An Empirical Analysis of the Bond Market Behavior and Cointegration in the Selected APEC's Countries
Bibliographic record
Abstract
This article examines the behavior of Treasury bond rates in Asia-Pacific Economic Cooperation’s countries. Granger causality tests based on the vector error correction model (VECM) suggest bidirectional Granger causalities between changes in (i) the Canadian and Malaysian Treasury bond rates, (ii) the Canadian and New Zealand bond rates, (iii) the US and Malaysian Treasury bond rates, and (iv) the South Korean and Malaysian Treasury bond rates. The results also reveal unidirectional Granger causalities from changes in (i) the Canadian to US Treasury bond rates, (ii) the South Korean to New Zealand and US Treasury bond rates, (iii) the Malaysian to New Zealand and Thai Treasury bond rates, (iii) the Thai to New Zealand and South Korean Treasury bond rates, and (iv) the US to New Zealand Treasury bond rates. The Granger causality test based on the augmented vector autoregressive (VAR) procedure yields largely similar results from VECM. These empirical findings may be attributable to differences in economic policies, governance, culture, and other institutional arrangements in each of these countries. The empirical results are important for investors and traders since they can use past information in one country to predict prices and returns in the future in other countries.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".