Quantitative Easing as a Policy Tool Under the Effective Lower Bound
Bibliographic record
Abstract
This paper summarizes the international evidence on the performance of quantitative easing (QE) as a monetary policy tool when conventional policy rates are constrained by the effective lower bound (ELB). A large body of evidence suggests that expanding the central bank’s balance sheet through large-scale asset purchases can provide effective stimulus under the ELB. Transmission channels for QE are broadly similar to those of conventional policy, notwithstanding some important but subtle differences. The effectiveness of QE may be affected by imperfect pass-through to asset prices, possible leakage through global capital reallocation, a reduced impact through the bank lending channel, and diminishing returns to additional rounds of QE. Although the benefits of QE appear, so far, to outweigh the costs, at some point this may be reversed. The exact “effective quantitative bound” where the costs of QE become larger than the benefits is as yet unknown. The summary of the evidence, however, suggests that QE is indeed an “adequate” substitute for monetary policy at the ELB, rather than a “perfect” one.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".