Was Monetary Policy Optimal During Past Deflation Scares?” Economic Review of the Federal Reserve Bank of Kansas City 2009, 3rd Quarter
Bibliographic record
Abstract
Countries around the world have fallen into one of the deepest recessions since the Great Depression—a recession exacerbated by a severe financial crisis. Among the challenges that face monetary policymakers in such uncertain times is the danger economies worldwide, including the United States, Japan, and the euro area, may enter a period of deflation, in which the prices of goods and services fall relentlessly. Policymakers and economists agree that sustained deflation would likely worsen the already fragile economic and financial environment. Past episodes of deflation in the wake of financial crises have included falling asset values, collapsing business and consumer confidence, credit crunches, widespread bankruptcies, long-lasting surges in unemployment, and other adverse conditions. Moreover, a deflationary environment has the potential to complicate the conduct of monetary policy. Central banks typically counteract slowing economic activity by lowering
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".