The Heterogeneity of the Inflation Expectations of Italian Firms along the Business Cycle
Bibliographic record
Abstract
We investigate how the cross-sectional heterogeneity of firms' inflation expectations reflects information availability and awareness of recent macroeconomic developments, observable firm characteristics, and broader macroeconomic developments using the Bank of Italy's survey on businesses' inflation and growth expectations. We find that, on average, about half of the dispersion of expectations is traceable to a lack of information about the most recent price developments; firms incorporate new information into their expectations within a quarter; the dispersion of expectations is related in a statistically significant way to some important aggregate economic variables, and it is greater when current inflation is farther away from the ECB's price stability goal. Since 2015 the weight attributed to prior beliefs of low inflation has steadily increased and the uncertainty surrounding them has decreased. Furthermore, since 2014 the empirical connection between the dispersion of expectations and the distance from the ECB price stability goal has become considerably weaker. These two facts suggest an increased risk of inflation expectations being de-anchored.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".