Acquirer Internal Control Weaknesses in the Market for Corporate Control
Bibliographic record
Abstract
Abstract This paper examines how disclosures regarding internal controls, required by sections 302 and 404 of the Sarbanes‐Oxley Act of 2002 (SOX), affect the market for corporate control. We hypothesize that acquirers with internal control weaknesses (ICWs) make suboptimal acquisition decisions based on poor‐quality information generated by their ineffective controls over financial reporting. We expect that such acquirers will be more likely to misestimate the value of their targets or the potential synergies from mergers, thereby overpaying for completed deals. Using a treatment sample of acquisitions made by acquirers that have disclosed ICWs and two matched control samples without ICW disclosures, we document that ICW acquirers experience a substantially more negative market response to acquisition announcements and have lower future performance than the two matched control samples without ICW disclosures. Overall, our results suggest that ineffective internal controls hinder decision making related to mergers and acquisitions (M&A).
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".