The Importance of Partner Narcissism to Audit Quality: Evidence from Taiwan
Bibliographic record
Abstract
ABSTRACT Relying on the size of partner signatures in audit reports in Taiwan to measure their narcissism, we find that audit quality rises with partner narcissism. Our analysis also implies that changes in audit quality are positively associated with changes in partner narcissism stemming from mandatory partner rotation. We also find that the impact of partner narcissism on audit quality only manifests when auditor independence is more likely to be compromised, although it does not vary with engagement complexity. These results suggest that partner narcissism improves audit quality mainly through increased auditor independence, rather than auditor competence. Additionally, we document that although partner narcissism has no perceptible impact on the incidence of Type I going concern reporting errors, it is negatively associated with the probability of making a Type II error, implying that more narcissistic partners are less likely to succumb to client pressure to issue opportunistic reports. Data Availability: Data are available from public sources as identified in the text. JEL Classifications: M40; M42.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".