Auditor Materiality Threshold and Audit Quality—Evidence from the Revised ISA 700 in the United Kingdom
Bibliographic record
Abstract
SYNOPSIS Using a broad sample of U.K. firms that are required to disclose auditor materiality thresholds under the International Standards on Auditing (United Kingdom and Ireland) 700, we examine whether the auditor materiality threshold is associated with audit quality. We document that a lower materiality threshold is associated with higher audit quality, as measured by lower absolute discretionary accruals, higher accruals quality, and a lower propensity to just meet or beat analysts’ earnings expectations. We also find some evidence that the negative association between the materiality threshold and audit quality is attenuated when the audit committee is more effective and when the auditor is more economically dependent on the client, and the negative association is more pronounced when management has a stronger incentive to manage earnings. Overall, our study extends the limited studies on large-sample archival evidence on the implications of audit materiality thresholds on audit outcomes. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: M40; M41; 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 | 0.005 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".