Effects of IFRS on Accounting Information Quality: Evidence for Brazil
Bibliographic record
Abstract
Understanding the effects of the International Financial Reporting Standards (IFRS) on accounting quality is fundamental for policy makers and financial market players in general. This paper analyzes whether the adoption of IFRS in Brazil has had the impact on accounting informational quality. To this end, a differentiated empirical strategy was adopted based on two steps: first, a matching of voluntary adopters of norms and non-adopters by propensity score is performed to construct control groups. This is important to mitigate the selection bias problem. Second, the measures of value relevance, timeliness and conservatism of accounting information are estimated using panel data models. The period of analysis extends from 2006 to 2010, with annual information for the first stage and quarterly for the second. The results show a positive impact of international standards on the value relevance. However, for the measures of timeliness and conservatism, sufficient evidence was not found to indicate any impact on the group of companies evaluated.
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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 | 0.007 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".