Determinants of Bank Failures in Multiple-Currency Regime in Zimbabwe (2009–2012)
Bibliographic record
Abstract
Upsurge in bank failure cases under a more stable currency environment are rare, but the Zimbabwean case raised a lot of questions, which justified the need to deeply investigate sources of bank failures. This is considered an imperative move considering the impact that bank failures pose to stakeholders outside the banking sector such as investors and depositors, the Zimbabwean banking sector itself as well as the entire economy. This study investigated the determinants of bank failures in Zimbabwe under the multicurrency environment. The study employed pooled logit estimator using general to specific logit estimation procedure on fourteen banks by making use of 2009–2012 panel data. Empirical findings indicated that the macroeconomic environment, in particular GDP growth rate, has much influence on bank failure than any other bank fundamental. Among bank fundamentals, liquidity, profitability and capitalisation proved to be prominent bank related determinants of bank failures in their respective order. Findings also suggest that loan-to-deposits ratio (LTD), deposits-to-assets ratio (DTA), gross revenue ratio (GRR), return on assets (ROA), efficiency ratio (EFR), SIZE and GDP growth rate (GDP) variables are negatively correlated to the possibility of banks failing while loan-to-assets (LTA) have positive influence on bank failures. Based on these findings the researcher recommends that RBZ must accentuate liquidity and capital requirements since both liquidity and capital ratios were significant and had higher marginal effects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".