Active cost management in Argentinean banks: an empirical test of sticky costs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study provides a test and analyses the existence and magnitude of sticky costs in an emerging economy’s financial sector. The results use data from Argentinean banks between 2005 and 2010 (total costs increase 0.55% for every 1% total income increase and decrease only 0.13% per 1% total income decrease) and show that the sticky cost magnitude is similar but more pronounced than those documented in previous studies, both in central economies (Anderson et al., 2003; Calleja et al., 2006) and in emerging economies (Ribeiro de Medeiros and de Souza Costa, 2004). This kind of analysis’ absence from Latin-American companies’ financial sectors, particularly those in Argentina, is one of the main characteristics of this study. Its main contribution to the literature is the topic’s novelty and its empirical validation in a G-20 emerging economy’s financial sector.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it