
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    Cited by:

    1. Levent SEZAL, 2023. "Analyzing the financial performance of Turkish bank groups during the Covid-19 pandemic with the TOPSIS method," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(4(637), W), pages 5-16, Winter.
    2. Wanke, Peter & Tsionas, Mike G. & Chen, Zhongfei & Moreira Antunes, Jorge Junio, 2020. "Dynamic network DEA and SFA models for accounting and financial indicators with an analysis of super-efficiency in stochastic frontiers: An efficiency comparison in OECD banking," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 456-468.
    3. M.V. Leonov, 2021. "Review of Modern Approaches for Assessing the Effectiveness of Banking," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 20(2), pages 294-326.
    4. Marc Sanchez-Roger & María Dolores Oliver-Alfonso & Carlos Sanchís-Pedregosa, 2019. "Fuzzy Logic and Its Uses in Finance: A Systematic Review Exploring Its Potential to Deal with Banking Crises," Mathematics, MDPI, vol. 7(11), pages 1-22, November.

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    More about this item

    Keywords

    Banking performance; BRICS; Fuzzy TOPSIS; Fuzzy regression; Data reliability;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G34 - Financial Economics - - Corporate Finance and Governance - - - Mergers; Acquisitions; Restructuring; Corporate Governance

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