The Impact of Non-Interest Income on Commercial Bank Profitability in the Middle East and North Africa (MENA) Region
Bibliographic record
Abstract
This study examines the effects of non-interest income on bank performance in the Middle East and North Africa (MENA) region, addressing existing research gaps and conflicting results. The analysis is based on data from 40 banks (5 banks from each country) operating in Bahrain, Egypt, Jordan, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates between 2010 and 2022. Using correlation analysis and three regression models (OLS, FE, and RE), this study explores the relationship between non-interest income, overheads, capital adequacy, loan loss provision, bank size, and return on assets. The findings reveal positive associations among banks’ overhead, size, capital adequacy, and loan loss provision. Additionally, a favorable correlation is observed between non-interest income and bank performance. Non-interest income significantly influences the profitability of MENA region banks across all three models, supporting the main hypothesis. While the study’s limitations include sample size and geographic focus, the findings of this study provide valuable insights for policymakers, allowing them to recognize the positive impact of increasing non-interest income on commercial bank profitability in the MENA region and consider implementing policies that encourage and support banks in diversifying their income sources.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".