Gender Differences in Financial Reporting Decision Making: Evidence from Accounting Conservatism
Bibliographic record
Abstract
Abstract This paper investigates the effect of CFO gender on corporate financial reporting decision making. Focusing on firms that experience changes of CFO from male to female, the paper compares the firms' degree of accounting conservatism between pre‐ and post‐transition periods. We find that female CFO s are more conservative in their financial reporting. In addition, we find that the relation between CFO gender and conservatism varies with the level of various firm risks, including litigation risk, default risk, systematic risk, and CFO ‐specific risk such as job security risk. We further find that the risk aversion of female CFO s is associated with less equity‐based compensation, lower firm risk, a higher tangibility level, and a lower dividend payout level. Overall, the study provides strong support for the notion that female CFO s are more risk averse than male CFO s, which leads female CFO s to adopt more conservative financial reporting policies.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".