Does the Addition of Explicit Clarification of Auditor Independence Statement to the Auditor’s Report Matter to Equity Analysts?
Bibliographic record
Abstract
The Public Company Accounting Oversight Board (PCAOB) adopted a new auditing standard to enhance the relevance and usefulness of the auditor’s report. One of the changes introduced in the new reporting model is the addition of a statement that explicitly clarifies the auditor’s independence (AS 3101.09.g). We administer a survey to investigate whether explicitly clarifying the auditor’s independence in the auditor’s report affects equity analysts’ perceptions of auditor independence, perceptions of financial reporting reliability, and their judgment when it comes to making stock recommendations to clients. A total of 123 equity analysts are recruited via Qualtrics for the study. The findings of the survey provide evidence that corroborates the position of the PCAOB that explicit clarification of auditor independence provides relevant information useful to public users such as equity analysts. Our study is the first to evaluate equity analysts’ perceptions about auditor independence using the new PCAOB auditor reporting model regarding the explicit clarification of auditor independence in the auditor’s report. Our study contributes to research, practice, and policy.
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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 | 0.104 | 0.428 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".