The Impact of IFRS Adoption on Accounting Conservatism in the European Union
Bibliographic record
Abstract
Purpose –The purpose of this study is to analyze mandatory IFRS adoption’s impact on accounting conservatism. Design/methodology/approach – Our empirical study is conducted on a sample of 15 European countries, observed from the year 2000 to 2010. We analyze both conditional and unconditional conservatism, which we measured, respectively, by timely bad news recognition as compared to recognition of good news and discretionary accruals. Findings – The results of the empirical study confirm a significant reduction of accounting conservatism in the IFRS adoption period. This reduction is affected by the accounting model prevailing in a particular country. Moreover, the study shows a reduction of the gap between the two accounting models in the post-IFRS adoption period. Practical implications – The results obtained would be relevant for many decision makers such as investors, standard setters, IASB, European Union countries as well as those wishing to adopt International Standards. Originality/value – Our study complements and enriches the existent literature about the impact of the International Standards adoption. It dresses an important issue in a relatively long period to better assess the impact of IFRS.
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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 | 0.008 | 0.033 |
| 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 | 0.002 | 0.001 |
| Open science | 0.001 | 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".