Financial Stability in the MENA Region: The Impact of Banking Capitalization and Institutional Environment on Credit Availability
Bibliographic record
Abstract
This study aims to analyze the applicability of the supply-side credit crunch in the MENA region by investigating the influence of bank capitalization and the institutional environment on the lending activities of banks operating in the region from 1999 to 2020. Employing the generalized method of moments (GMM) panel data estimator, our analysis reveals that bank lending is shaped by specific bank-related variables, country-level macroeconomic variables, and the quality of institutions. Our findings underscore that increases in bank capitalization levels, competition levels, or banks' liquidity ratios exert a negative impact on credit availability. Conversely, the size and profitability of banks have a positive effect on the accessibility of loans. It is evident that the banks under consideration consistently expand their credit supply in tandem with economic expansion and low inflation rates, thereby positively influencing credit demand. Furthermore, our study indicates that robust anti-corruption measures, political stability, and adherence to the rule of law act as catalysts, encouraging banks to enhance their lending availability.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".