The effects of exchange rate changes and its variability on trade of red meat between Canada and the United States
Bibliographic record
Abstract
Since 1974, the Canadian dollar has depreciated relative to the U.S. dollar: from close to a parity in 1974 to approximately $0.84 in year 2004, reaching unprecedented low levels in between. The prevalence of favourable Canada-U.S exchange rate has been cited as an important contributor to improved price competitiveness of agri-food products produced in Canada. However, changes in exchange rate took place while the Canada-U.S. border became increasingly open due to two regional trade agreements, CUSTA and NAFTA. An important policy question is the extent to which exchange rate changes contributed to the expansion of red meat and live cattle exports from Canada to the United States. The purpose of this study is to quantify the effects of exchange rate changes and its variability on red meat trade between Canada and the United States using the Johansen's Maximum Likelihood Cointegration procedure. The results of this study suggest that a depreciating Canadian dollar, relative to the U.S. dollar, has significant positive effect on Canadian red meat exports to the United States. Growth in red meat exports to the U.S. can be largely attributed to a favourable Canada-U.S. exchange rate and not to either CUSTA or NAFTA. Exchange rate volatility has negative effects on Canadian red meat exports to the United States. These effects, while significant in the short run for some commodities, are found to be relatively small. Policies and marketing strategies should promote the use of financial markets by relevant participants to minimize the financial risk associated with exchange rate changes.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".