Voluntary accounting changes and analyst following
Bibliographic record
Abstract
Purpose – This study aims to examine the relation between voluntary accounting changes (VACs) and analyst following. Design/methodology/approach – A sample of firms was collected with VACs in the period from 1994 to 2008 and their major competitors, as well as industry benchmarking firms without accounting changes. The authors then investigated how VACs affect analysts’ following decisions given accounting choice heterogeneity. Findings – The findings demonstrate that VAC is negatively associated with analysts’ following decisions. Such association becomes stronger after taking into account accounting choice heterogeneity before and after VACs. Originality/value – This study contributes to the literature in the economic consequences of VACs and suggests that analysts presumably are able to comprehend the differences in accounting choices. However, the additional level of effort and the concern of manipulation may affect analysts’ behavior. This study documents whether VAC results in different accounting choices from the firm’s major competitors or industry benchmarking firms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.010 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".