New Approach to Estimation of the Core Inflation*
Bibliographic record
Abstract
Recently, the Inflation Targeting System (ITS) has emerged as a major monetary policy scheme in countries like England, Canada, and Australia. Such transition toward the ITS was initiated mainly by the desire to achieve economic stability by using more extensive information variables than a simple traditional money supply variable. The success of the ITS is believed to depend on which variables are utilized as tools, and which are used as the target variable. Variables like monetary aggregates, interest rate, exchange rate and so forth have been extensively used as information variables, while the so-called core inflation has been utilized as a target variable. The key issue of the ITS thus comes down to how to define and estimate the core inflation, the target variable. So far, the core inflation has been derived as a quasi-trend after arbitrarily truncating extreme fluctuations. This process obviously causes a serious loss of information. In addition, correlation between the headline inflation
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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 | 0.001 |
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".