Future Nonaudit Service Fees and Audit Quality
Bibliographic record
Abstract
Prior to the Sarbanes–Oxley Act of 2002, audit partners experienced economic pressure to grow revenue from the sale of nonaudit services to their audit clients. To an auditor who is highly rewarded for revenue generation and growth, nonaudit services may represent a particularly strengthened economic bond with the client. Prior research shows that, in general, nonaudit service fees received in the current period do not impair audit quality. We examine a different setting. We propose that auditor independence can become impaired, and audit quality compromised, when clients that currently purchase relatively low amounts of nonaudit services, increase their purchases of nonaudit services from the auditor in the subsequent period. We test our prediction in the context of earnings management as a proxy for audit quality, measured by (a) performance‐adjusted discretionary accruals and (b) classification shifting of core expenses. Our results indicate that prior to the Sarbanes‐Oxley Act, rewards to the auditor in the form offutureadditional nonaudit service fees from current‐year high fee‐growth‐opportunity clients adversely affects audit quality. This effect is particularly strong among companies with powerful incentives to manage earnings. Our findings indicate that regulators should consider the multiperiod nature of the client–auditor relationship when contemplating policies that restrict nonaudit services, as well as the overall environment in which audit partners operate. This might include partner compensation arrangements that put pressure on audit partners to focus on increasing revenue at the expense of audit quality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".