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Record W2018366355 · doi:10.5539/ijef.v1n1p117

AFTA and the Intra-Trade Patterns among ASEAN-5 Economies: Trade-Enhancing or Trade-Inhibiting?

2009· article· en· W2018366355 on OpenAlexvenueno aff
Kim Lan Siah, Chee‐Keong Choong, Zulkornain Yusop

Bibliographic record

VenueInternational Journal of Economics and Finance · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsDistributed lagEconomicsGravity model of tradeEconomic integrationBilateral tradeInternational free trade agreementInternational tradeInternational economicsTrade barrierOrder (exchange)Comparative advantageGeographyEconometrics

Abstract

fetched live from OpenAlex

This paper examines ASEAN economic integration and its ability to promote intra-ASEAN trade, namely, Indonesia, Malaysia, Philippines, Singapore and Thailand. In order to achieve this goal, a modified gravity model is estimated within autoregressive distributed lag (ARDL) framework, or bounds testing approach for each of the five ASEAN countries based on data from year 1970 to year 2001. The empirical results indicate that the effects of the size of economy on bilateral trade flow in ASEAN are either trade-enhancing or trade-inhibiting dependent on the country-specific. There is evidence that AFTA preferential arrangements are important and prevalent in enhancing intra-ASEAN trade. However, ASEAN countries may not as a whole benefit from the formation of AFTA as the trade deflection might occur in the regional market.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.023
GPT teacher head0.214
Teacher spread0.190 · 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 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

Citations16
Published2009
Admission routes1
Has abstractyes

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