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Record W4391175766 · doi:10.1111/1911-3846.12936

Audit firm tenure disclosure and nonprofessional investors' perceptions of auditor independence: The mitigating effect of partner rotation disclosure

2024· article· en· W4391175766 on OpenAlexvenueno aff
Sarah Judge, Brian M. Goodson, Chad M. Stefaniak

Bibliographic record

VenueContemporary Accounting Research · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
FundersUniversity of South CarolinaClemson University
KeywordsAccountingAuditBusinessIndependence (probability theory)Auditor independencePerceptionAuditor's reportPsychologyJoint auditInternal audit

Abstract

fetched live from OpenAlex

Abstract In 2017, the PCAOB began requiring audit firm tenure disclosure within the audit report for SEC registrant clients. Many commenters raised the concern that prominent disclosure of firm tenure would lead investors to inappropriately infer a negative relation between audit quality and long tenure. This is particularly troubling given that empirical evidence generally does not support this concern. In our first experiment, we predict and find that disclosing an audit firm's long tenure within the audit report increases investors' perceptions that the audit firm's independence was impaired while conducting the audit. However, we also identify an intervention that mitigates the effects of disclosing long tenure—an accompanying disclosure in the audit report of the firm's adherence to the SEC's mandatory partner rotation requirement. We find that such a disclosure moderates the effect of long tenure disclosure such that in the absence (presence) of a partner rotation disclosure, investors do (do not) perceive increased independence impairment when long firm tenure is disclosed. In a second experiment, we predict and find that long firm tenure disclosure reduces investors' preference to invest in an otherwise quantitatively optimal investment and that this relation is driven, in part, by perceptions of independence impairment. Again, this result is attenuated by partner rotation disclosure. Our results should be useful to regulators in understanding the effects of their disclosure mandate and to audit firms in understanding a practical way in which they might mitigate the implications of such effects.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.022
GPT teacher head0.312
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2024
Admission routes1
Has abstractyes

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