Conditional Conservatism and Debt versus Equity Financing
Bibliographic record
Abstract
Abstract Extant research suggests that conditional conservatism reduces information asymmetry between a firm and its shareholders as well as its debtholders. However, there is little evidence on whether conditional conservatism reduces information asymmetry differentially for shareholders and debtholders. We use the setting of a firm's choice between equity versus debt when it seeks a significant amount of external financing to examine this research question. We find that when firms raise a significant amount of external financing, the use of equity (versus debt) increases with the level of conservatism. We also find that the reduction in cost of equity associated with conservatism is greater for equity issuers than for debt issuers, but find no such difference when we examine cost of debt. In addition, we find that the positive effect of conservatism on the choice of equity issuance (versus debt issuance) is accentuated when the information asymmetry between the firm and its shareholders is more severe. Overall, our results suggest that conservatism reduces information asymmetry more between firms and shareholders than between firms and debtholders.
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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 | 0.006 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".