Does the Identity of Engagement Partners Matter? An Analysis of Audit Partner Reporting Decisions
Bibliographic record
Abstract
Abstract This study examines the persistence and economic consequences of variations in reporting style across audit partners in individual engagements. Our results show that both aggressive and conservative audit reporting, measured by the pattern of prior Type 2 and Type 1 audit reporting error rates in auditor‐specific clienteles, persist over time and extend to other clients of the same partner. Analyses of abnormal accruals and persistence of client firms’ accrual estimates corroborate this finding, and hold both for private and publicly listed companies. Further, our results also show that the market penalizes client firms susceptible to aggressive audit partner reporting decisions. In particular, we find that our proxies for aggressive audit reporting are related to higher interest rates, worse credit ratings and less favorable forecasts of insolvency for private client companies, and a lower Tobin's Q for publicly listed client companies. Collectively, these results imply that audit partner aggressive or conservative reporting is a systematic audit partner attribute and not randomly distributed across engagements.
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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 | 0.006 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".