Liquidity Provision, Ambiguous Asset Returns and the Financial Crisis
Bibliographic record
Abstract
For an economy with dysfunctional intertemporal financial markets the financial sector is modelled as a competitive banking sector offering deposit contracts. In a setting related to Allen and Gale (JoF, 1998) properties of the optimal liquidity provision are analyzed for illiquid assets with ambiguous returns.In the context of our model, ambiguity -- i.e. incalculable risk -- leads to dynamically inconsistent investor behaviour. If the financial sector fails to recognize the presence of ambiguity, unanticipated fundamental crises may occur, which are incorrectly blamed on investors 'loosing their nerves' and 'panicing'.The basic mechanism of the Financial Crisis resembles the liquidation of illiquid assets during a banking panic. The combination of providing additional liquidity and supporting distressed financial institutions implements the regulatory policy suggested by the model.A credible commitment to such 'bail-out policy' does not create a moral hazard problem. Rather, it implements the second best efficient outcome by discouraging excessive caution. Reducing ambiguity by increasing stability, transparency and predictability -- as suggested by ordo-liberalism and the 'Freiburger Schule' -- enhances ex-ante welfare.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".