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Record W2905155338 · doi:10.1111/1911-3846.12427

Audit Firm Tenure, Bank Complexity, and Financial Reporting Quality

2018· article· en· W2905155338 on OpenAlexvenueno aff
Brian Bratten, Monika Causholli, Thomas C. Omer

Bibliographic record

VenueContemporary Accounting Research · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
FundersUniversity of Nebraska-LincolnUniversity of Kentucky
KeywordsAuditBusinessQuality (philosophy)AccountingQuality auditAssociation (psychology)Affect (linguistics)Going concernFinanceAuditor's reportPsychology

Abstract

fetched live from OpenAlex

ABSTRACT Theory from organizations and economics research posits that in an inter‐organizational relationship, both parties invest in relationship‐specific knowledge, which in turn facilitates the effectiveness of the relationship while strengthening the attachment between the parties. In complex settings where there are more opportunities for knowledge creation, the investments will be larger and the attachment stronger. Because banks are complex institutions that present unique challenges to auditors, we suggest that effective audits critically depend on the accumulation of significant investments in client‐specific expertise through a long association with the client. We find a positive association between audit firm tenure and financial reporting quality, and this association is particularly strong in banks that are more complex. Also, contrary to recent research we find that benefits of audit firm tenure for complex banks accrue even for long tenure and are not limited to medium tenure. Our findings largely support the notion that a long relationship with the client reflects the underlying demand for expertise, which is critical for high‐quality audits of complex organizations. Imposing short‐term limits on audit firms would adversely affect the investments in client‐specific expertise especially in the cases where this expertise is needed the most. Our findings do not support calls for mandatory audit firm rotation for large complex institutions.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.092
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.349
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.092
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.003
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.134
GPT teacher head0.362
Teacher spread0.229 · 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

Labeled directly by 2 models reading the full record.

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

Citations92
Published2018
Admission routes1
Has abstractyes

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