Inflation Targeting and Medium-Term Planning: Some Simple Rules of Thumb
Bibliographic record
Abstract
Inflation targeting, a stable macroeconomic environment, and an average growth rate for potential output that is not expected to vary much in the next several years all help households, businesses, and governments in their medium-term economic and financial planning. Several simple rules of thumb can be usefully employed in this planning. Specifically, inflation targeting has maintained most major measures of inflation quite close to the target midpoint on average over a number of years. Combined with a clear fiscal framework, this has contributed to a more stable macroeconomic environment in which output varies less around its potential level. Potential output growth is expected to average around 3 per cent over the next several years. In light of these factors and historical relationships, labour income, profits, and consumer spending will likely grow, on average, by about 5 per cent over the medium term. Real and nominal long-term interest rates should also continue to be stable, with real 30-year yields varying around 3.5 or 4.0 per cent, and nominal yields varying around 5.5 or 6.0 per cent.
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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 | 0.016 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".