Real Activities Manipulation and Subsequent Accounting Performance ---Yes, the Manipulating Direction Matters
Bibliographic record
Abstract
Previous studies reveal mixed results for the association between managers¡¯ aggressive real activities manipulation and a firm¡¯s subsequent performance. To examine the effects of real activities manipulation on a firm¡¯s subsequent accounting performance, this study incorporates the manipulating patterns (income-increasing vs. income-decreasing) into model, and uses unbalanced- panel data to establish the empirical regressions. The results reveal that a firm¡¯s income-increasing real activities manipulation is associated with a remarkable subsequent accounting performance. This finding supports the signal future prospect hypothesis of firms¡¯ strategic earnings reporting through aggressive real activities manipulation. However, the conjecture that the income-decreasing real activities manipulation is associated with better subsequent performance gains supported only in some settings. This study demonstrates some diagnostic checks, and provides evidence that the results are robust to the various specifications.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".