How Does the Exchange Rate and Its Volatility Influence FDI to Canada? A Disaggregated Analysis
Bibliographic record
Abstract
This study investigates the relationship between the real effective exchange rate (REER) and its volatility with the net inflow of foreign direct investment (FDI) to Canada, placing a novel emphasis on sector-level analysis. The study utilizes time series data from 2007 to 2022 and employs the autoregressive distributed lag (ARDL) approach to assess short-run and long-run relationships between the said variables. The findings reveal significant impacts of changes in REER, its volatility, and GDP on net FDI in the short run, with lasting effects of REER and its volatility, lagged GDP, and trade openness on FDI in the long run. At the sectoral level, FDI inflows in energy and mining, manufacturing, finance, and insurance exhibit significant sensitivity to changes in REER. Simultaneously, the volatility of REER has a significant impact on FDI inflows in manufacturing industries and the finance and insurance sector in the short run. In the long run, REER exerts a significant influence on the net FDI inflows in energy and mining, as well as manufacturing industries. The asymmetry in findings suggests a need for sector-specific attention to retaining and attracting FDI to Canada.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".