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Record W1525971336 · doi:10.1111/1467-8462.12114

Information Disclosure and Bank Risk‐Taking under a Partially Implicit Deposit Insurance System: Evidence from China

2015· article· en· W1525971336 on OpenAlex
Zongrun Wang, Jiangyan Chen, Yuanyuan Wan, Yanbo Jin, Jared Anthony Mazzanti

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAustralian Economic Review · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsUniversity of Toronto
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsChinaBailoutDeposit insuranceBusinessGovernment (linguistics)Chinese financial systemBank runEmpirical evidenceActuarial scienceEmpirical researchMonetary economicsFinancial systemEconomicsFinanceFinancial crisisPolitical scienceMacroeconomics

Abstract

fetched live from OpenAlex

Abstract This article examines the role of information disclosure on bank risk‐taking behaviour in China. The study uses a game theory model to analyse the interaction mechanism between bank risk‐taking behaviour and its information disclosure under China's partially implicit deposit insurance system. It is found that banks that are more likely to receive a government bailout when they are in trouble tend to take excessive risk. In addition, the implicit guarantee weakens the market‐monitoring effect of information disclosure. Using data from 60 commercial banks in China, we find strong empirical support for our findings.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.052
GPT teacher head0.270
Teacher spread0.218 · 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