Is Audit Committee Equity Compensation Related to Audit Fees?*
Bibliographic record
Abstract
ABSTRACT Section 301 of the Sarbanes‐Oxley Act (SOX) implicitly assumes that audit committees can independently determine audit fees. Critics of section 301 have questioned this assumption in particular, and the efficacy of section 301 more generally. In response, the SEC issued a concept release in 2015 calling for public disclosure of the process that audit committees follow for determining auditor compensation. Motivated by these calls and the widespread use of stocks and options to compensate firms' independent directors, we examine the relation between equity compensation granted to audit committee members and audit fees. Using a sample of 3,685 firm‐year observations during 2007–2015, we find a negative relation between audit committee equity compensation and audit fees, consistent with larger equity pay inducing audit committee members to compromise independence by paying lower audit fees. These findings are robust to controlling for endogeneity, firm size, alternative measures of equity compensation, alternative samples, and an alternative treatment of extreme values. We further show that larger equity compensation is associated with lower earnings quality. We also find that the negative effect of equity compensation on audit fees is stronger when city‐level audit market competition is high. However, this negative relation disappears when (i) firms face high litigation risk, (ii) auditors have stronger bargaining power, (iii) the audit committee includes a high proportion of accounting experts, and (iv) auditors are industry experts. Our results are relevant for regulators and investors.
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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 | 0.084 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".