Assessing the value of indicators of underlying inflation for monetary policy
Bibliographic record
Abstract
This paper considers a number of different measures of core inflation and tries to identify those containing the most useful information about future movements in headline inflation rates over the horizons relevant for monetary policy for the United States, the euro area, Japan, the United Kingdom and Canada. The paper shows that the adjusted indicators do considerably better than the headline rate at determining the underlying inflation trend and, being considerably less volatile, can also be used at higher frequencies to provide more timely information. Most of these indicators also contain information relevant to predicting future headline inflation and which is additional to that contained in the headline rate. However, the relative performance of different indicators varies considerably across economies, and in some cases across sample periods. There is evidence that headline inflation tends to converge toward core inflation over time horizons of between 12 and 24 months. However, the estimated model incorporating this relationship between headline and core inflation does rather poorly in out-of-sample tests, althoughout-of-sample performance is much better for other specifications.
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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 | 0.010 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".