Capital Structure, Earnings Management, and Sarbanes-Oxley: Evidence from Canadian and U.S. Firms
Bibliographic record
Abstract
SYNOPSIS I examine Sarbanes-Oxley's (SOX) effect on capital structure. I find that SOX is associated with higher long-term debt ratios, as firms listed in the U.S. raise their long-term debt ratios by 2 to 3 percentage points. This finding is consistent with the idea that, although the reduction in information asymmetry associated with SOX could prompt managers to increase equity financing, debt is still safer and less costly than equity in the SOX era. Further analysis shows that the increase in debt occurs in the two quarters prior to SOX, suggesting that firms anticipate a higher cost of debt after SOX and acquire debt while it is relatively cheap. Also, firms that heavily (lightly) manage earnings prior to SOX use less (more) debt after SOX. This result is consistent with the view that firms that aggressively manage earnings before SOX reveal intrinsically weaker earnings after SOX, casting doubt on those firms' ability to repay debt and relegating those firms to issue equity for financing purposes. JEL Classifications: G32; G38. Data Availability: Data available upon request.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.012 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".