The impact of institutional environment on auditor reporting: evidence from China's anti-corruption campaign
Bibliographic record
Abstract
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.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".