Further Evidence on the Size and Power of the Bierens and Johansen Cointegration Procedures
Bibliographic record
Abstract
Although both the Johansen (1991, 1994) trace test and Bierens (1997a, b) nonparametric lambda-min test for cointegration have good size properties in Monte Carlo studies by Hubrich, Lutkepohl, and Saikkonen (2001) and Boswijk, Lucas, and Taylor (2000), the Bierens test has very low power. In contrast, Bierens reports good power for his procedure. Meanwhile, Hubrich et al. and Boswijk et al. do not include Bierens' companion method for estimating the number of cointegrating vectors, nor do they investigate the effect of serial correlation on Bierens'' test. In the present paper, inclusion of the estimation step does not significantly degrade size of the Bierens procedure, even with serial correlation, but power is not improved. Serial correlation does degrade the size of the Johansen test, but it remains superior. Analysis of Bierens'' (1997b) Monte Carlo results suggests that their indication of high power reflects the test''s lack of scale invariance.
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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 | 0.099 | 0.381 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.026 | 0.004 |
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".