Interest Rate Pass-Through and Monetary Transmission in Asia
Bibliographic record
Abstract
This study seeks to examine the effectiveness of interest rates transmission mechanism from money market rate into retail banking rate in several Asian countries. In particular, we intend to investigate the differences in the degree of pass-through from monetary policy rate into deposit and lending rates across countries and between the pre- and post-crisis of 1997. The study is carried out by running the Seemingly Unrelated Regression (SUR) equations. The results suggest that the transmission rate from money market rate into deposit and lending rates is slow and sluggish across economies. There is no much difference between the pass-through rate into deposit and lending rates but the pass-through into deposit rate is slightly higher than that in lending rate. Most of the countries have slower adjustment rates after the crisis 1997, indicating low effectiveness of monetary policy, imperfect financial market and lower degree of financial integration if these economies. However, there is an exception for Malaysia.
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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 | 0.000 | 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".