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Record W1820350860 · doi:10.5539/ijef.v7n11p62

Effects of Regional Bank Merger on Small Business Borrowing: Evidence from Japan

2015· article· en· W1820350860 on OpenAlexvenueno aff
Hironobu Miyazaki, Hiroyuki Aman

Bibliographic record

VenueInternational Journal of Economics and Finance · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsnot available
FundersZengin Foundation For Studies On Economics And FinanceToyo UniversityJapan Society for the Promotion of ScienceNanzan University
KeywordsLoanBusinessPortfolioFinancial systemEconomies of scaleSmall businessMonetary economicsEconomicsFinance

Abstract

fetched live from OpenAlex

This study examines the impact of a regional bank merger in Japan on borrowing by small businesses, focusing on firms that borrow from the acquiring bank, the acquired bank, or both. First, we find that post-merger borrowing costs declined. This result suggests that small borrowers enjoy more favorable post-merger financing conditions because efficiencies from economies of scale lead to lower costs. Second, we find that post-merger borrowing costs decline for firms that borrow only from the acquiring or acquired bank, whereas they did not decline for firms that borrow from both. Third, we find that only small business loans to firms that borrow from both the acquiring and acquired banks decrease post-merger. This result suggests that small business lending might decline because of a merged bank’s loan portfolio and lending strategy.

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)0.005
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 score0.028
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.001
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 head0.045
GPT teacher head0.238
Teacher spread0.193 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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