The Term Structure of Interest Rates: A Cointegration Analysis in the Non-Linear STAR Framework
Bibliographic record
Abstract
This paper analysis the term structure of interest rates for the Group of Seven (G7) countries. In addition to standard cointegration testing procedures, a cointegration test in a nonlinear smooth transition autoregression (STAR) framework developed by Kapetanios et al. (2006) is also employed. While the standard cointegration test results suggest the existence of cointegration relationship between short and long-term interest rates for Canada, France, Italy, Japan, and US data, these tests fail to establish a cointegration relationship for Germany and the United Kingdom. In case we take account of cointegration with non-linear adjustment, the results provide clear evidence of cointegration for all countries except Germany. Our finding implies that, especially in the case of UK, we may achieve important implications by taking account of possible nonlinearities. Overall, our findings support the proposition of expectation hypothesis for all of the G7 countries except Germany.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 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".