Core Inflation, Expectations and Inflation Dynamics in Brazil
Bibliographic record
Abstract
This work investigates the adequacy of core inflation measures as indicators of forward-looking expectations in the hybrid new Keynesian Phillips curve (HNKPC) for the Brazilian economy. For that purpose, we use monthly data between January 2002 and August 2015 and the heteroscedasticity and autocorrelation consistent generalized method of moments (HAC-GMM). The results indicate that the HNKPC is a robust mechanism to model Brazilian inflation dynamics in the period analyzed; that the recent increase in the degree of indexation of the Brazilian economy seems to have contributed to the formation of a stronger inertial component of inflation; and also that the core inflation measures appear to be potential indicators to model forward-looking expectations in the HNKPC in Brazil. Furthermore, the inflation forecasts extracted from these models are statistically similar to those generated by models that use market prognoses from the Focus survey published by the Central Bank of Brazil. Therefore, the core inflation measures appear to have adequately anchored the inflation expectations in Brazil in the period analyzed.
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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 | 0.010 |
| 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 | 0.000 |
| 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".