Do Regional Integration Agreements Increase Business-Cycle Convergence? Evidence from Apec and Nafta
Bibliographic record
Abstract
Using monthly industrial sector data from January 1971 to March 2004, we test for business cycles convergence among the major APEC members: Japan, South Korea, Malaysia, Mexico, USA, and Canada. In addition, we examine the synchronization of business cycles among Australia, Japan, and South Korea, based on the quarterly data for the 1957-2003 period, as well as among the different economic sectors of the NAFTA countries from January 1970 through March 2004. We apply different techniques to identify business cycles. In particular, we propose a new trend-cycle decomposition method based on wavelet analysis. The results show that convergence of business cycles of Asia-Pacific countries is far from complete, but joining the APEC has increased the mean correlation of industrial production cycles of the member economies. On the other hand, although some economic sectors of the NAFTA countries already exhibited some degree of business cycle co-movement even during pre-NAFTA period, the volatility of pair-wise correlation of business cycles declined during NAFTA. In addition, we conclude that, in general, the transmission of business cycles is relatively slow, and, consequently, business cycles appear to be asynchronous.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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 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".