Inflation Persistence in the G7: The Effects of the Covid‐19 Pandemic and of the Russia‐Ukraine War
Bibliographic record
Abstract
ABSTRACT This note analyses how shocks caused by the Covid‐19 and the Russia‐Ukraine crisis impact on inflation persistence G7 countries. Using data ending at December‐2019, high estimates of the persistence parameter d indicate a strong persistence of inflation. The unit root hypothesis could not be refuted for Germany, Japan, and the United States, while this hypothesis is rejected in favour of higher orders of integration in the remaining cases. Expanding the dataset to include the pandemic and the Russia‐Ukraine crisis reveal that d‐values remain significantly elevated across all countries, reinforcing the persistence of inflation. Interestingly, Canada, previously excluded from the group, now aligns with Germany, Japan, and the United States. This suggests a change in inflation dynamics for Canada during these extraordinary periods. Additionally, employing a recursive estimate reveals a slight increase in inflation persistence for most countries, except Japan, which exhibits an almost flat trend in the evolution of the differencing parameter.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".