Monetary Policy Uncertainty in the United States and Investment Sentiment in Advanced Economies
Why this work is in the frame
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Bibliographic record
Abstract
Abstract How does uncertainty originating from the future path taken by monetary policy enacted by the Federal Reserve in the United States affect the business confidence in other advanced economies? Does US monetary policy uncertainty affect economic activity in the United States and in Canada, France, Germany, Italy, Japan, and the United Kingdom. Motivated to answer these questions, we use monthly data and a bivariate GARCH-in-Mean VAR model. We also use a multivariate structural VAR model and a different measure of US monetary policy uncertainty, achieving identification by a combination of short-run and long-run restrictions. Our evidence shows that US monetary policy uncertainty, irrespective of how it is measured, has negative effects on the business confidence and output in the advanced G7 economies.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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