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Record W4310015960 · doi:10.1016/j.heliyon.2022.e11906

Bank lending behaviour and macroeconomic factors: A study from strategic interaction perspective

2022· article· en· W4310015960 on OpenAlexaff
Huong Le, Thai Vu Hong Nguyen, Chrıstophe Schınckus

Bibliographic record

VenueHeliyon · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsUniversity of the Fraser Valley
FundersĐại học Kinh tế Thành phố Hồ Chí Minh
KeywordsEconomicsMonetary economicsPerspective (graphical)Macroeconomic modelMonetary policyPanel dataVietnameseStrategic interactionMechanism (biology)MacroeconomicsMicroeconomicsEconometrics

Abstract

fetched live from OpenAlex

This study investigates the moderating role of strategic interaction on the relationship between bank lending and macroeconomic factors, using panel data on Vietnamese commercial banks over 2008-2018. We find that the effect of macroeconomic and monetary policy shocks on bank lending behaviour is less pronounced when banks engage in a less competitively aggressive environment. The study contributes to the literature of bank lending by incorporating macroeconomic environment and micro (strategic interaction)-level to analyze the lending behaviour of an individual bank. Since the analysis of macroeconomic factors alone is insufficient to explain the aggregate relationships in the model of banking, understanding the nature of strategic interaction is essential to predetermine how bank lending behaviour relates to the transmission mechanism of monetary policy.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.044
GPT teacher head0.268
Teacher spread0.224 · 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 source (direct Gemma or distilled Codex), 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

Citations14
Published2022
Admission routes1
Has abstractyes

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