Effects of Canadian Exchange rate Volatility on Imports and Exports
Bibliographic record
Abstract
This paper examines effects of exchange rate volatility proxied by GARCH model on Canadian total exports, exports to the USA, total imports, and imports from the USA and used monthly data from 1997M04 to 2017M08. To estimate long-run relationship ARDL co-integration bound test technique has been used. The results conclude that long-run equilibrium relationship does exist between exchange rate volatility and Canadian total exports, exports from the USA, total imports, and imports from the USA. Further results indicate that exchange rate volatility has a significant inverse long-run relationship with total exports (=-20394705), exports to USA (=-11,195,316), and total imports (=-144,000,000), but an insignificant inverse relationship with Canadian imports from the USA. Further, vector error correction mechanism (VECM) confirms long-run equilibrium relationship between variables. The absolute magnitudes of error correction terms 2.8098, 4.5239, 0.3818, and 0.5306 represent speeds of adjustment for exchange rate volatility, and Canadian total exports, exports to the USA, total imports, and imports from the USA, respectively, in case of any departure from long-run equilibrium. In short term Toda and Yamamoto test finds bi-directional between exchange rate volatility and Canadian total exports, exchange rate volatility and exports to the USA, exchange rate volatility and Canadian total imports, and exchange rate volatility and imports from the USA. Findings of the current study have very important implications for policymakers to design such policies that can establish both short term and long-run equilibrium relationship between exchange rate volatility, exports and imports adjusting short-term exchange rate and trade deficit shocks to avoid violation of international budget constraints.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".