Exported retail sales along the Texas‐Mexico border
Bibliographic record
Abstract
Trade between the U.S. and Mexico has boomed over the past 10 years due partly to the significant reduction in tariffs from the North American Free Trade Agreement (NAFTA) and the strong growth in the maquiladora industry. While commercial trade between the countries is well documented, less is known about the size of the cross‐border retail trade that occurs. Though the size of this activity is small in comparison to commercial trade, it is a significant part of the economies of many border cities. In 2005 alone, there were more than 45 million non‐commercial crossings at the bridges along the Texas‐Mexico border. Many of these individuals were coming to purchase goods to take back to their home country. Since most of the retail trade conducted on the U.S. side of the border is done in cash, it is difficult to document the share of retail spending accounted for by Mexican nationals. In this article we use several techniques based on a simple consumption function to estimate the size of retail spending that is essentially exported to Mexico via cross‐border shoppers. We then check our estimates of the proportion of retail sales going to Mexican nationals in the Texas border metros to see if they are consistent with the impacts to retail sales of movements in the real peso‐dollar exchange rate.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".