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Record W2588067679 · doi:10.1111/cjag.12133

The Intensive and Extensive Margins of China's Agricultural Trade

2017· article· en· W2588067679 on OpenAlexvenueno aff
Xiaoheng Zhang, Xianhui Geng, Xu Tian

Bibliographic record

VenueCanadian Journal of Agricultural Economics/Revue canadienne d agroeconomie · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsChinaMargin (machine learning)ProductivityAgricultureEconomicsInternational tradePolitical scienceHumanitiesWelfare economicsGeographyEconomic growthPhilosophy

Abstract

fetched live from OpenAlex

Utilizing the 1995–2013 Harmonized System's six‐digit agricultural product data for China, this study measures the dual margin contribution to export growth in China's agricultural products. Results show that contribution from the intensive margin has reached and been staying at a high level since 2007, providing new insight in explaining the deteriorating terms of trade in China's agricultural products. In light of this, an empirical analysis of the determinants of dual margins indicates that larger trading partners lead to less growth in exports of both new and existing products. Destination countries with higher labor productivities and lower fixed trade costs are China's target markets to convert intensive‐margin‐driven growth into extensive‐margin‐driven growth. In addition, the impact of relative labor productivity and free trade agreements on the intensive margin differs between primary and processed products due to their product characteristics. Au moyen des données à six chiffres du produit agricole pour la Chine provenant du Système harmonisé de 1995–2013, cette étude mesure la double marge de contribution à la croissance, des exportations des produits agricoles chinois. Les résultats démontrent que la contribution provenant de la marge intensive a atteint et demeure élevée depuis 2007, fournissant de nouvelles explications aux termes de l′échange des produits agricoles chinois. Étant donné ces informations, une analyse empirique des déterminants des doubles marges indique que les grands partenaires commerciaux mènent à moins de croissance dans les exportations à la fois de produits nouveaux et existants. La Chine choisit comme cibles les pays de destination avec une productivité élevée de la main‐d'œuvre et de faibles coûts fixes de commerce pour convertir la croissance stimulée par les marges intensives en croissance stimulée par les marges extensives. Qui plus est, l'impact de la productivité relative de la main‐d'œuvre et des accords de libre‐échange sur les marges intensives diffère des produits primaires aux produits transformés en raison des caractéristiques du produit.

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)0.001
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 score0.017
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.167
Teacher spread0.130 · 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

Citations11
Published2017
Admission routes1
Has abstractyes

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