Bank size, competition, and efficiency: a post-GFC assessment of Australia and New Zealand
Bibliographic record
Abstract
This paper investigates the impact of the global financial crisis (GFC) on banking market structure and efficiency in both countries, and the relationship of bank size and market competition with cost and profit efficiencies. Efficiencies of 11 Australian and New Zealand large commercial banks are estimated with a one-stage stochastic frontier approach (SFA) for the period 2003–2017. The Herfindahl- Hirschman Index (HHI) and Lerner index are used as proxies for market competition along with eight banking environment variables. Cost and profit efficiencies significantly declined during 2008 and 2009, but the impact of the GFC persisted longer in New Zealand than in Australia. The level of risk and competition has reduced, and bank size increased in the post-GFC period. Bank size is found to be positively associated with bank efficiency. Market competition negatively influenced cost and profit efficiencies during the study period, especially after the GFC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".