To What Degree and through Which Channel Do Central Banks Other Than the Federal Reserve Cause Spillovers?
Bibliographic record
Abstract
Spillovers play a crucial role in driving monetary policy around the world. The literature focuses predominantly on spillovers from the Federal Reserve. Less attention has been paid to spillovers from other central banks. I measure the degree to which 20 central banks cause spillovers. I show that central banks in medium- to high-income countries cause spillovers to medium- to long-term interest rates in similar countries through a bond-pricing channel. These effects are narrower than spillovers from the Federal Reserve, which also affect emerging markets, short-term interest rates, and other assets. However, they are still pronounced. Fourteen central banks other than the Federal Reserve cause significant spillovers: the central banks of Australia, Canada, Czechia, the eurozone, Japan, Mexico, Norway, New Zealand, Poland, Romania, South Korea, Sweden, Switzerland, and the United Kingdom. Consequently, the Federal Reserve causes only one-fifth of the spillovers to 10-year interest rates, and the United States is the recipient of large spillovers. My results imply that central banks, especially the Federal Reserve, are affected by greater spillovers than is commonly believed, and that non-Fed central banks cause spillovers through a bond-pricing channel.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".