Determinants of the corporate decision to record goodwill impairment loss: Canadian evidence
Bibliographic record
Abstract
The initial application of the new goodwill accounting standard enables firms to record an actual goodwill impairment loss in their books without affecting their earnings. The recording of a goodwill impairment loss indicates that the acquiring firm paid an excessive premium at the time of the business combination, and that this goodwill does not enable it to generate future earnings. This study is based on the hubris hypothesis and governance structure and is aimed at predicting whether managers will choose to record a goodwill impairment loss. Using a sample of high-tech Canadian firms, we noted that firms where: (1) managers showed excessive confidence, (2) the CEO cumulates the function of chairman and (3) the dominant shareholder was also a manager tended to record a goodwill impairment loss. The results are consistent with those of previous studies, which suggest that systematic differences exist between firms that choose alternative accounting methods. Hence, the results provide further support in the developing framework of a positive theory of accounting methods.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".