Accounting for Software Development Costs and Information Asymmetry
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
I investigate the impact of implementing SFAS No. 86, which provides an exception to the GAAP requirement of the immediate expensing of research and development (R&D), on information asymmetry. Using bid-ask spread and share turnover as proxies for information asymmetry, I find that after the introduction of SFAS No. 86, information asymmetry decreases for software firms relative to that of other high-tech firms. Within the software industry, I find that information asymmetry is significantly lower for firms that capitalize (capitalizers) than for those who expense (expensers) software development costs. Thus, accounting for software development costs per SFAS No. 86 reduces information asymmetry and, consequently, the cost of capital. As well, investors' uncertainty about the future benefits of software development costs is reduced when firms capitalize these costs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.005 |
| 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