Exchange Rate Pass-Through to Canadian exports price: \nAn industry-based Approach
Bibliographic record
Abstract
In this paper we studied the degree of Exchange Rate Pass-Through (ERPT) into the price of seven major crude and fabricated materials exported to the United-States.They include iron ore and scrap, paper and paperboard, crude oil and gas, petroleum and coal manufacturing, plastic and rubber, wood and aluminum.Our study covers the period going from Jan 2002 where the Canadian dollar started its appreciation to Apr 2007.We Used Vector autoregressions (VAR) technique and estimated the Cumulative Impulse Reaction Function generated.In the short term, we found evidence of null ERPT in the iron and petroleum and coal manufacturing industries and incomplete ERPT in the paper, crude petroleum and natural gas, wood and aluminum industries.ERPT is however more than complete for plastic and rubber.ERPT to US dollar exports price tends to rise over time.Our findings are consistent with previous empirical studies that found evidence of incomplete degree of ERPT to the US imports price.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.016 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.071 | 0.011 |
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".