Optimum Currency Areas within the US and Canada a Data Analysis Approach
Bibliographic record
Abstract
Over the last few decades Robert Mundell’s theory (1963) of Optimum Currency Areas (OCA) has attracted significant attention between researchers and policy makers especially after the formation of the European Monetary Union and the debate over whether the eurozone countries actually consist an OCA. In this paper, we take this debate to the area that was originally the subject of Mundell’s motivation: the US and Canada. We employ the methodology of Correspondence Analysis and Hierarchical Cluster Analysis, in a sample of macroeconomic data from the fifty US states and ten Canadian provinces for 2009 in an effort to investigate whether the current currency split between north (Canada) and south (the US) is an OCA or possibly another split may be more appropriate. Our results show that three OCAs are identified within US states and Canadian provinces: one that includes regions of eastern US and Canada, one that includes regions of central-eastern and eastern US and Canada and finally one with regions of western US and Canada.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".