Inflation rate dispersion and convergence in monetary and economic unions: lessons for the ECB
Bibliographic record
Abstract
Using a set of regional inflation rates we examine the dynamics of inflation dispersion within the U.S.A., Japan and across U.S. and Canadian regions. We find that inflation rate dispersion is significant throughout the sample period in all three samples. Based on methods applied in the empirical growth literature, we provide evidence in favor of significant mean reversion (?- convergence) in inflation rates in all considered samples. The evidence on ?-convergence is mixed, however. Observed declines in dispersion are usually associated with decreasing overall inflation levels which indicates a positive relationship between mean inflation and overall inflation rate dispersion. Our findings for the within-distribution dynamics of regional inflation rates show that dynamics are largest for Japanese prefectures, followed by U.S. metropolitan areas. For the combined U.S.-Canadian sample, we find a pattern of withindistribution dynamics that is comparable to that found for regions within the European Monetary Union (EMU). In line with findings in the so-called 'border literature' these results suggest that frictions across European markets are at least as large as they are, e.g., across North American markets.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".