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Record W1515111749

The economic effects on NAFTA of trans-atlantic free trade agreements

2011· article· en· W1515111749 on OpenAlexaboutno aff
Sadequl Islam

Bibliographic record

VenueApplied econometrics and international development · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsEuropean unionSubsidyInternational economicsInternational free trade agreementInternational tradeFree tradeEconomicsWelfareCustoms unionEconomic integrationChinaComputable general equilibriumTrade barrierTrade diversionGoods and servicesEconomyPolitical scienceMacroeconomics
DOInot available

Abstract

fetched live from OpenAlex

This paper investigates the effects of a bilateral free trade agreement between Canada and the European Union and the effects of a free trade agreement between the European Union and NAFTA on various trade related variables in NAFTA countries, the European Union , and other countries. The paper primarily relies on the Global Trade Analysis Project(GTAP) model and database, version 7. Two policy experiments are considered : 1) Elimination of all tariffs and export subsidies for all goods and services involving Canada and the European Union; and 2) Elimination of all tariffs and export subsidies for all goods and services involving NAFTA countries and the European Union. The main findings are : 1) A Canada-EU free trade deal will increase the economic welfare in Canada and the European Union with adverse effects on other regions, notably the United States and 2) a NAFTA-EU free trade agreement will increase the economic welfare of the United States and the European Union but reduce that of Canada , Mexico and other regions notably, China.

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.249
Threshold uncertainty score0.495

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.065
GPT teacher head0.196
Teacher spread0.131 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2011
Admission routes1
Has abstractyes

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