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Record W4253571495 · doi:10.5937/bankarstvo2104036r

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

2021· article· en· W4253571495 on OpenAlexaboutno aff
Željko Račić, Branka Paunović

Bibliographic record

VenueBankarstvo · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMarket liquidityPandemicProfitability indexBalance sheetQuarter (Canadian coin)BusinessCoronavirus disease 2019 (COVID-19)Sample (material)Capital (architecture)Financial systemDemographic economicsEconomicsFinanceGeographyMedicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.708

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.292
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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