Currency Area and Non-synchronized Business Cycles between the US and Puerto Rico
Bibliographic record
Abstract
Frankel and Rose (1997, 1998) state that greater intensity of trading leads to more highly correlated business cycles across countries. Since 2005 Puerto Rico, which belongs to the US currency area, has suffered from economic stagnation. This raises the issue of whether currency areas lead to synchronized business cycles or not. Following Vahid and Engle (1997), we use a test of codependence to examine the short-run co-movements in outputs and prices between the US and Puerto Rico. The outcomes indicate that both economies share a common non-synchronized business cycle. The response from Puerto Rico to temporary US shocks occurs at a lag of one quarter. In addition, Puerto Rican prices respond to temporary shocks to US prices with a lag of two quarters. Furthermore, the forecast error variance decomposition shows that the Puerto Rican economy is highly dependent on the US economy. All evidence suggests that currency areas do not lead to synchronized business cycles. However, even though Puerto Rico has a non-synchronized common cycle with the US, the results appear to be that the current economic struggle in Puerto Rico is a long-term one, instead of a short-term one.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".