Regulatory Spillovers in Common Audit Markets
Bibliographic record
Abstract
We find that Sarbanes–Oxley (SOX) had two significant effects on the audit market for nonpublic entities. The first short-run effect stems from inelastic labor supply coupled with an audit demand shock from public companies. As a result, private companies reduced their use of attested financial reports in bank financing by 12%, and audit fee increases for nonprofit organizations (NPOs) more than doubled. The second long-run effect was a transformation in the audit supply structure. After SOX, NPOs were less likely to match with auditors most exposed to public companies, whereas auditors increasingly specialized their offices based on client type. Audit market concentration for NPOs dropped by more than one-half within five years of SOX and remained at this level through the end of our sample in 2013, whereas the number of suppliers increased by 26%. Our results demonstrate how regulation directed at public companies generates economically important spillovers for nonpublic entities. This paper was accepted by Suraj Srinivasan, accounting.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 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".