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Record W4251830784 · doi:10.1093/jae/13.2.302

Regionalism and Labour Market Structure: A CGE Analysis of UEMOA Customs Union

2004· article· en· W4251830784 on OpenAlexaff
Bernard Decaluwé

Bibliographic record

VenueJournal of African Economies · 2004
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsEconomicsOpenness to experienceCustoms unionComputable general equilibriumWelfareWageInternational economicsMarket structureRigidity (electromagnetism)Labour economicsMarket economyMacroeconomics

Abstract

fetched live from OpenAlex

In this study, we analyse the impact of the creation of a customs union among UEMOA (Western African Economic and Monetary Union) countries, with a special emphasis on the labour market structure. The implementation of the customs union reform translated in most of these countries, into a greater openness, even with third party countries. This greater openness raises concerns in these countries as regards its potential impact on welfare, production and employment. In contrast to previous papers, we relax the assumption of a perfect functioning of the labour market. We consider the presence of a dualism in the labour market and the downward rigidity of the wage of formal workers. Using a multi- country CGE model, we find that this rigidity could reduce significantly the gains of the customs union. Our simulation results suggest that the costs of this rigidity may reach 45%, as a proportion of the welfare gain obtained without rigidity.

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 score0.060
Threshold uncertainty score0.119

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 communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.021
GPT teacher head0.196
Teacher spread0.175 · 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

Citations0
Published2004
Admission routes1
Has abstractyes

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