The Influence of Management's Internal Audit Experience on Earnings Management*
Bibliographic record
Abstract
ABSTRACT We examine whether firms with managers that have prior internal audit experience are less likely to manage earnings. This examination is important because the internal audit function (IAF) is uniquely positioned to provide experiences that could influence future managerial behavior, including limiting the potential negative repercussions of earnings management. We find that firms with managers that have internal audit experience are associated with lower real earnings management (REM) but not accruals‐based earnings management. Effects are strongest when managers with internal audit experience have greater power or currently hold financial roles, or when there are a greater number of managers with internal audit experience. The results are robust to including firm fixed effects, using entropy‐balancing and performance‐matching approaches, using a subsample of firm‐years required to have an IAF, using a subsample of firms for which we can measure IAF quality, and measuring internal audit experience at a previous employer. These results point to an important benefit of manager internal audit experience, as research suggests that REM is common, difficult to detect, not always within the scope of financial reporting regulators, and detrimental to future performance.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".