The de minimis threshold in international trade: The costs of being too low
Bibliographic record
Abstract
Abstract With tariffs largely negotiated away, trade facilitation issues such as custom delays and border costs are one of the next key barriers for trade policymakers to address. One important trade facilitation issue is the de minimis threshold (DMT)—a valuation ceiling for imports below which no duty or tax is charged and the clearance procedures are minimal. Customs assessments are costly and low thresholds can hinder trade flows. We offer a detailed analytical approach to assess the direct economic effects of raising theDMT. We focus on Canada, which has one of the lowestDMTs among developed countries. We utilise a unique data set and find that raising Canada'sDMTwould have positive effects for consumers and businesses, particularly small businesses because the cost saving for smaller entities is disproportionately large. For the government, foregone duty and tax revenues are outweighed by the cost saving, resulting in a fiscally neutral or even positive effect for government revenues.
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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 | 0.005 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".