Border Effects Before and After 9/11: Panel Data Evidence Across Industries
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The paper builds a unique industry‐level panel data set to estimate the border effects associated with US–Canada trade for each year from 1992 to 2005. We first establish the theoretical foundation of our empirical model as a multisector version of Anderson and van Wincoop. Estimates from data aggregated at the province/state level yield border effects that increase slightly in the early 1990s, then decline after the implementation of the North American Free Trade Agreement ( NAFTA ), but then increase significantly after 2001. Results based on three‐digit NAICS level data reveal higher border effects in the early 1990s and substantial heterogeneity across industries. The results are robust to a variety of specifications and models, and they suggest that the security measures adopted in the aftermath of the tragic events of 11 September 2001 had considerable adverse effects on US–Canada trade.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it