Banking market structure and efficiency: an assessment of the USA and Canada
Bibliographic record
Abstract
Purpose The study aims to analyze the changes in banking market structure and their impact on the bank efficiency. Design/methodology/approach This study uses a one-stage stochastic frontier analysis (SFA) to compare the impact of the market structure and the GFC on the economic efficiency of the major banks in both countries. Findings A significant negative impact of the GFC is observed on bank efficiency. Overall, Canadian banks posted better efficiency scores than their American counterparts. Additionally, cost-efficient banks are found to be more resilient to crises and more profit-efficient in the post-GFC period. The authors found that market power had a positive impact on the cost and profit efficiency of banks. Higher levels of equity, market power and concentration helped banks be more cost-efficient. Research limitations/implications Only large banks are selected for study although it represents the majority stake of both banking sectors. Practical implications Banking regulators should include more measures to assess the banking market structure and performance. Originality/value As per the best knowledge of the authors, it is the first study to assess the change in banking market structure and efficiency of the US and Canadian banking sectors in the post-GFC period.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".