Does the efficiency of banks adversely affect financial stability? A comparative study between traditional and Islamic banks: Evidence from Egypt

  • Received October 26, 2021;
    Accepted March 11, 2022;
    Published April 25, 2022
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/bbs.17(2).2022.02
  • Article Info
    Volume 17 2022, Issue #2, pp. 13-26
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The efficiency of banks is an important factor that effectively contributes to the stability of the world financial system, thus reducing financial failure rates of banks and international financial crises that leads to the stability of the global financial system. This study aims to investigate whether the efficiency of Egyptian banks adversely affects financial stability. A sample of 30 banks operating in Egypt was selected to answer this question using the data envelopment analysis (DEA) approach and financial ratios. This study enables the Central Bank of Egypt to identify which banking system (Islamic banks or traditional banks) is more efficient and contributes significantly to boost economic growth. Results revealed that the efficiency of banks is a core factor to affect financial stability. The statically explanatory power of this effect is significant but weak at 14.1% for all Egyptian banks, 6.3% for traditional banks, strong for traditional banks with Islamic window at 22%, and stronger for Islamic banks at 55%. Consequently, the Islamic banking system in Egypt is more efficient compared to traditional banks and has a greater impact on financial stability as one of the pillars of financial inclusion to boost economic growth in Egypt.

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    • Table 1. Efficiency index
    • Table 2. Variables’ definitions
    • Table 3. Descriptive statistics (Model A)
    • Table 4. Correlation matrix for Model A
    • Table 5. Analysis output for Model A
    • Table 6. Descriptive statistics for Model B
    • Table 7. Correlations matrix for Model B
    • Table 8. Analysis output for Model B
    • Table 9. Descriptive statistics for Model C
    • Table 10. Correlations matrix for Model C
    • Table 11. Analysis output for Model C
    • Table 12. Descriptive statistics for Model D
    • Table 13. Correlations matrix for Model D
    • Table 14. Analysis output for Model D
    • Table 15. Results summary of the statistical model
    • Table 1A. The study sample
    • Conceptualization
      Hassan Mohamed Mohamed Hafez
    • Data curation
      Hassan Mohamed Mohamed Hafez
    • Formal Analysis
      Hassan Mohamed Mohamed Hafez
    • Investigation
      Hassan Mohamed Mohamed Hafez
    • Methodology
      Hassan Mohamed Mohamed Hafez
    • Project administration
      Hassan Mohamed Mohamed Hafez
    • Software
      Hassan Mohamed Mohamed Hafez
    • Supervision
      Hassan Mohamed Mohamed Hafez
    • Validation
      Hassan Mohamed Mohamed Hafez
    • Visualization
      Hassan Mohamed Mohamed Hafez
    • Writing – original draft
      Hassan Mohamed Mohamed Hafez
    • Writing – review & editing
      Hassan Mohamed Mohamed Hafez