The Concentration of the Banking Industry and Its Exposure to Financial Contagion
Bibliographic record
Abstract
This paper focuses on the effects that the concentration of the banking industry has on its exposure to the risk of systemic crises due to direct, balance-sheet financial contagion. Studying three stylized (and analytically tractable) classes of interbank networks – namely the complete, star and ring networks – we show that the magnitude of the smallest insolvency shock that is capable of causing the default of all banks in the system depends on the degree of concentration of the industry. Concerning complete and ring interbank networks, we obtain that the more concentrated the banking system is, the smaller the magnitude of the shock that induces the insolvency of the entire system. That is, concentration renders the banking system more fragile. Conversely, we show that the opposite applies to star interbank networks – i.e. networks composed of a bank at the centre connected to a set of peripheral banks that are not connected among themselves. In this case, the more concentrated the industry, the larger the smallest shock that causes a systemic crisis, i.e. the smaller the exposure to systemic risk.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".