Strategic Entry Decisions, Accounting Signals, and Risk Management Disclosure*
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
ABSTRACT This study provides evidence that hedge accounting information under Statement of Financial Accounting Standards (SFAS) 133, Accounting for Derivative Instruments and Hedging Activities , is related to rivals' market entry decisions. Documenting accounting information's relevance to competition decisions requires context‐specific settings. Using data for the airline industry in the United States, I predict and find that entrants are less likely to enter routes in which incumbents report higher accumulated other comprehensive income from fuel hedging, an indication of lower future operating costs. As predicted, this relation is stronger after the adoption of SFAS 161, Disclosure about Derivative Instruments and Hedging Activities , in 2008, a systemic shock that significantly increases risk management disclosure requirements. The findings illustrate the product market relevance of hedge accounting signals and disclosure in the US airline industry and extend the understanding of SFAS 133 and SFAS 161 beyond the capital markets.
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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 | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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