Mobile money, credit to deposit ratio and monetary policy: Empirics from Ghana
Bibliographic record
Abstract
The effectiveness of monetary policy in Ghana has been questionable with the advent of mobile money activities, which are gradually replacing some of the roles of commercial banks. This study investigates the effects of mobile money transactions on Ghanaian commercial banks' credit-to-deposit ratio and the effectiveness of the monetary policy rate in the era of mobile money services using ARDL techniques, Granger causality and impulse response functions. The study reveals that Ghanaian commercial banks' credit-to-deposit ratio decreases with increased mobile money transactions, indicating a substitutability relationship. Banks' credit-to-deposit ratio is impacted by non-performing loans and asset returns, while the monetary policy rate has an insignificant impact. The results from the IRFs also showed that a positive shock to monetary policy reduces banks’ credit-to-deposit ratio but increases mobile money transactions and non-performing loans. For policy implications, collaboration between commercial banks and mobile money service providers can be enhanced through interoperability services.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".