CEO power and bank risk in the UAE

  • Received July 26, 2020;
    Accepted September 1, 2020;
    Published September 11, 2020
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/bbs.15(3).2020.11
  • Article Info
    Volume 15 2020, Issue #3, pp. 117-128
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This work is licensed under a Creative Commons Attribution 4.0 International License

The lessons from the 2008 global financial crisis show that excessive risk taking and governance failures contribute to the failure of several banks. As a result, the relationship between corporate governance mechanisms and risk taking has been the subject of many studies. However, extant studies report inconclusive results. Therefore, this study aims to investigate the relationship between CEO power and bank risk in the UAE using data over the period of 2015–2018 and a sample of 19 UAE banks. The study uses a Pearson pairwise correlation to analyze the relationship between CEO power and bank risk. In addition, a two-tailed t-test is used to examine the differences between conventional and Islamic banks in terms of CEO power and risk-taking. The results of the study show that CEO power measured using CEO duality and CEO tenure reduces risk. Furthermore, the paper indicates that larger boards and higher CEO ownership tend to increase risk. The study also reports that conventional banks have higher return variability, larger boards and powerful CEOs than Islamic banks. However, Islamic banks tend to have higher non-performing finances than conventional banks. The study provides important insights on the relationship between CEO power and bank risk and concurs with earlier studies. The findings can be of interest to policy makers and can be used as input data for the development of corporate governance mechanisms. Shareholders can also use the survey results as input when appointing a CEO for their banks.

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    • Figure 1. Conceptual framework of variables
    • Table 1. Variable description
    • Table 2. Summary statistics
    • Table 3. Pearson correlation analysis of the relationship between dependent and independent variables
    • Table 4. Pearson correlation analysis of the interaction between dependent and independent variables
    • Table 5. Test of the significance difference between conventional and Islamic banks
    • Table A1. List of banks included in this study as of July 31, 2019
    • Conceptualization
      Haileslasie Tadele, Baliira Kalyebara
    • Data curation
      Haileslasie Tadele, Baliira Kalyebara
    • Formal Analysis
      Haileslasie Tadele, Baliira Kalyebara
    • Investigation
      Haileslasie Tadele
    • Methodology
      Haileslasie Tadele
    • Software
      Haileslasie Tadele
    • Writing – original draft
      Haileslasie Tadele
    • Writing – review & editing
      Baliira Kalyebara