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Record W4413406849 · doi:10.1016/j.irfa.2025.104515

Cross-border banking and the transmission of global shocks to credit cycles in developing economies: A commodity price cycles channel

2025· article· en· W4413406849 on OpenAlexaff
François d’Assises Babou Bationo, Victor Murinde, Issouf Soumaré

Bibliographic record

VenueInternational Review of Financial Analysis · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsUniversité LavalMarch of Dimes Canada
FundersForeign, Commonwealth and Development OfficeEconomic and Social Research CouncilDepartment for International Development, UK Government
KeywordsCommodityChannel (broadcasting)EconomicsMonetary economicsTransmission channelTransmission (telecommunications)International economicsBusinessFinanceTelecommunications

Abstract

fetched live from OpenAlex

The literature on the transmission of global credit market shocks to credit cycles in developing countries emphasizes the role of cross-border banking, but it seems to sidestep the important role of commodity trade. To address the gap, we hypothesize that global credit market shocks are transmitted to credit market cycles in developing economies directly through cross-border banking capital flows and indirectly through the interaction between bank capital flows and commodity price cycles. We specify plausible econometric models to represent the hypotheses, and we estimate the models using a panel sample of 74 developing countries. We uncover new robust evidence that cross-border banking capital flows directly accentuate credit cycles in developing countries. The evidence also identifies commodity price cycles as an important indirect transmission channel. We estimate that a 1 % change in the interaction term between cross-border banking capital flows and commodity price index increases credit cycles by about 4.11 basis points. Overall, these findings prompt policymakers in developing countries to pay attention to the commodity price cycles channel when designing policies to minimize vulnerability to global financial shocks.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.442
Threshold uncertainty score0.464

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
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 head0.015
GPT teacher head0.321
Teacher spread0.306 · 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 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

Citations2
Published2025
Admission routes1
Has abstractyes

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