The Impact of Corporate Governance on the Financial Performance of the Banking Sector in the MENA (Middle Eastern and North African) Region: An Immunity Test of Banks for COVID-19
Bibliographic record
Abstract
The purpose of this paper is to measure the impact of internal and external corporate governance mechanisms on the financial performance of banks in the under-researched Middle Eastern and North African (MENA) region during the COVID-19 pandemic period. Bank annual reports, the Orbis Bank Focus database, and World Bank reports were used to collect both financial and non-financial information on the banking sector, followed by fixed effects regressions and two-stage least squares. Results showed that the corporate governance measures of presence of independent members on the board of directors, high ownership concentration, lack of political pressure on board members, and strong legal protection, had positive effects on bank financial performance. Corporate governance mechanisms, such as performance-based compensation, the presence of women on boards, moderate size of the board, and anti-takeover mechanisms had no significant impact on bank performance during the crisis period. An effective internal and external corporate governance mechanism could improve the financial performance of banks in MENA countries in times of pandemics and crises.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".