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Record W2964884915 · doi:10.20849/abr.v4i2.617

Potential Gains to New Zealand From CPTPP Membership

2019· article· en· W2964884915 on OpenAlexaboutno aff
Satya Gonuguntla

Bibliographic record

VenueAsian Business Research · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsTariffInternational tradeProduct (mathematics)Comparative advantageInternational economicsGeneral partnershipRevealed comparative advantageBusinessEconomicsFinance

Abstract

fetched live from OpenAlex

New Zealand is a signatory to the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) consisting of 11 countries. NZ does not have any bilateral trade agreement with three member countries viz., Canada, Japan, and Mexico which account for 73% of CPTPP’s GDP. Presently, NZ accounts for less than 1% of the merchandise imports of these countries. This paper investigates whether CPTPP membership would enable NZ to increase its exports to these member countries. In other words, does CPTPP membership enhance NZ’s Trade Intensity with the selected member countries? An analysis of the Trade Intensity Indices show that the value of trade with Canada, and Mexico is less than optimal, and with Japan it has been on the decline which can be attributed to the fact that these countries mostly import high value added goods such as capital goods whereas, NZ mostly exports primary goods such as animals. A further analysis of NZ’s Revealed Comparative Advantage reveals that NZ’s comparative advantage is mostly concentrated in primary products. As a consequence, the scope for NZ to enhance its exports to the selected member countries is limited in the post CPTPP era, and any gains arising out of the agreement would be mostly in the form of tariff reductions, and relaxation of non-tariff barriers. The contribution of this paper is about highlighting NZ’s product-wise Revealed Comparative Advantage in relation to the selected member countries, which reveals that NZ has the potential to export Intermediate and Consumer goods, in addition to the Primary goods.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.001

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 head0.149
GPT teacher head0.302
Teacher spread0.152 · 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 designTheoretical or conceptual
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
Published2019
Admission routes1
Has abstractyes

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