The impact of International Financial Reporting Standards (IFRS) adoption and IFRS renouncement on audit fees: The case of Switzerland
Bibliographic record
Abstract
Several studies have shown that International Financial Reporting Standards (IFRS) adoption is associated with higher audit fees. We provide additional evidence on this issue by analyzing the Swiss context, which is particularly suitable for two reasons. First, it allows a better estimation of the impact of IFRS adoption on audit fees because the choice of accounting standards (IFRS, US generally accepted accounting principles [GAAPs] or Swiss GAAPs) is left to companies. Accordingly, comparisons can be made within the same institutional context. Second, it is also possible to measure the impact of IFRS renouncement on audit fees because Swiss companies following IFRS can switch back to Swiss GAAPs at any time. Based on a hand‐collected database including 1,651 firm‐year observations over 15 years, we show that, with the exception of very large companies, firms using IFRS pay higher audit fees. We also find that firms switching to IFRS incur additional audit fees in the year preceding the change. By contrast, the return to local GAAPs does not result in lower audit fees, which confirms the stickiness of audit fees reported by several prior studies.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".