NAFTA's Impact on Mexico, the U.S., and Canada's Economies: A Look at Stock Returns
Bibliographic record
Abstract
The North American Free Trade Agreement continues to be a controversial topic, and with the impending implementation of the Trans-Pacific Partnership trade agreement, NAFTA has been a heavily discussed issue during the 2016 presidential campaign. Past research has critically assessed the extent to which NAFTA delivered on promises made by its lobbyists to improve economic welfare and stimulate growth in the North American markets, via trade and investment. These studies explain that NAFTA has helped to boost intra-regional trade and investment flows in North America, but has fallen short on any substantial improvements in welfare and deeper regional economic integration. However, researchers have found evidence for convergence among North American equity markets, and argue that this is generated by NAFTA. Using time series data from 1990 to 2007, this study builds on these conclusions to examine how NAFTA impacted equity markets in the North American region. I look at returns to each major stock index for Mexico, the U.S. and Canada, and find evidence that returns on these indexes improve in the post-NAFTA period for Mexico and the U.S., but not for Canada. Additionally, there is evidence to suggest that exports and FDI are the primary drivers for this improvement in stock returns.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".