Impacto de fatores macroeconômicos e da solvência sobre a eficiência bancária dos principais bancos brasileiros
Bibliographic record
Abstract
The literature on banking efficiency has grown a lot in recent years. In Brazil, due to the changes in the macro and microeconomic scenario, which made the environment more competitive and dynamic, this was no different. In this scenario, this study aims to estimate the partial impact of shocks on macroeconomic variables (representing future expectations, country risk measure, economic activity and inflation) and microeconomic variables (bank-specific, representing solvency) on the banking efficiency of the main financial institutions in Brazil, from the first quarter of 2009 to the fourth quarter of 2019. Efficiency scores are estimated through the stochastic frontier analysis (SFA), and the analysis of their interrelation with the other variables is done through the application of Vector Autoregression Models (VAR), followed by their structural analysis. In general, the results contribute to the literature, highlighting that each financial institution is its own and that there is no convergence between the samples analyzed for the highlighted 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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 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".