Measuring the Severity of a Banking Crisis and Finding Its Associated Factors: How Are the Factors Different for Simple and Severe Banking Crises?
Why this work is in the frame
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Bibliographic record
Abstract
This study measures the severity of a banking crisis by using its duration and the cost. Using this new methodology, we find that the factors associated with a severe banking crisis are not quite the same as those associated with a simple banking crisis. An ordered logit model and a large panel data set were used for this study. One of our major findings is that there exists a four-year time lag between an economic boom, or financial system liberalization, and the occurrence of a severe banking crisis in a country. This indicates that banking problems start much earlier than the time when they are revealed as banking crises. This study also finds that the lower the remains of a past banking crisis, the higher the probability of a severe banking crisis. It could be due to less-attentiveness of banking sector policy-makers with elapsed time. A high rate of inflation, existence of an explicit deposit insurance scheme, and a weak institutional environment are found to be common factors positively associated with both simple and severe banking crisis.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it