An Empirical Examination of the Effect of COVID-19 Travel Restrictions on Canadians’ Cross-Border Travel and Canadian Retailers
Bibliographic record
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has been devastating for many Canadian retailers. In this article, we estimate the offsetting positive effects of decreased international travel by Canadians on retail revenues. We use data from 1991 to 2021 on Canadians' travel to the United States to estimate a model of cross-border travel and establish community-level counterfactual staying rates had the pandemic not occurred. Combined with actual staying rates and elasticities of retailers' revenues with respect to staying rates, we estimate offsetting revenue gains due to the fall in cross-border travel. Our results suggest that, on average, the border closure generated a 1.49 percent offsetting gain in revenues for small Canadian retailers located within 150 kilometres of the border. We document variation across communities and sub-sectors, with estimates ranging from 0 to 125 percent. Retailers located in less-affluent communities near US shopping opportunities, and those operating in sub-sectors catering to travellers, experienced the largest gains.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".