Value relevance of discretionary accruals under environmental uncertainty: the incidence of IFRS and the country's legal regime
Bibliographic record
Abstract
This paper studies whether IFRS adoption and the country's legal regime affect the value relevance of discretionary accruals under environmental uncertainty (measured by sales variability). The sample includes France and UK domiciles, providing a code/common law legal regime partition. We show that IFRS improve the value relevance of discretionary accruals to a larger extent in France than in the UK. Under local GAAP, discretionary accruals are more valued in the UK than in France while no significant difference is observed under IFRS, suggesting a marginal effect of the country%s legal regime. Under high uncertainty, results suggest that IFRS improve investors' ability to distinguish between earnings managed opportunistically and earnings management that provides a credible signal about future cash flows. Overall, IFRS would allow stock market participants to better assess properties of earnings management while reducing stock pricing discrepancies between code law and common law regimes.
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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 | 0.004 | 0.035 |
| 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 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".