Comparative analysis of the impact of balance sheet size on bank operations in the Republic of Serbia in the period before and during the Covid-19 pandemic
Bibliographic record
Abstract
This paper aims to analyze the impact of the size of banks operating in the Republic of Serbia on the main indicators of their business activity and assess whether the Covid-19 pandemic has changed the nature and intensity of this impact. The research was conducted on a representative sample of twenty-three domestic banks. The paper's conclusions are based on the results of applying static panel regression models and cover the period from the second quarter of 2014 to the third quarter of 2021. From the study results, it can be concluded that larger banks reduced lending activities and increased liquidity during the pandemic compared to smaller banks. This had no impact on their profitability, meaning that banks achieved higher returns on capital compared to smaller banks, as in the prepandemic period. In addition, the study found that larger banks reduced the ratio of capital to total assets during the pandemic compared to smaller banks, but not to the extent that threatened the banking sector's stability.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".