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Record W2992947642

INDUSTRY, FOREIGN TRADE AND DEVELOPMENT: ECONOMETRIC MODELS OF EUROPE AND NORTH AMERICA, 1965-2003

2006· article· en· W2992947642 on OpenAlexaboutno aff
María del Carmen Guisán Seijas

Bibliographic record

VenueInternational journal of applied econometrics and quantitative studies · 2006
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsOrder (exchange)Production (economics)EconomicsEconometric modelInternational tradeCapital goodInternational economicsEconometric analysisNoticeGoods and servicesIndustrial productionCapital (architecture)Foreign capitalSupply and demandSupply sideBusinessForeign direct investmentEconomyMacroeconomics
DOInot available

Abstract

fetched live from OpenAlex

We compare several econometric models of Western Europe, Central Europe, the United States, Canada and Mexico in order to analyze the impact of foreign trade and industry on development Regarding the positive effects of foreign trade it is important to notice that they are more due to the positive role of imports from the supply side than to the effect of exports from the demand side, although both sides are relevant. The main benefit from increasing exports is usually to increase the capacity to import intermediate inputs and other goods and services which are necessary or help to foster economic development in the domestic market. There are many studies which show the positive effects of exports but very few focused on the role of imports, and this study contributes in this regard.. On the other hand the analysis of industrial contribution to the non industrial sectors is twofold: directly providing intermediate and capital goods to non industrial sectors and indirectly increasing exports and the capacity to import foreign inputs which contribute to domestic production.

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)0.002
metaresearch head score (Gemma)0.006
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.884
Threshold uncertainty score0.231

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.134
GPT teacher head0.263
Teacher spread0.129 · 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

Citations22
Published2006
Admission routes1
Has abstractyes

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