The Monetary Policy Transmission Mechanism and Policy Rules
Bibliographic record
Abstract
The inflation targeting regime in place in Canada requires a clear understanding of the monetary policy transmission mechanism and a way to exploit knowledge of that mechanism in making policy decisions� This paper describes the Bank of Canada’s current understanding of the monetary policy transmission mechanism as well as our research, in the context of a model based on that understanding, to identify policy rules to help guide the formulation of monetary policy� Section 1 discusses the Bank’s view of the monetary policy transmission mechanism in Canada � It begins with the major linkages and then focuses in turn on transmission through financial variables, the impact of financial variables on aggregate demand, and the impact on inflation from the output gap, expectations, and the exchange rate� Because of the importance of inflation projections in the framework used at the Bank of Canada, section 2 reviews the range of approaches that have been investigated for generating such projections � These include the construction of small models of the Canadian economy, single-equation models of quarterly inflation, and a fully specified model, the Quarterly Projection Model (QPM) � Section 3 outlines recent work at the Bank of Canada on policy rules � This section covers the QPM policy rule, simulation analyses comparing forward-looking The authors have benefited from the technical assistance of Hope Pioro and from comments by their colleagues (especially Bob Amano, Tiff Macklem, and Dinah Maclean), by Pablo García, and by participants at the Third International Conference of the Central Bank of Chile � The views expressed in this paper are those of the authors � No responsibility for them should be attributed to the Bank of Canada�
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".