The Role of Corporate Governance in Reducing the Negative Effect of Earnings Management
Bibliographic record
Abstract
This paper aims to examine the role of corporate governance in reducing the negative effect of earnings management. The accounting data for U.S. firms during 2002-2010 were collected from WorldScope database and the corporate governance data were from ASSET4, which is an affiliate of Thomson Reuter. Earnings management can be harmful to firm value if it arises from managerial opportunism, whereas it can also be beneficial if managers intend to convey some information about future earnings or reduce the volatility of reported earnings. The empirical evidence has shown that earnings management has a negative effect on firm value. However, the negative effect of earnings management is neutralized by the role of corporate governance, which helps to reduce managerial opportunism. Firms with a lower CG score face the negative effect of earnings management, whereas firms with a higher CG score face a less-negative effect from earnings management. In other words, managerial opportunism with earnings management is lower in good-governance firms. Therefore, corporate governance provides a crucial role in reducing the negative effect of earnings management.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".