The Bank of Canada's New Quarterly Projection Model, Part 3. The Dynamic Model: QPM
Bibliographic record
Abstract
The Bank of Canada's new Quarterly Projection Model, QPM, combines the short-term dynamic properties necessary to support regular economic projections with the consistent behavioural structure necessary for policy analysis. The theoretical underpinnings of the model and the properties of its dynamically stable steady state are described in the first volume of this series. In this third volume, the authors review the history of macro modelling at the Bank and how that history has conditioned the nature of QPM and the methodology used in its construction. They then describe the model, focussing on the types of shocks it was designed to handle and the key elements of its dynamic structure. Two important features of that dynamic structure are forward-looking expectations and endogenous policy rules. Unlike previous Bank models, QPM is not estimated; rather, it is calibrated to reflect the Canadian data. The authors discuss the methodology of calibration and provide examples of how it was done for QPM. Finally, they illustrate QPM's properties in dynamic simulation by describing the results of numerous shocks to the model.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".