Irreducibility and structural cointegrating relations: an application to the G‐7 long‐term interest rates
Bibliographic record
Abstract
Abstract In this paper we examine the causal linkages between the G‐7 long‐term interest rates by using a new technique, which enables the researcher to analyse relations between a set of I(1) series without imposing any identification conditions based on economic theory. Specifically, we apply the so‐called Extended Davidson's Methodology (EDM), which is based on the innovative concept of an irreducible cointegrating (IC) vector, defined as a subset of a cointegrating relation that does not have any cointegrated subsets. Ranking the irreducible vectors according to the criterion of minimum variance allows us to distinguish between structural and solved relations. The empirical results provide support for the hypothesis that larger, more stable economies can achieve policy objectives more successfully by accommodating rather than driving other countries' policies. It appears that the driving force is Canada, which is linked to the USA, UK and France in three out of the four fundamental relations, and which is a reference point for the US, Italian and German rates, which are not cointegrated, seem to be determined by country‐specific factors. Copyright © 2001 John Wiley & Sons, Ltd.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".