Predicción de quiebras empresariales en economías emergentes: uso de un modelo logístico mixto
Bibliographic record
Abstract
Este trabajo replica y adapta el modelo de Jones y Hensher (2004) a los datos de una economía emergente con el propósito de evaluar su validez externa. Se compara el desempeño del modelo logístico estándar en relación con el modelo logístico mixto para predecir el riesgo de crisis en el periodo 1993-2000, utilizando estados contables de empresas argentinas y ratios de nidos en estudios de Altman y Jones y Hensher. Como en estudios anteriores, rentabilidad, rotación, endeudamiento y flujo de fondos operativos explican la probabilidad de crisis financiera. La contribución de esta nueva metodología reduce la tasa de error del tipo I a un 9 %. Se demuestra que el modelo logístico mixto, que tiene en cuenta la heterogeneidad no observada, supera ampliamente el desempeño del modelo logístico estándar.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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; both teacher heads agree on what is shown here.
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".