Une analyse économétrique de l’ajustement récent de la balance commerciale canadienne (1978-1979)
Bibliographic record
Abstract
The Canadian merchandise trade surplus increased rather modestly in 1978 and 1979 given that the depreciation of the real exchange rate since 1977 had considerably reinforced our competitive position. With the aid of an econometric model, we try to measure the respective contributions of the factors influencing the merchandise trade balance during that period. Our partial equilibrium simulations reveal that the depreciation of the Canadian dollar, both in nominal and real terms, substantially improved the merchandise trade surplus. High capacity utilization rates in Canada had a substantial impact on the trade balance through a large increase of imports, especially imports of producers' equipment, and through a significant reduction of exports of manufactured goods other than automotive products. Excluding the automobile sector, which has experienced a "structural" change in the United States, cyclical divergences between the two countries did not influence substantially the evolution of the merchandise trade account over that period. The rapid improvement of the terms of trade in 1979 strongly contributed to the increase of the nominal merchandise trade surplus. Our simulations show that the rise in the prices of certain primary commodities relative to the U.S. prices of manufactured goods was an important factor behind the stronger terms of trade.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".