U.S. Evidence from D&O Insurance on Accounting-Related Agency Costs: Implications for Country-Specific Studies
Bibliographic record
Abstract
ABSTRACT Many studies use country-specific evidence to investigate research questions of broad interest due to data availability or to exploit an exogenous event that allows identification. One such research stream largely examines Canadian directors' and officers' (D&O) insurance and finds that more coverage (i.e., higher limits) is negatively associated with financial reporting quality and positively related to litigation (accounting-related agency costs). However, the U.S. and Canada differ on key issues relevant to securities litigation and D&O insurance. Thus, we predict and find that premiums, rather than limits, provide information about U.S. accounting-related agency costs. Nonetheless, the incremental information provided by premiums about accounting-related agency costs is limited, and audit fees provide better information about these agency costs. Thus, although researchers argue for disclosure of U.S. D&O insurance information, the usefulness of such disclosures may be limited because audit fees are already disclosed. Our findings suggest caution in broadly generalizing country-specific studies.
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".