Capital market liberalization and auditors' accounting adjustments: Evidence from a quasi‐experiment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Using a shock to the Chinese capital market and unique and detailed audit‐adjustment data, this paper investigates the effect of a capital market liberalization program on auditors’ adjustments to their clients’ financial reports. Employing difference‐in‐differences tests with propensity score matching and firm fixed effects (FE), we find that the capital market liberalization induced by the implementation of the Shanghai‐Hong Kong Stock Connect affects auditors’ professional judgment and leads to audit‐adjustment changes stimulated by greater reputational and litigation risks for auditors. Specifically, while the liberalization significantly decreases the frequency and magnitude of upward audit adjustments, the probability of downward adjustments remains the same in most cases. Further evidence shows that the effect is more pronounced for companies with high trading volume from Hong Kong investors, audited by the largest audit firms and with low financial transparency.
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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 | 0.001 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.009 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it