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Record W4287151243 · doi:10.18280/ijsse.120301

Econometric Analysis of the Formation of Deposit Resources of Households and Their Role in Ensuring Financial Security of the State

2022· article· en· W4287151243 on OpenAlexvenueno aff
Dubyna Maksym, Tarasenko Olena, Popova Liubov, Kalchenko Olga, Safonov Yuriy, Lozychenko Oleksandr

Bibliographic record

VenueInternational Journal of Safety and Security Engineering · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEconomic and Technological Developments in Russia
Canadian institutionsnot available
Fundersnot available
KeywordsState (computer science)BusinessEconometric analysisEconomicsFinanceEconometricsComputer science

Abstract

fetched live from OpenAlex

Within the article, the formation of deposit resources of households and their role in ensuring financial security of the state is considered. Significant attention is paid to the formation of such resources within the financial system. To this end, a statistical analysis from 2007 to 2020 of the main trends in the formation of deposits by households in Ukraine, a study of the impact of macroeconomic factors on this process is carried out, peculiarities of the deposit market in periodic economic and political instability are substantiated. The econometric analysis of the impact of certain macroeconomic factors on the creation of these resources within the national economy was also conducted. Accordingly, the article included the national currency exchange rate, the level of the average wage and the level of the real weighted average interest rate on time deposits. The methodology for constructing a multifactor linear regression model was chosen for econometric modeling. This model was also tested for adequacy. In the article, the role of household deposit resources in ensuring financial security of the state is also described in detail, the importance of providing stable conditions for the functioning of the deposit services market in order to resist external and internal threats is substantiated.

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 score0.403
Threshold uncertainty score0.122

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.006
GPT teacher head0.196
Teacher spread0.190 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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