Determinants of dividend policy in Palestinian banks
Bibliographic record
Abstract
This study aims to examine whether the dividend theories that were principally developed for non-financial companies in developed institutional environments can explain the dividend policies of banks in Palestine, an emerging market with a high level of uncertainty. It also aims to determine the main factors affecting the banks’ propensity to pay dividends and the banks’ dividend payout ratios. The study uses pooled Probit and ordinary least squares regressions to analyze 10 years of data from all listed banks in the Palestine Stock Exchange Market. The results indicate that agency cost, signaling, and regulatory pressure theories are valid for Palestinian banks. In addition, the analysis shows that bank size, profitability, and capital adequacy are the main positive determinants of Palestinian banks’ propensity to pay dividends and of the dividend payout ratios. Furthermore, after winsorizing the data, the results were found to remain consistent. Finally, the results of a general dominance analysis revealed that bank size is the most important determinant, followed by bank profitability and bank capital adequacy, all three of which positively influence dividend policy decisions in Palestinian banks. This study is among the first to investigate dividend policy determinants in the financial sector. Moreover, this study is conducted in Palestine, an emerging economy. Furthermore, unlike prior studies, this study considers banks’ propensity to pay dividends and banks’ dividend payout ratios concurrently when analyzing the dividend determinants in order to make a significant contribution to solving the dividend determinant puzzle.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".