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Record W4393407375 · doi:10.1093/rcfs/cfae005

Shareholder-Creditor Conflict and the Resolution of Financial Distress

2024· article· en· W4393407375 on OpenAlexafffund
Yongqiang Chu, Ha Diep-Nguyen, Jun Wang, Wei Wang, Wenyu Wang

Bibliographic record

VenueThe Review of Corporate Finance Studies · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Insolvency and Governance
Canadian institutionsQueen's UniversityUniversity of Manitoba
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCreditorFinancial distressBusinessShareholderDistressFinanceFinancial systemCorporate governancePsychologyDebt

Abstract

fetched live from OpenAlex

Abstract Constructing a comprehensive data set of financially distressed firms that restructured their debts from 2000–2014, we find that firms with financial institutions’ loan-equity simultaneous holdings are more likely to restructure out of court than to file for bankruptcy. The effect is stronger when loans are oversecured and when the expected bankruptcy costs are larger. We use mergers of financial institutions and instrumental variable estimations to address potential endogeneity concerns. Firms with simultaneous holdings experience higher stock returns. The evidence suggests that mitigating shareholder-creditor conflict results in cost-effective resolutions of financial distress.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.596
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.056
GPT teacher head0.271
Teacher spread0.215 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2024
Admission routes2
Has abstractyes

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