Bibliographic record
Abstract
Over the past twenty five years, central bank communications have undergone a major revolution. Central banks that previously shrouded themselves in mystery now embrace social media to get their message out to the widest audience. The Federal Reserve System has not always been at the forefront of these changes, but the volume of information about monetary policy that the Federal Open Market Committee (FOMC) now releases dwarfs what it was releasing a quarter century ago. In this paper we focus on just one channel of FOMC communications, the post-meeting statement. We document how it has evolved over time, and in particular the extent to which it has become more detailed, but also more difficult to understand. We then use a VAR with daily financial market data to estimate a daily time series of U.S. monetary policy shocks. We show how these shocks on Fed statement release days have gotten larger as the statement has gotten longer and more detailed, and we show that the length and complexity of the statement has a direct effect on the size of the monetary policy shock following a Fed decision.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 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 teacher head, 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".