Independent Agencies, Distribution, and Legitimacy: The Case of Central Banks
Bibliographic record
Abstract
Delegation to independent agencies can reap real benefits for policy-making. In the case of monetary policy, it shores up the credibility of the central bank. However, the discretion of IAs needs to be constrained to ensure their legitimacy. This letter focuses on one potential constraint, namely, the idea that IAs should not make choices on distributional trade-offs. Given that monetary policy today has significant distributive consequences, if this constraint were respected, the independence of central banks would have to be repealed. This would be just as undesirable as a monetary policy whose distributive consequences remain unchecked. Instead, this letter encourages the search for alternative solutions and puts forward three possible institutional arrangements to manage the tension between the distributive consequences of monetary policy on the one hand and central bank legitimacy on the other.
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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 | 0.017 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.036 |
| Scholarly communication | 0.019 | 0.011 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.016 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 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".