Accounting Comparability and Economic Outcomes of Mandatory <scp>IFRS</scp> Adoption
Bibliographic record
Abstract
Abstract This study examines the associations between four economic outcomes of the 2005 mandatory adoption of International Financial Reporting Standards (IFRS) and concurrent changes in two important accounting constructs, accounting comparability and reporting quality. My primary purpose is to evaluate the relative importance of cross‐country accounting comparability and firm‐specific reporting quality in explaining previously documented increases in Tobin's Q, stock liquidity, analyst forecast accuracy, and analyst forecast agreement following IFRS adoption. Given that improvements in both comparability and reporting quality are primary stated objectives of the International Accounting Standards Board (IASB), it is important to understand their relative roles in shaping the information environment of financial statement users following IFRS adoption. Using 1,861 first‐time adopters in 23 countries, I find that firms with a larger improvement in comparability have larger increases in Q, liquidity, forecast accuracy, and forecast agreement following adoption, relative to other adopters. In contrast, improvements in reporting quality around adoption appear to have only a second‐order effect that is generally limited to Q effects among those adopters with concurrent improvements in comparability. These results are robust to alternative design and variable specifications. Finally, I continue to find these results for samples restricted to countries with weaker pre‐adoption institutional environments and countries that did not initiate proactive financial statement reviews, indicating that strong institutions and regulatory improvements are not driving the results. Overall, my results suggest that improvements in cross‐country accounting comparability played an important role in the previously documented economic benefits that accrued to 2005 mandatory IFRS adopters.
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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 | 0.046 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".