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Record W3124308742 · doi:10.3917/edd.215.0069

North-South technology diffusion, regional integration, and the dynamics of the “natural trading partners” hypothesis

2008· article· en· W3124308742 on OpenAlexaff
Maurice Schiff, Yanling Wang

Bibliographic record

VenueRevue d économie du développement · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Productivity
Canadian institutionsCarleton University
Fundersnot available
KeywordsProductivityEconomicsArgument (complex analysis)Total factor productivityWelfareInternational economicsInternational tradeEconomic geographyNatural (archaeology)DiffusionMacroeconomicsGeographyMarket economy

Abstract

fetched live from OpenAlex

Based on static analysis, a number of studies argue that forming a regional trade agreement (RTA) is more likely to raise welfare if member countries are “natural trading partners,” while other studies claim the opposite. This paper considers the argument from a dynamic viewpoint by examining the impact of trade with Japan, North America and the EU on technology diffusion and total factor productivity (TFP) in Jordan, Korea and Mexico. Using industry-level data, we show that: i) technology diffusion and productivity gains tend to be regional: Jordan, Korea, and Mexico tend to benefit mainly from trade with the EU, Japan, and North America respectively; and ii) the dynamic version of the “natural trading partners” hypothesis seems to hold.JEL Classification: F02, F13, F15, F43, O39

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.243
Threshold uncertainty score0.534

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.043
GPT teacher head0.199
Teacher spread0.156 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2008
Admission routes1
Has abstractyes

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