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Record W2403288142

NAFTA's Impact on Mexico, the U.S., and Canada's Economies: A Look at Stock Returns

2016· article· en· W2403288142 on OpenAlexaboutno aff
Justin Beck

Bibliographic record

VenueScholarship - Claremont (Claremont Colleges) · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsStock (firearms)EconomicsEconomyInternational economicsInternational tradeBusinessGeography
DOInot available

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.342
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.042
GPT teacher head0.223
Teacher spread0.182 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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