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Record W2157665626 · doi:10.1111/1540-5982.00158

Skill differentiation and wage disparity in a decentralized matching model of North–South trade

2002· article· en· W2157665626 on OpenAlexvenueno aff
Hesham M. Abdel–Rahman, George Norman, Ping Wang

Bibliographic record

VenueCanadian Journal of Economics/Revue canadienne d économique · 2002
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic theories and models
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsWageWelfare economicsMatching (statistics)Wage inequalityImperfectProduction (economics)Nash equilibriumMicroeconomicsLabour economicsMathematics

Abstract

fetched live from OpenAlex

In this paper we develop a North–South trade model in which the South produces food and the North produces both food and a high–tech good. Food production is undertaken by unskilled workers, while the high–tech product is made only by horizontally differentiated skilled workers. Owing to the possibility of a peer–group effect, we allow the unskilled workers in the North to be equally or more productive than in the South. Horizontal matching of skilled workers is generally imperfect and the skilled wages are determined by a symmetric Nash bargain. We characterize two different types of equilibrium: a closed–economy equilibrium without trade and a free trade equilibrium without labour mobility. We then extend the benchmark framework to consider the presence of transport costs. In all cases with trade, the equilibrium properties of goods pricing, the volume of trade as well as between–group and within–group wage inequality are examined. JEL Classification: F10, D51, D63, J31 Différentiation d’habiletés et disparité de salaires dans un modèle décentralisé de commerce nord–sud dans lequel les habiletés sont arrimées. Ce mémoire développe un modèle de commerce international nord–sud dans lequel le Sud produit de la nourriture et le Nord produit à la fois de la nourriture et un bien de haute technologie. La production de la nourriture nécessite seulement une main d’œuvre non–spécialisée, alors que la production du bien de haute technologie réclame seulement une main d’œuvre spécialisée et différentiée horizontalement. On assume que les travailleurs non–spécialisés dans le Nord sont aussi productifs ou plus productifs que ceux dans le Sud. Pour ce qui est des travailleurs spécialisés, l’arrimage horizontal est généralement imparfait et les salaires sont déterminés par une négociation symétrique à la Nash. On définit deux types d’équilibres : un équilibre en économie fermée sans commerce international, et un équilibre de libre échange sans mobilité des travailleurs. On étend alors le cadre de référence pour prendre en compte les coûts de transport. Dans tous les cas où il y a commerce international, on examine les propriétés en équilibre des prix des biens, du volume de commerce ainsi que de l’inégalité de salaires tant entre les groupes qu’à l’intérieur des groupes.

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)0.003
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 score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.115
GPT teacher head0.164
Teacher spread0.049 · 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

Citations2
Published2002
Admission routes1
Has abstractyes

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