Bibliographic record
Abstract
A bank panic is an expectation-driven redemption event that results in a self-ful…lling prophecy of losses on demand deposits.From the standpoint of theory in the tradition of Diamond and Dybvig (1983) and Green and Lin (2003), it is surprisingly di¢cult to generate bank panic equilibria if one allows for a plausible degree of contractual ‡exibility.A common assumption employed in the standard banking model is that returns are linear in the scale of investment.Instead, we assume the existence of a …xed investment cost, so that a higher riskadjusted rate of return is available only if investment exceeds a minimum scale requirement.With this simple and empirically-plausible modi…cation to the standard model, we …nd that bank panic equilibria emerge easily and naturally, even under highly ‡exible contractual arrangements.While bank panics can be eliminated through an appropriate policy, it is not always desirable to do so.We use our modelWe thank Todd Keister for his many insightful comments.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".