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Record W4410483402 · doi:10.1016/j.intfin.2025.102176

Financial sector development and intra-African trade

2025· article· en· W4410483402 on OpenAlexaff
Lewis-Landry Gakpa, Issouf Soumaré, Hugues Kouadio, Charles Adjasi

Bibliographic record

VenueJournal of International Financial Markets Institutions and Money · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsEconomicsFinancial sector developmentFinancial sectorInternational economicsFinance

Abstract

fetched live from OpenAlex

• Relationship between Financial Sector Development (FSD) and intra-African trade. • Positive impact of financial development and cross-border banking flows on intra-African trade. • Financial institution indicators have more impact than financial market indicators. • The relationship between financial development and trade is heterogeneous across African regions. • Financial development affects trade indirectly through the services and industrial sectors. This paper examines the nature of the relationship between Financial Sector Development (FSD) and intra-African trade. Using a sample of African countries with available data from 1998 to 2021 , and robust estimation techniques that address endogeneity and omitted variables biases, we find a positive significant impact of the composite financial development indicator and cross-border banking flows on intra-African trade. Further analysis reveals that the effects of the financial institution sub-indicators are more pronounced than those of the financial market sub-indicators. The effects are also heterogeneous across the different African Regional Economic Communities (RECs). Finally, our results show that financial sector development affects intra-African trade indirectly through its impact on the services and industrial sectors.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.950
Threshold uncertainty score0.537

Codex and Gemma teacher scores by category

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

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 head0.034
GPT teacher head0.227
Teacher spread0.192 · 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 teacher head, 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
Published2025
Admission routes1
Has abstractyes

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