Canadian Interest Rate Setting: The Information Content of Canadian and U.S. Central Bank Communication
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We explain Canadian target rate decisions using macroeconomic variables as well as Bank of Canada and Federal Reserve communication indicators. Econometrically, we employ an ordered probit model of a Taylor rule to explain and predict 60 target rate decisions between 1998 and 2006. We find that communications, especially speeches and testimony by Canadian Governing Council members, provide a significant and robust explanation of Canadian target rate decisions. However, prior to the introduction of fixed announcement dates, Canadian communications contained more information on upcoming policy moves. Finally, communications by the U.S. Federal Reserve Bank—which are much more frequent—outperform our Canadian communication indicators in explaining Canadian interest rate decisions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it