The Impact of the Global Business Cycle on Small Open Economies: A FAVAR Approach for Canada
Bibliographic record
Abstract
Building on the growing evidence on the importance of large data sets for empirical macroeconomic modeling, we use a factor-augmented VAR (FAVAR) model with more than 260 series for 20 OECD countries to analyze how global developments affect the Canadian economy. We focus on several sources of shocks, including commodity prices, foreign economic activity, and foreign interest rates. We evaluate the impact of each shock on key Canadian macroeconomic variables to provide a comprehensive picture of the effect of international shocks on the Canadian economy. Our findings indicate that Canada is primarily exposed to shocks to foreign activity and to commodity prices. In contrast, the impact of shocks to global interest rates or global inflation is substantially lower. Our findings also expose the different channels through which higher commodity prices impact the Canadian economy: Canada benefits from higher commodity prices through a positive terms of trade shock, but at the same time, higher commodity prices tend to lower global economic activity, hurting demand for Canadian exports.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".