Effect of the Adoption of IFRS on the Information Relevance of Accounting Profits in Brazil
Bibliographic record
Abstract
This study aimed to assess the effect of adopting the International Financial Reporting Standards (IFRS) in Brazil on the information relevance of accounting profits of publicly traded companies. International studies have shown that the adoption of IFRS improves the quality of accounting information compared with domestic accounting standards. Concurrent evidence is sparse in Brazil. Information relevance is understood herein as a multidimensional attribute that is closely related to the quality and usefulness of the information conveyed by accounting profits. The associative capacity and information timeliness of accounting profits in relation to share prices were examined. Furthermore, the level of conditional conservatism present in accounting profits was also analyzed because according to Basu (1997), this aspect is related to timeliness. The study used pooled regressions and panel data models to analyze the quarterly accounting profits of 246 companies between the first quarter of 1999 and the first quarter of 2013, resulting in 9,558 quarter-company observations. The results indicated that the adoption of IFRS in Brazil (1) increased the associative capacity of accounting profits; (2) reduced information timeliness to non-significant levels; and (3) had no effect on conditional conservatism. The joint analysis of the empirical evidence from the present study conclusively precludes stating that the adoption of IFRS in Brazil contributed to an increase the information relevance of accounting profits of publicly traded companies.
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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 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".