Effect of Family Involvement and Corporate Governance on Dividend Policy: A Study of Non-Financial Listed Firms in Morocco
Bibliographic record
Abstract
Current research on the determinants of dividend policy has focused on the study of developed countries, while research on emerging countries remains limited. The objective of this research is to study the effect of the involvement of the family firm on dividend policy. This paper uses Ordinary Least Squares regression, we analyzed data for Moroccan nonfinancial firms listed on the Casablanca Stock Exchange over the period 2015-2017. The results of this paper show that family firm pay less dividends than non-family firms. Thus, ownership concentration and firm size influence dividend policy, unlike the composition of the board of directors, which doesn’t influence it. Our paper contributes to broaden our understanding of the effect of the family firm on dividend policy in one of the emerging countries. It is suggested that the characteristics of corporate ownership determine the share of profits to be distributed, not to say dividend policy, since concentration of ownership limits the power of minority shareholders to make their voices heard. Despite the presence of laws protecting minority shareholders, their room for maneuver remains limited. Our paper enriches the existing literature on the family firm dividend policy by studying the Moroccan context. The results show that family ownership and family CEO involvement do not have the same influence on the dividend policy of family firms, but it depends on the context. Our paper also provides relevant information for practitioners regarding dividend policy in Moroccan family firms.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".