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Record W2080520925 · doi:10.1506/d171-8534-4458-k037

Do Investors Care about the Auditor's Economic Dependence on the Client?*

2006· article· en· W2080520925 on OpenAlexvenueno aff
Inder K. Khurana, K. K. Raman

Bibliographic record

VenueContemporary Accounting Research · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessAuditor independenceAuditAccountingRevenueCredibilityCorporate governanceAuditor's reportAudit substantive testExternal auditorCapital marketJoint auditFinanceInternal audit

Abstract

fetched live from OpenAlex

Abstract In this study, we investigate whether investor perceptions of the financial reporting credibility of Big 5 audits are related to the auditor's economic dependence on the client as measured by nonaudit as well as total (audit and nonaudit) fees paid to the incumbent auditor. We use the client‐specific ex ante cost of equity capital as a proxy for investor perceptions of financial reporting credibility and examine auditor fees both as a proportion of the revenues of the audit firm and as a proportion of the revenues of the audit firm's practice office through which the audit was conducted. Our findings suggest that both nonaudit and total fees are perceived negatively by investors' that is, the higher the fees paid to the auditor, the greater the implied threat to auditor independence, and the lower the financial reporting credibility of a Big 5 audit. Furthermore, our findings appear to be largely unrelated to corporate governance: investors do not perceive the auditor as compensating for weak governance. Separately, recent anecdotal evidence suggests that declining revenues from nonaudit services' as a result of recent regulatory restrictions” are being offset by substantial increases in audit fees. Other things being equal, rising audit fees imply higher profit margins for audit services, indicating that the audit function may no longer be a loss leader. Thus, to the extent that investors perceive total fees negatively, recent regulatory initiatives to limit nonaudit fees may not have adequately addressed the perceived, if not the actual, threat to auditor independence posed by fees.

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 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)0.005
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.309
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.004

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 head0.041
GPT teacher head0.284
Teacher spread0.243 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations167
Published2006
Admission routes1
Has abstractyes

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