Political Instability and Banks Performance in the Light of Arab Spring: Evidence From GCC Region
Bibliographic record
Abstract
The purpose of this empirical study is to investigate the consequences of the Arab spring on the banks financial performance at the level of Islamic and conventional banks in the Gulf Cooperative Council (GCC). The sample of this empirical research comprises 20 Islamic banks and 37 conventional banks during the period 2000-2018. The quantitative research methodology was employed by using Bivariate analysis and a panel regression on longitudinal data. The empirical findings show that the Arab spring had a direct negative influence on the bank’s performance in the GCC, whether Islamic or non-Islamic banks. The direct negative influence is most prominent on the banking system in the GCC region in the inability of these banks to enhance and maintain their financial performance and profitability level during the Arab spring. The results also revealed influenced negatively on the country-specific variables. These findings considered to be a caution to policymakers when establishing a strategy for microeconomic and macroeconomic financial performance. It is broadly known that the Arab spring has an important influence on the economies of the GCC countries. Notably, the influence of the Arab spring on the banking industry performance and profitability has not so far been exposed to detailed investigation. Therefore, this research pursues to shed light on this gap by employing robust quantitative analysis. It differentiates between pre and post the Arab spring, it also classified banks into Islamic and non-Islamic and it employs micro and macroeconomic variables to investigate the influence of Arab spring effectively. It`s also the first to examine the micro and macroeconomic variables across both Islamic and non-Islamic banks pre and post the Arab spring. This research employed both Bivariate analysis and a panel regression on longitudinal data on both Islamic and conventional banks.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| 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".