Contagion in the European Union: An Analysis of the Channels of Transmission
Bibliographic record
Abstract
This study analyzes contagion from the global financial crisis that began in August 2007 to the European Union (EU) crisis and uses a statistical approach to determine which channels were, and still are, important for contagion transmission in the European crisis. A logit regression is used to statistically determine which common contagion channels - trade linkages, the common creditor, portfolio investors and macroeconomic fundamentals – transmitted infection among the 27 EU countries. The results show that the macroeconomic fundamentals channel is the most important channel and specifically high levels of government and private debt along with a large current account deficit are the most important determinants of contagion. Additionally, the results suggest that the European crisis is at root a balance of payments crisis. Finally, the results predict that the country, beyond those that have already received assistance form the EU, ECB and IMF, that is most vulnerable to further contagion is Malta.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".