Analysis of the seeds of the debt crisis in Europe
Bibliographic record
Abstract
This paper presents an analysis of the seeds of the recent debt crisis that occurred in the Eurozone area using a variant of Fleming and Stein [2004. “Stochastic Optimal Control, International Finance and Debt.” Journal of Banking and Finance, 28: 979–996] model. This model has two risk drivers arising from uncertainties in the return on capital and the effective rate of return on net foreign assets. Given the risk drivers, we model the net worth value process of an economy under a stochastic setting and show that opening to the rest of the world by pursuing the growth maximizing leverage strategy is better than remaining closed, as that strategy enhances the growth of the net worth process. Second, we provide an extra condition to show when the excessive leverage poses a threat to the sustainable growth of an economy. In this way, we improve the model introduced by Fleming and Stein as a signal of possible debt crises. Finally, we conduct an econometric analysis for the group of countries considered under this study, and show that there is a long-run relationship between the capital stock and the total external debt justifying the use of the structural model we employ.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".