The Ex-Ante Versus Ex-Post Effect of Public Guarantees
Bibliographic record
Abstract
In October 2006, Dominion Bond Rating Service (DBRS) introduced new ratings for banks that account for the potential of government support. The rating changes are not a reflection of any changes in the respective banks’ credit fundamentals. We use this natural experiment to evaluate the consequences of bail out expectations for bank behavior using a difference in differences approach. The results suggest a striking difference between the effects of bail out probabilities during calm times (“ex ante”) versus during crisis times (“ex post”). During calm times, higher bail-out probabilities result in higher risk taking, consistent with the moral hazard view and much of the empirical literature. However, in crisis times, we find that banks with higher bail out probabilities tend to increase their risk taking less compared to banks that were ex ante unlikely to be bailed-out. Charter values are one part of the explanation: Supported banks may have a funding advantage relative to non-supported banks during the crisis. However, we cannot rule out that other factors also may be playing a role, including tighter supervision of supported banks in crisis times.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 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".