Corporate risk disclosures in turbulent times: An international analysis in the global financial crisis
Bibliographic record
Abstract
Abstract Focusing on the global financial crisis period, this paper examines risk disclosure patterns and outcomes in a cross‐country setting. We build on prior risk disclosure literature and draw upon institutional and agency‐based theoretical lenses to investigate the nature, comprehensiveness, evolution, and quality of disclosed risk information for matched samples of manufacturing firms in the United States, Canada, Germany, and China (Chinese Hong Kong‐listed firms). The results show a high degree of heterogeneity in risk disclosure behavior and volume among the sample firms attributed to both institutional differences and corporate reporting incentives in the study period. Furthermore, we document significant associations between risk proxies, risk disclosures, and firm market performance suggesting that corporate risk disclosures are potentially informative and useful to investors and other stakeholders. The paper highlights the important joint role of corporate incentives and legal institutions in interpreting and implementing accounting standards and stock exchange listing regulations around the world and during turbulent times.
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How this classification was reachedexpand
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".