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Record W4396701508 · doi:10.1108/jaee-09-2023-0304

The impact of institutional environment on auditor reporting: evidence from China's anti-corruption campaign

2024· article· en· W4396701508 on OpenAlexaff
Guoping Liu, Jerry Sun

Bibliographic record

VenueJournal of Accounting in Emerging Economies · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsUniversity of WindsorToronto Metropolitan University
Fundersnot available
KeywordsLanguage changeChinaBusinessAuditAccountingPolitical scienceLaw

Abstract

fetched live from OpenAlex

Purpose The purpose of this study is to examine whether the institutional environment influences auditor reporting. Design/methodology/approach This study employs China's anti-corruption campaign as an exogenous shock to its institutional environment and compares auditors' issuance of modified audit opinions (MAOs) to small-profit clients before and during the campaign. Findings This study documents that small-profit clients were more likely to receive MAOs during the anti-corruption campaign period than before, indicating that auditors issued more conservative audit opinions to small-profit clients because of the anti-corruption campaign. Additionally, this study finds that increased auditor conservatism was more pronounced for auditors of large clients. Practical implications This study suggests that a weak institutional environment adversely affects auditor conservatism. This offers valuable insights for governments and regulators to improve the audit environment and for audit firms to enhance auditors' integrity and independence. Originality/value This study contributes to the research on institutional environments and auditing by observing a unique exogenous event.

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)0.003
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.312
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.258
Teacher spread0.242 · 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 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

Citations4
Published2024
Admission routes1
Has abstractyes

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