Empirical Results for Some Monetary Areas According to Optimum Currency Area Criteria
Bibliographic record
Abstract
The euro area is the biggest monetary union in the World. In post-crisis time, the possibilities of creation a new monetary union are discussed again. The aim of this article is to evaluate, according to OCA criteria, an appropriateness of selected countries for a membership in a monetary union or for creation new monetary union. The second aim is to confront the existing monetary union - the euro area, with two potential monetary areas - NAFTA and MERCOSUR. The criteria are based on the OCA theory and partly on the so called OCA index. According to the results, there are countries (so called core countries) such as Austria or Luxemburg which reach satisfactory values. On the other hand there are countries such as Estonia, Finland, Latvia, Greece or Italy which reach worse values. Quite surprisingly, the values of most indicators (except for DISSIM) have worsened since the crisis in the euro area. It seems to be convenient for both Canada and Mexico to adopt a common currency with the USA. In case of MERCOSUR we could barely find a pair of countries with better values compare with euro area's all-time average.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".