What do the RBA’s Forecasts Imply about its Preferences over Inflation and Output Volatility?*
Bibliographic record
Abstract
The Reserve Bank of Australia (RBA) has recently commenced publishing its forecasts of inflation and output growth in their quarterly Statement on Monetary Policy. As the RBA can potentially influence future outcomes for inflation and output through its choice of cash rate target, we examine whether the RBA’s forecasts reveal useful information about its tradeoff between inflation and output volatility. Our results suggest that the RBA targets a linear combination of deviations of inflation around target and output growth around potential growth – where the weight given to output growth deviations is about one-third that given to inflation deviations. If we interpret this weight as the ratio of a central bank’s (relative) preference for output volatility and the slope parameter of the Phillips Curve; for typical values of the latter parameter we find the RBA – while not a strict inflation targeter – gives significantly less weight to minimising deviations in the output gap, than it does to minimising deviations of inflation around target.
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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 | 0.006 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".