Testing unit roots, structural breaks and linearity in the inflation rates of the G7 countries with fractional dependence techniques
Bibliographic record
Abstract
In this paper, we have examined the inflation rates in the Group of Seven countries, investigating issues such as the existence of unit roots, structural breaks, fractional integration and potential non‐linearities using a fractional dependence (FD) approach based on Chebyshev polynomials in time. This robust FD approach allows one to test for persistence as well as non‐linearity of the series. We first tested for stationarity and structural breaks using classical approaches and observed inconclusive results with regard to the stationarity levels of the series. Using Bai–Perron tests, we actually confirmed significant structural breaks, even up to five, in each of the inflation series. However, noting that structural breaks are significantly related to fractional differentiation, this latter approach was also conducted. Here, we observed that the estimates of the differencing parameter were quite stable across time, and evidence of unit roots was found in the cases of the UK, Canada, France, Japan and the USA; for Germany, we found some evidence of mean reversion, while estimates of d above 1 were found in the case of Italy. On the other hand, non‐linear deterministic trends were clearly rejected in all cases. Copyright © 2016 John Wiley & Sons, Ltd.
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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) | 0.000 | 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".