Toward a North American Security Perimeter? Assessing the Trade and FDI Impacts of Liberalizing 9/11 Securiy Measures
Bibliographic record
Abstract
This paper examines, for the first time, the trade and FDI impacts of a North American Security Perimeter that would liberalize the post 9/11 security measures at the Canada-US border. First, the study estimates econometrically the impact of post 9/11 security measures on bilateral (US-Canada) trade flows using a gravity model. Second, using these econometric estimates together with a three-region nine-sector general equilibrium model, we compute sectoral tariff rates “equivalent” to the 9/11 security measures. Finally, we assess the (general equilibrium) impacts on trade and FDI of a change of security paradigm toward a North American Security Perimeter. The paper shows that the economic opportunity gains occurring to Canada and the US from the liberalization of the 9/11 security measures amount to US$20 billion annually. This figure, once added to the direct administrative costs of the post 9/11 security measures, warrants serious consideration in policy discussions of a North American Security Perimeter. / Cet article examine les impacts commerciaux et d’investissement direct étranger (IDE) d’un périmètre de sécurité Nord-Américain qui libéraliserait les mesures de sécurité qui furent introduites à la frontière Canado-américaine à partir du 11 Septembre 2001 (9/11). Dans un premier temps, l’étude estime économétriquement l’impact des mesures post 9/11 sur les flux commerciaux bilatéraux (US-Canada) en utilisant un modèle de gravité. L’étude utilise ensuite ces estimations économétriques conjointement avec un modèle d’équilibre général à 3 régions et à 9 secteurs afin de calculer les tarifs sectoriels équivalents aux mesures de sécurités 9/11. Finalement, nous évaluons les impacts (en équilibre général) sur le commerce et l’IDE d’un changement de paradigme de sécurité en faveur d’un Périmètre de Sécurité Nord-Américain. Cet article estime que les gains (d’opportunité) économiques pour le Canada et les États-Unis résultants de la libéralisation des mesures de sécurité 9/11 sont de 20 milliards de US$ annuellement. Ce montant, lorsque cumulé aux coûts administratifs directs des mesures de sécurité 9/11, devrait susciter des discussions politiques sérieuses sur la mise en oeuvre d’un tel Périmètre de Sécurité Nord-Américain.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".