Monetary policy responses of Asian countries to spillovers from US monetary policy
Bibliographic record
Abstract
Regional integration in Asia has been considerably enhanced over the past 20 years or so. Whether integration helps Asian countries reduce their vulnerability to external shocks or is a channel for spreading external shocks remains an open question. This paper assesses the spillovers from US monetary policy shocks to Asian countries while taking into account country‐specific characteristics in explaining differences in timing and magnitude of responses across Asian countries. The results indicate that policy interest rates in Asian countries generally respond to innovations in the Fed rate in the same direction, but typically with a lag of one quarter. However, the size of the responses varies across Asian countries with respect to country‐specific characteristics. These results suggest that an independent monetary policy may not be feasible for an Asian developing country that adopts a pegged rate regime while being extensively integrated into the world economy. However, the hypothesis of the impossible trinity may not be relevant in the case of China.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.009 |
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; both teacher heads agree on what is shown here.
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".