Short-run and long-run consequences of unconventional monetary policy in Japan
Bibliographic record
Abstract
Monetary policy is a powerful policy tool in stabilizing short-term economic fluctuations. However, no matter how effective it is, it could have unintended adverse impacts on the economy if the central bank continued extreme monetary easing over a long period of time. Japan is an exceptional country where such concern exists. This paper analyzes the effects of unconventional monetary policy in Japan since the end of the 1990s. We explore the effects not only on stabilizing short-term macroeconomic fluctuations such as the GDP gap, but also on medium- and long-term productivity such as total factor productivity (TFP). If the prolonged ultra-low interest rate environment distorts the price mechanism and causes misallocation of funds, the unconventional monetary policy could reduce the productivity of the economy. The estimation results show that the Bank of Japan (BOJ)'s unconventional monetary policy had a significant positive impact on the GDP gap even under a liquidity trap where the policy rate hit its effective lower bound (ELB). However, they also show that unconventional monetary policy had a significant negative impact on TFP growth. The results suggest that while unconventional monetary policy was effective in boosting the economy in the short term, the prolonged ultra-low interest rate environment may have had a negative impact on medium- and long-term productivity growth in the Japanese economy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".