The interactive relationship between credit growth and profitability of people's credit funds in Vietnam
Bibliographic record
Abstract
This study purposes to discover the interactive relationship between credit growth and profitability and to examine factors that affect the credit growth and profitability of people's credit funds (PCFs). After regression analysis on a set of panel data from 2013 to 2018 on 24 selected PCFs, it appeared that deposit growth and loan-to-deposit ratio had positive relationships with credit growth, and capital adequacy ratio and profitability had negative relationships with credit growth of PCFs. The age of PCFs has a positive relationship with profitability, while the credit growth, debt-to-equity ratio, non-performing loan ratio, economic growth and inflation have negative relationships with profitability of PCFs. The study found the credit growth and profitability have relationships with each other in a contrary trend. Based on the findings the study proposes policy measures that could be implemented by the managers to increase PCFs' credit growth rate and profitability.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 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".