CEO Characteristics and Real Earnings Management in Jordan
Bibliographic record
Abstract
The Chief Executive Officer (CEOs) tends to be the most influential member of a corporation as they exert control over corporate decisions such as financial disclosure, board structure, and company performance in ensuring enhanced corporate performance and earnings. The issue of earnings management (EM) that has captured the attention of researchers may be among the most critical factors that are linked to financial statement manipulation. Therefore, the current study explored the effects of the personal characteristics of CEOs on real earnings management (REM) practices in Jordan. Data of 58 companies listed on the Amman Stock Exchange for six years from 2013 to 2018 were utilised to achieve this study’s objectives. The results of this study revealed that CEOs’ experience had a significantly positive association with REM. Meanwhile, CEOs’ tenure had no impact on REM among Jordanian firms. Also, the results exposed the presence of a significantly negative association between CEO duality and REM. Finally, CEOs’ political connection was found to have a significantly positive association with REM. This study offers empirical evidence on the effect of CEO characteristics on REM and how such characteristics can lead to exploitation, which brings an impact on the financial reporting quality.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".