The transmission mechanism of monetary policy near zero interest rates: the Japanese experience, 1998–2000
Bibliographic record
Abstract
The Bank of Japan (BOJ) has gone through a unique experience in the past few years. When I joined the Bank's newly formed policy board in April 1998, the overnight call market rate, the key policy instrument of the BOJ, was already below 0.5%. The economy was in the midst of the most serious recession in the postwar period, although it took us a little while to realise this. We guided the call rate down to virtually zero in the first quarter of 1999 and followed up by promising to keep it there until deflationary concerns had been dispelled. Finally, in August 2000, we brought the rate up to 25 basis points after having kept the zero rate for one and a half years. In this short paper, I would like to discuss some of the key aspects of the evolution of our thinking on monetary policy over the period 1998–2000. In so doing, I would like to focus specifically on the characteristics of the 1997–98 Japanese recession, the transmission process of monetary policy in the neighbourhood of a zero rate and the background thinking behind the rate hike in August 2000. The nature of the 1997–98 recession It is appropriate to begin with a brief discussion of the nature of the recession that started in 1997(Q4), which is what the BOJ was trying to respond to in 1998–2000.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".