Assessing Long-Run Determinants of Cross-Border Freight Flows Between the United States and Canada
Bibliographic record
Abstract
The cross-border freight flows between the United States (US) and Canada have rapidly increased since the NAFTA was implemented. Over the period of 2004:Q1-2013:Q1, US freight exports to Canada have increased by 60.6% and US freight imports from Canada have risen by 36.0%. Given the growing US-Canada cross-border freight trade, this paper explores the long-run impacts of GDP, the bilateral exchange rate, PPI on US freight exports and imports by transportation mode. For this purpose, the paper employs fully modified ordinary least squares (FM-OLS) approach. The FM-OLS model provides an unbiased estimate of the long-run relationship between variables when the variables are nonstationary and integrated of order one I(1). The empirical results show that US GDP plays a key role in determining US imports by truck, rail, pipeline, and air, while Canadian GDP is the primary determinant of US exports by truck, rail, and pipeline. This suggests that in the long-run, the cross-border flows are highly responsive to the economic growth in the importing country for most transportation modes. The real exchange rate tends to be positively associated with US imports, but negatively related to US exports. This indicates that the US dollar depreciation against the Canadian dollar increases demand for US commodities in Canada, but weakens demand for Canadian commodities in the US. Finally, PPI of the exporting country appears to have a negative impact on the cross-border freight flows between the US and Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".