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Record W1862534233 · doi:10.5539/ijef.v7n8p31

Regulation of Bank Capital Requirements and Bank Risk-Taking Behaviour: Evidence from the Nigerian Banking Industry

2015· article· en· W1862534233 on OpenAlexvenueno aff
Georgina Obinne Ugwuanyi

Bibliographic record

VenueInternational Journal of Economics and Finance · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsnot available
Fundersnot available
KeywordsCapital requirementCapital adequacy ratioRisk appetiteCapital (architecture)Economic capitalEconomicsRisk-adjusted return on capitalBank regulationFinancial capitalMonetary economicsFinancial systemBusinessCapital formationFinanceRisk managementHuman capitalMicroeconomicsMarket economyIncentive

Abstract

fetched live from OpenAlex

This study examines how the regulation of bank minimum capital base in Nigeria interacts with the bank risk-taking behavior of the bank operators. Adopting the ex-post-facto researchdesign the study presented in this paper ascertained the effect of the regulation of bank capital on bank risk-taking behavior utilizing post financial crises annualreports of quoted banks from years 2009-2013. Simultaneous linear regressions were used to ascertain the behaviour of banks to regulatory capital requirements from time to time. The panel least squares result suggests that risk, size, and interest margin (spread), and capital adequacy relate positively with changes in risk thus implying that an increase in size and capital, increases bank risk taking appetite. Conclusively, therefore, regulation pressure has a negative correlation with capital adequacy and risk taking appetite but does not significantly affect the capital adequacy as well as risk taking appetite of Nigerian banks.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.055
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.057
GPT teacher head0.268
Teacher spread0.211 · 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

Citations15
Published2015
Admission routes1
Has abstractyes

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