The relation between innovation and earnings management: evidence for the UK
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper seeks to investigate the potential utilisation of research and development expenses by executives of innovative firms in the UK economy as a means of manipulating financial statement users. This study uses discretionary accruals and abnormal activities as proxies for earnings management and research and development as a proxy for innovation. This study finds dissimilar results for the discretionary accrual and abnormal activity models, it conducts additional analysis that accounts for the innovation to beat the earnings group, and refers to this group as the 'downward' group; another analysis accounts for the innovation to reduce earnings, and refers to this group as the 'upward' group. The results suggest that there is a negative association between discretionary accruals and downward innovation and finds a similar relationship in abnormal activities and the downward group, which indicates the referential value of beating earnings over innovation. This study also documented that innovative firms engage more in manipulation than non-innovative firms.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 it