Does the audit quality have any moderating impact on the relationship between ownership structure and dividends? Evidence from Jordan
Bibliographic record
Abstract
The article aims at investigating whether audit quality impacts the relationship between ownership structure and dividends in companies listed on the Amman Stock Exchange (ASE). The article is constructed on the analysis of time-series–cross-section (TSCS) (Panel Data). The study sample comprises 34 companies listed on the Amman Stock Exchange between 2016 and 2021. The study sample’s content of the financial reports is analyzed to attain appropriate data for the study. The Findings indicate that family ownership and ownership of board members negatively impact dividends. In contrast, institutional ownership and concentrated ownership positively impact dividends, as no effect of foreign ownership is found on dividends. By introducing audit quality as a modified variable on the relationship between ownership structure and dividends, the findings demonstrate that audit quality positively enhances and strengthens this relationship. This article with its results is of great significance to future stockholders and shareholders, as they help in selecting companies capable of distributing higher dividends than other companies and achieving satisfactory investment returns. The findings of the study also focus on the significance of audit quality as a guarantor for regulating the relationship between forms of ownership structure and the distribution of dividends. This study is regarded among the little research investigating the factors that would impact the relationship between ownership structure and dividends. This article plays a key role in bridging the research gap related to the lack of studies dealing with the relationship between ownership structure and dividends in emerging markets.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".