Heterogeneidade das expectativas de inflação mensal no Brasil: evidências a partir de dados agregados da pesquisa Focus
Bibliographic record
Abstract
Neste artigo é analisada a heterogeneidade das expectativas de inflação coletadas pelo Banco Central do Brasil, por meio de estatísticas descritivas e estimações econométricas para o comportamento da mediana, dispersão, amplitude e recorrência da presença de instituições no grupo Top 5, de maior acerto das previsões. São utilizadas expectativas agregadas do IPCA de janeiro de 2003 a agosto de 2016. Os resultados mostram correlação quase perfeita entre as previsões do conjunto de respondentes e os Top 5, ajuste gradual das expectativas, importância da data de referência para apuração do Top 5 e relação positiva entre variações da mediana e sua dispersão. O sistema de premiação das instituições Top 5 parece induzir uma parcela relevante dos respondentes a manter atualizadas as suas expectativas.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.014 |
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; both teacher heads agree on what is shown here.
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".