Determinants of banking efficiency in the MENA region: A two-stage DEA-Tobit approach

  • 19 Views
  • 5 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

In today’s volatile financial environment, banks encounter various risks, including political instability, regulatory changes, and global market fluctuations, which can undermine efficiency and threaten systemic stability. This study focuses on banking efficiency in the MENA region, highlighting its crucial role in economic growth and financial stability. This paper addresses the gap in banking efficiency research in the MENA region by evaluating the technical and pure technical efficiency of 59 conventional banks from 11 MENA countries between 2019 and 2023 and identifying the internal and external factors affecting their efficiency. Using a Data Envelopment Analysis, the study evaluates efficiency based on three inputs and two outputs. A panel Tobit regression model is then applied to analyze the impact of eight internal factors and four external factors on efficiency. The findings indicate that just 16% of the MENA banks were technically efficient, with Qatari banks outperforming and banks in Morocco and Jordan underperforming. The Tobit regression model results indicate that both return on assets and capital adequacy positively influence technical efficiency (TE) and pure technical efficiency (PTE). In contrast, Liquidity and operational costs negatively affect PTE and TE. Non-performing loans negatively impact TE but not PTE, and macroeconomic factors positively influence both TE and PTE. In conclusion, banks in the MENA region must prioritize improving their efficiency to stay competitive. The findings offer valuable insights into operational best practices and provide practical guidance for policymakers, regulators, and banking institutions to enhance the performance of the region’s financial systems.

view full abstract hide full abstract
    • Figure 1. Average TE, PTE, and SE in the 11 countries
    • Table 1. Input and output variables used in the DEA model
    • Table 2. 59 conventional banks of 11 MENA region countries
    • Table 3. Internal and external factors
    • Table 4. TE and PTE scores of the 59 banks over 2019–2023
    • Table 5. Results of the fixed-effects Tobit model applied to TE
    • Table 6. Results of the random-effects Tobit model applied to TE
    • Table 7. Hausman test
    • Table 8. Results of the fixed-effects Tobit model applied to PTE
    • Table 9. Results of the random-effects Tobit model applied to PTE
    • Table 10. Hausman test
    • Conceptualization
      Soufiane Benbachir
    • Data curation
      Soufiane Benbachir
    • Formal Analysis
      Soufiane Benbachir
    • Investigation
      Soufiane Benbachir
    • Methodology
      Soufiane Benbachir
    • Project administration
      Soufiane Benbachir
    • Resources
      Soufiane Benbachir
    • Software
      Soufiane Benbachir
    • Supervision
      Soufiane Benbachir
    • Validation
      Soufiane Benbachir
    • Visualization
      Soufiane Benbachir
    • Writing – original draft
      Soufiane Benbachir
    • Writing – review & editing
      Soufiane Benbachir