Mandatory <scp>IFRS</scp> Adoption and Financial Statement Comparability
Bibliographic record
Abstract
This study examines whether mandatory adoption of International Financial Reporting Standards ( IFRS ) leads to capital market benefits through enhanced financial statement comparability. U.K. domestic standards are considered very similar to IFRS , suggesting any capital market benefits observed for U.K.‐domiciled firms are more likely attributable to improvements in comparability (i.e., better precision of across ‐firm information) than to changes in information quality specific to the firm (i.e., core information quality). If IFRS adoption improves financial statement comparability, we predict this should reduce insiders' ability to benefit from private information. Consistent with these expectations, we find that abnormal returns to insider purchases ― used to proxy for private information ― are reduced following IFRS adoption. Similar results obtain across numerous subsamples and proxies used to isolate IFRS effects attributable to comparability. Together, the findings are consistent with mandatory IFRS adoption improving comparability and thus leading to capital market benefits by reducing insiders' ability to exploit private information.
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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 | 0.009 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".