A Structural Balance Sheet Model of Sovereign Credit Risk
Bibliographic record
Abstract
Résumé Cet article étudie les écarts de crédit souverains à l’aide d’un modèle d’actifs contingents et d’une représentation bilantielle de l’économie souveraine. Les formules analytiques d’évaluation de la dette domestique, de la dette externe ainsi que de la garantie financière sont obtenues dans un cadre d’analyse où le taux de recouvrement est déterminé de manière endogène comme la solution d’un jeu stratégique de renégociation. L’approche permet de relier les écarts de crédit souverains à des facteurs macroéconomiques observables et, en particulier, prend en compte des effets de contagion au travers des secteurs industriel et bancaire. La performance d’évaluation ainsi que les prédictions concernant les déterminants des écarts de crédit sont testées avec succès sur l’économie brésilienne.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".