Border Crossing for Trucks Twenty Three Years after NAFTA
Bibliographic record
Abstract
Despite the liberalization achieved by the North American Free Trade Agreement (NAFTA), and substantial investments in infrastructure, technology, and equipment, significant barriers to efficient truck transport remain between the United States and Mexico. We present the practical and economic implications of changes to the NAFTA border crossing system put in place after the terrorist events of September 11, 2001. Security measures have “thickened” NAFTA’s borders, increasing costs and delays associated with border crossings. These measures have a global impact on the logistics chain, since they are applied to all countries that source goods to the United States. We review literature on costs and impacts of border delays due to enhanced security and build on our earlier research on these institutional peculiarities and their impacts of the US-Canada- Mexico border crossing system. We discuss procedures used today and note changes to border processing since our earlier work. Based on interviews and review of the literature, we present the institutional context in which barriers exist and border authorities’ rationale for establishing new barriers or continuing of pre-existing ones. Based on this information and the time and costs associated with cross-border freight movements, we estimate the welfare effect of these measures on the NAFTA economies in a CGE framework. Our counterfactual assumes the implementation of a “seamless freight flow” system similar to Europe’s Transport International Routier (TIR) system, and calculates the time and cost differentials between such a system and the status quo. We estimate net annual welfare gains for the NAFTA countries accruing from the streamlining of the U.S.-Mexican brokerage system and find that NAFTA-wide annual welfare could rise by $7.5 billion. Extending the simulation to include streamlining intra-NAFTA security-related delays could add an additional $14.7–28.6 billion to annual welfare across the region.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".