Global inflation dynamics and inflation expectations
Bibliographic record
Abstract
In this paper we investigate dynamics of inflation and short-run inflation expectations. We estimate a global vector autoregressive (GVAR) model using Bayesian techniques. We then explore the effects of three source of inflationary pressure that could drive up inflation expectations: domestic aggregate demand and supply shocks as well as a global increase in oil price inflation. Our results indicate that inflation expectations tend to increase as inflation accelerates. However, the effects of the demand and supply shocks are short-lived for most countries. When global oil price inflation accelerates, however, effects on inflation and expectations are often more pronounced and long-lasting. Hence, an assessment of the link between observed inflation and inflation expectations requires disentangling the underlying sources of inflationary pressure. We also examine whether the relationship between actual inflation and inflation expectations changed following the global financial crisis. The transmission between inflation and inflation expectations is found to be largely unaffected in response to domestic demand and supply shocks, while effects of an oil price shock on inflation expectations are smaller post-crisis.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".