The Sarbanes-Oxley Act and corporate acquisitions
Bibliographic record
Abstract
Purpose The purpose of this paper is to analyze and compare the performance of corporate acquisitions between the pre- and post-SOX periods, using both short-term and long-term analyses. Design/methodology/approach The sample includes 9,463 mergers and tender offers undertaken by publicly traded US firms between 1996 and 2009. The authors used the standard event study methodology for short-term performance analysis; Berkovitch and Narayanan (1993) method to identify merger motives; and standard benchmark adjusted return on assets (sales) (Barber and Lyon, 1996) and buy-and-hold abnormal returns (Mitchell and Stafford, 2000) to analyze long-term performance. Findings Compared to the pre-SOX period, US acquirers experience significantly higher announcement returns in the post-SOX period; the results are robust to various controls like bidder, target and deal characteristics, bidder management quality, and product market competition. Similar results (in favor of post-SOX US acquirers) are obtained with long-term post-acquisition operating and stock performance analyses. Research limitations/implications This paper only addressed domestic acquisitions. Originality/value This paper adds to the growing body of research on the impact of SOX on publicly traded US corporations. By examining corporate acquisitions, an important long-term investment decision for a firm, the paper shows that despite the complex nature of SOX, substantial compliance costs and the unintended negative consequence it engendered, the act had a beneficial impact in an important area of corporate finance.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".