ToTEM II: An Updated Version of the Bank of Canada’s Quarterly Projection Model
Bibliographic record
Abstract
This report provides a detailed technical description of an updated version of the Terms-of-Trade Economic Model (ToTEM II), which replaced ToTEM (Murchison and Rennison 2006) in June 2011 as the Bank of Canada’s quarterly projection model for Canada. ToTEM has been improved along a number of dimensions, with important changes to the model structure, including: (i) multiple interest rates, (ii) sector-specific demand specifications for consumption, housing investment and inventory investment, (iii) a role for financial wealth in household consumption, and (iv) rule-of-thumb price and wage setters. These new features remove some of the restrictions on model dynamics implied by assumptions in ToTEM, making ToTEM II more general and flexible than its predecessor. Furthermore, most of ToTEM II’s parameters are now formally estimated using full information estimation techniques, leading to significantly improved in-sample goodness of fit. The report discusses the model’s estimation and reviews the most important changes in the model’s properties. Finally, some important applications of ToTEM II in addressing recent policy questions are provided.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.038 | 0.007 |
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".