Developing a Market-Based Monetary Policy Transparency Index and Testing Its Impact on Risk and Volatility in the United States
Why this work is in the frame
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Bibliographic record
Abstract
This paper extends the literature by developing an objective market-based index, which is \ndynamic and continuous and can be used to measure the monetary policy transparency \nfor a country or, simultaneously, a series of countries. It was found that the agents in the \nmoney market are forward looking and that the more transparent the monetary policy is, \nthe less risky and volatile the money market will be. Furthermore, during the tenure of \nChairman Greenspan, the volatility and risk in the money market fell. The policy regime \nchanges of adjusting the target rate by multiples of 25 or 50 basis points and including a \nbalance-of-risks sentence in FOMC statements also resulted in a reduction in volatility in \nmoney markets.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it