Capitalization of In‐Process Research and Development under SFAS 141R and Information Asymmetry
Bibliographic record
Abstract
ABSTRACT This study examines the effect of capitalizing acquired in‐process research and development (IPR&D) on information asymmetry under Statement of Financial Accounting Standards No. 141 (R) (SFAS 141R). SFAS 141R requires acquirers to fully recognize IPR&D at fair value as an indefinite‐lived intangible asset until completion or discontinuation of the project. Prior research suggests IPR&D capitalization will result in an improvement in the information environment. In contrast, we find no evidence that capitalizing IPR&D improved the information environment for IPR&D acquirers. Instead, most of our results suggest no significant change in information asymmetry for IPR&D acquirers during the post‐SFAS 141R period, relative to the concurrent changes for non‐IPR&D acquirers. In cases in which the results suggest a statistically significant increase, the economic magnitudes are relatively small. In addition, we find no evidence that IPR&D acquirers engaged in increased classification shifting between IPR&D and goodwill during the post‐SFAS 141R period, as critics of capitalization had feared.
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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 | 0.015 | 0.076 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".