Does mandatory IFRS adoption affect large and small public firms' accounting quality differently? Evidence from Canada
Bibliographic record
Abstract
Canada adopted International Financial Reporting Standards (IFRS) in 2011. We investigate the impact of this mandatory change by examining whether value relevance and non-market-based accounting information changed for a comprehensive set of Canadian companies on the Toronto Stock Exchange (TSX). Our findings reveal the effects of IFRS adoption are not consistent across all firms as demonstrated by a minimal change in value relevance for large firms, but a significant increase for small firms. These differences are primarily attributed to the weakening (strengthening) relationship of book value to stock price for large (small) firms and a strengthening (weakening) relationship of earnings to stock price for large (small) firms. This suggests the goal of IFRS in providing improvement to the balance sheet is only achieved for small firms in Canada. For the non-market-based accounting quality measures of earnings persistence, earnings smoothing, earnings discretion, and the frequency of small profits to losses, the findings are mixed for large firms, but improve for small firms after IFRS adoption.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".