Effects of exchange rate variability on trade of agri-food products between Canada and the United States
Bibliographic record
Abstract
Since the demise of the Bretton Woods system and the introduction of a flexible exchange rate regime, Canadian dollar depreciated relative to the U.S. dollar. The favorable Canada-U.S. exchange rate has been cited as an important reason for the growth in exports of processed potato. Similarly, other agri-food industries in Canada have also been enjoying improved price competitiveness relative to their U.S. counterparts. An important policy question is the extent to which exchange rate changes contributed to the expansion of Canadian agri-food exports to the United States over the past few years. The purpose of this study is to quantify the effects of Canada-U.S. exchange rate changes and its volatility on "two-way" trade in selected fresh and processed agri-food products between Canada and the United States using Johansen's Maximum Likelihood Cointegration analysis. The conclusions of this study suggest that while currency devaluation has a positive long run effect on bilateral trade, fluctuations in bilateral exchange rate lead to adverse effects on trade of selected agri-food products in both the short and long term. The policy implications imply that exporting firms should adjust their sales quickly following a depreciation to increase their profits in the short term. Exporters should also make effective use of forward (futures) markets for foreign exchange to minimize 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".