Bibliographic record
Abstract
Using a new data set from the Office of the Superintendent of Financial Institutions, I conduct an in-depth study on cost efficiency and returns to scale (RTS) in Canadian banking. I estimate a transcendental log cost function for the six largest Canadian commercial banks which account for approximately 90% of chartered bank assets over the 1996-2011 sample period. The minimal amount of firm entry and exit simplifies many difficulties in the analysis, and the panel dynamic ordinary least squares estimator (PDOLS) provides less biased results than the fixed-effect OLS. Departing from previous studies in banking, I calculate whether the estimated cost function satisfies the microeconomic properties of a monotonicity and price concavity. To my knowledge, this is the first paper to find evidence of constant RTS among the Canadian banks. The result is robust to a number of different asset and price specifications. Furthermore, there is little evidence to suggest cost inefficiencies among the large Canadian banks. This is true whether the Greene (2005) true fixed effects ML estimator is estimated or a distribution-free approach is measured. Combining these two results, the large Canadian banks managed costs efficiently and minimized costs from 1996 to 2011.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".