Bank Competition, Efficiency, and Stability in Macau
Bibliographic record
Abstract
Macau has the uppermost population density and the fourth-highest GDP per capita in the world. Macau’s banking system is regarded as one of the most important indicators of Macau’s macroeconomic growth and stability during its transformation into a wealthy and modern metropolis. In this study, we use a sample of 26 banks to explore the relationship of bank competition, efficiency and stability in Macau from its return to China in 1999 to 2016. Our results demonstrate that bank competition does cause efficiency in Macau throughout the study period. We also find indications of a positive but not significant connection between bank market power and bank fragility including income volatility and insolvency risk. Moreover, this study finds no evidence that the size of operations proxied by total bank loans and total assets would impact bank efficiency, indicating that economies of scale or bank market share don’t necessarily bring about efficiency in Macau. Our evidence contributes to the literature by being the first to thoroughly examine the relation of bank competition, efficiency and stability in Macau. The findings provide meaningful implications to the practitioners and policymakers to make sound decisions accordingly, especially to closely monitor and maintain a proper level of competition in Macau’s banking sector.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".