Ownership structure and earnings management: evidence from Jordan
Bibliographic record
Abstract
Purpose The purpose of this paper is to examine the association between internal corporate governance mechanism and earnings management of Jordanian companies. More specifically, the author examines several hypotheses regarding the relationships between ownership and earnings management. Design/methodology/approach This study measures the magnitude of discretionary accruals as a proxy for earnings management using the cross-sectional modified Jones model. A number of econometric techniques are used including ordinary least squares and generalized least squares to test the relationship between company ownership and earnings management, using a sample of 62 companies listed on the Amman Stock Exchange. Findings The results revealed that insider managerial ownership, institutional ownership, external blockholder, family ownership and foreign ownership have superior influence on financial reporting quality, as it is, to a greater extent, potentially able to curtail earnings management. The findings contended that the aspects of ownership structure have a significant influence on earnings management, which is in agreement with the theories of corporate governance and opinions that have been highlighted through a number of international bodies. Research limitations/implications Due to lack of data, the paper depends on cross-sectional data applied to isolate abnormal accruals. Practical implications The evidence may be conceivably beneficial as a supporting fundamental for regulatory action, particularly those that affect the ownership structure. The findings have significant implications for regulators as well as supervisors, who will benefit by the comprehension of how ownership structure affects earnings management and enhance financial reporting quality. Originality/value The current research produced its essential contribution through empirically displaying that ownership structure has different implications on earnings management. Moreover, the results recommended that both policymakers and researchers would no longer contemplate ownership structure as a whole, given that ownership structure has different implications on earnings management, measured by the discretionary accruals.
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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 | 0.001 | 0.003 |
| 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) | 0.003 | 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".