ToTEM: The Bank of Canada's New Quarterly Projection Model
Bibliographic record
Abstract
The authors provide a detailed technical description of the Terms-of-Trade Economic Model (ToTEM), which replaced the Quarterly Projection Model (QPM) in December 2005 as the Bank's principal projection and policy-analysis model for the Canadian economy. ToTEM is an open-economy, dynamic stochastic general-equilibrium model that contains producers of four distinct finished products: consumption goods and services, investment goods, government goods, and export goods. ToTEM also contains a commodity-producing sector. The behaviour of almost all key variables in ToTEM is traceable to a set of fundamental assumptions about the underlying structure of the Canadian economy. This greatly improves the model's ability to tell coherent, internally consistent stories about the current evolution of the Canadian economy and how it is expected to evolve in the future. In addition, ToTEM's multiple-goods approach enables the Bank to gain insight into a much wider variety of shocks, including relative-price shocks. In particular, ToTEM is better equipped to handle terms-of-trade shocks, such as those stemming from movements in world commodity prices. But ToTEM does not mark a radical departure from QPM's design philosophy; rather, it should be regarded as the next step in the evolution of openeconomy macro modelling at the Bank. Indeed, ToTEM adopts most of the features that distinguished QPM from its predecessors, including a well-defined steady state, an explicit separation of intrinsic and expectational dynamics, an endogenous monetary policy rule, and an emphasis on the economy's supply side. However, ToTEM extends this basic framework, allowing for optimizing behaviour on the part of households and firms, both in and out of steady state, in a multi-product environment.
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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 | 0.001 | 0.004 |
| 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 | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".