Impact of Excess Auditor Remuneration on the Cost of Equity Capital around the World
Bibliographic record
Abstract
This study examines the relation between excess auditor remuneration and the implied required rate of return (IRR hereafter) on equity capital in global markets. We conjecture that when auditor remuneration is excessively large, investors may perceive the auditor to be economically bonded to the client, leading to a lack of independence. This perceived lack of independence increases the information risk associated with the credibility of financial statements, thereby increasing IRR. Consistent with this notion, we find that IRR is increasing in excess auditor remuneration, but only in countries with stronger investor protection. Finding evidence of a relation only in stronger investor protection countries is consistent with the more prominent role of audited financial statements for investors' decisions in these countries. In settings in which investors are less likely to rely on audited financial statements and instead rely on alternative sources of information (i.e., in countries with weaker investor protection), the impact of client-auditor bonding should have less of an effect on investors' decisions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".