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The Impact of Trade Liberalization on Enterprises in Small Backward Economies: the Case of Chad and Gabon

2006· article· en· W3124477277 on OpenAlexaff
Giorgio Barba Navaretti, Riccardo Faini, Bernard Gauthier

Bibliographic record

VenueReview of Development Economics · 2006
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsEconomicsProductivityIncentiveVirtuous circle and vicious circleDevaluationInternational economicsLiberalizationPanel dataFree tradeInternational tradeMonetary economicsMacroeconomicsMarket economyExchange rate

Abstract

fetched live from OpenAlex

Abstract This paper examines the impact of trade and fiscal reforms and of the 1994 devaluation of the CFA franc on enterprise development in Chad and Gabon. These reforms provide a natural experiment to assess the impact of trade liberalization in countries with a small and backward manufacturing sector. The empirical analysis is based on a new panel data base covering virtually the whole population of manufacturing firms in Chad and Gabon, and containing data spanning from the year before to two years after the reforms. The paper finds that although firms’ response to changing incentives was non‐negligible, with a shift of output from nontradable to tradable and an increase in productivity, the reform process was unable to generate a virtuous and self‐sustained circle, where export expansion brings a generalized productivity increase which in turn feeds on further export growth.

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)0.002
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 score0.167
Threshold uncertainty score0.332

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.003
Scholarly communication0.0040.001
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.230
Teacher spread0.194 · 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

Citations1
Published2006
Admission routes1
Has abstractyes

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