Determinants of the Capital Level of Banks in Hong Kong
Bibliographic record
Abstract
Banks in Hong Kong generally maintain capital adequacy ratios well above the regulatory requirement. The buffers are largely determined by the internal considerations of the banks, their responses to market discipline, and the regulatory framework. Despite the presence of excess capital, banks still respond to changes in capital requirements, and the buffer will only partially absorb a change in the regulatory requirement. The minimum capital requirement, therefore, remains an effective policy instrument. To the extent that part of the high capital buffer is due to the agency problem, information asymmetries, or a mismatch between the expectation of the regulator and banks over the approach to maintaining a capital buffer to prevent a breach of capital requirements, action could be taken to improve the use of capital. In this connection, the initiative under Basel II is expected to help address some of these issues. Our analysis also confirms that banks tend to hold a higher CAR in economic downturns, but a lower capital ratio in upturns. The implications of such a procyclical nature of the capital ratio on the economy, and how it may be affected by the forthcoming changes in the more risk-sensitive approach under Basel II, are worth exploring.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".