Cross-border banking and the transmission of global shocks to credit cycles in developing economies: A commodity price cycles channel
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".