The New Basel Capital Accord and the Cyclical Behaviour of Bank Capital
Bibliographic record
Abstract
The authors conduct a counterfactual simulation of the proposed rules under the new Basel Capital Accord (Basel II), including the revised treatment of expected and unexpected credit losses proposed by the Basel Committee in October 2003. When the authors apply the simulation to Canadian banking system data over the period 1984–2003, they find that capital requirements for banks will likely fall in absolute terms even after allowing for the new operational risk charge (bearing in mind that the induced behavioural response of banks to the changed incentives under Basel II is not captured). The impact on the volatility of required bank capital is less clear. It will depend importantly on the credit quality distribution of banks' loan portfolios and on the precise way in which they calculate expected and unexpected losses. Sensitivity analysis, including that based on a range of hypothetical distributions for banks' loan portfolios, shows the potential for a substantial increase in implied volatility. Moreover, if historical relationships are a good indicator of the future, changes in required capital and provisions for commercial and industrial, interbank, and sovereign exposures will likely be countercyclical under Basel II (i.e., capital requirements will increase during recessions). This raises questions about the new accord's potentially procyclical impact on banks' lending behaviour, and the resultant macroeconomic implications.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".