Effects of Audit Quality on Earnings Management and Cost of Equity Capital: Evidence from China*
Bibliographic record
Abstract
We examine the effects of audit quality on earnings management and cost of equity capital for two groups of Chinese firms: state-owned enterprises (SOEs) and non-state-owned enterprises (NSOEs). The differences in the nature of the ownership, agency relations and bankruptcy risks lead SOEs to have weaker incentives than NSOEs to engage in earnings management. As a result, the effect of audit quality in reducing earnings management will be greater for NSOEs than for SOEs. In addition, investors’ pricing of information risk as reflected in the cost of equity capital will be more pronounced for NSOEs than for SOEs with high and low audit quality. We find empirical evidence consistent with these hypotheses. Our findings indicate that (1) while high-quality auditors play a governance role in China, that role is limited to a subset of firms, and (2) even under the same legal jurisdiction, the effects of audit quality (in the form of lower earnings management and cost of equity capital) vary across firms with different ownership structures. Our study extends prior research by focusing on the economic consequences of SOEs’ and NSOEs’ auditor choices and underscores the importance of controlling for ownership type when conducting audit research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".