Spillovers of US interest rates: Monetary policy & information effects
Bibliographic record
Abstract
This paper quantifies the international spillovers of U.S. interest rates by accounting for the “Fed Response to News” channel. Using the identification strategy of Bauer and Swanson (2023a), we decompose monetary policy surprises into two components: a pure U.S. monetary policy shock and a “Fed Response to News” component around FOMC meetings. I find that a U.S. monetary tightening driven by pure policy shocks causes a global recessions, exchange rate depreciation, and tighter financial conditions. In contrast, a tightening driven by the “Fed Response to News” channel leads to an economic expansion, exchange rate appreciation, and looser financial conditions. Ignoring the “Fed Response to News” channel biases estimates, explaining recent atypical findings of expansionary impacts. By isolating these components, I reconcile traditional and recent views of monetary policy spillovers. Results are robust across advanced and emerging economies, alternative methods, and identification strategies.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".