Are central banks really breaking the (policy) rules?
Bibliographic record
Abstract
▀ Looking at the strength of the global economy, it's no surprise that simple policy rules suggest that interest rates in some advanced economies are much too low and/or that several rate hikes would be needed in 2018 to avoid falling further behind the curve. Nonetheless, we expect central banks to respond cautiously and we see a slower pace of tightening than the consensus view. ▀ Policy rules, such as the Taylor Rule, have long been considered a useful guide to the potential path for policy rates. But while it suggests that current US, Eurozone and Australian central bank rates are broadly appropriate, it signals that UK, Canadian, and Swedish rates should be substantially higher. Based on our economic forecasts, Taylor Rules suggest that the central banks in the US, Eurozone, Canada and Australia will all need to raise intertest rates by around 100bps by end‐2018. ▀ However, there are several reasons not to draw strong conclusions from such point estimates. First, the Taylor Rule requires estimates of two unobservable variables – the output gap and the natural rate of interest – which cannot be estimated precisely. ▀ Second, using models that were designed to predict US policy responses in the 1990s to forecast central banks' behaviour today is likely to be misleading. Meanwhile, inferring central banks' reaction functions from recent policy rate moves to assess the future policy path is fraught with difficulties. Not only have interest rates been broadly unchanged for the bulk of the post‐financial crisis period, but policymakers have provided other forms of policy support. ▀ Third, outside the US at least, Taylor Rules have historically pointed to persistently different policy rates from those observed, yet inflation has been well anchored. ▀ The upshot of all this is that we expect central banks in the advanced economies to err on the side of caution and anticipate interest rates rising less quickly than the consensus amongst economists.
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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 | 0.012 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.023 | 0.011 |
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".