The nonlinear effects of banks' vulnerability to capital depletion in euro area countries
Bibliographic record
Abstract
When capital in the banking system becomes depleted, the degree to which financial intermediation and the macroeconomy are adversely affected is likely to depend on the financial and macroeconomic environment. However, existing studies either assume that the effects of bank capital shocks are linear or ignore feedback effects and the impact on the macroeconomy. Using data on the largest euro area countries and Bayesian Panel Threshold VARs, we investigate the importance of different factors in amplifying shocks in banks' vulnerability to capital depletion. Our results demonstrate that nonlinearities matter. When the banking sector is already vulnerable to large capital losses, it is more difficult for banks to accommodate a depletion in capital and lending and economic activity contract more severely. Similarly, low interest rates, which are typically associated with low bank margins and profitability, also lead to a larger decline in lending. De-risking is also more pronounced in these cases. The state of the business cycle, though, does not influence the propagation of shocks to the same extent. We conclude that financial factors play a larger role than the macroeconomic environment in heightening shocks to banks' vulnerability to capital depletion.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".