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Record W3084744244 · doi:10.1108/jdqs-01-2015-b0005

Corporate Payout Policy and CEO‘s Inside Debt Holdings

2015· article· en· W3084744244 on OpenAlexaff
Yura Kim, Jeongsun Yun, Hyun Woo Choi, Gyu-Young Hwang

Bibliographic record

VenueJournal of Derivatives and Quantitative Studies 선물연구 · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsDebtDividend payout ratioMonetary economicsEquity (law)BusinessDividendDividend policyExecutive compensationShareholderFinancial systemEconomicsFinanceCorporate governance

Abstract

fetched live from OpenAlex

Literature documents that executives' inside debt holdings (debt-based managerial compensation) such as defined-benefit pensions and retirement funds are often unfunded and unsecured and have long maturities, and thus provide managerial incentives to pursue strategies to avoid the overall firm risk. This study investigates the effect of managerial inside debt compensation relative to equity-based compensation on a firm's dividend payout policy. We find that a inside debt holdings are positively associated with various measures of a firm's dividend payout policy. Additionally, we find empirical evidence in firms with inside debt holdings that the inverse relationship between high default risk measured by KZ index and dividend payout weakens as the portion of inside debt relative to equity-based compensation rises. This finding indicates that the needs for the firm to restrain dividend payouts to equity holders is reduced as the executive's debt-to-equity compensation ratio becomes larger. Overall, the results suggests the mitigating effect of executives' inside debt holdings on the conflicts between bondholders and shareholders can lead to generous payout 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 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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score0.597

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.138
GPT teacher head0.319
Teacher spread0.182 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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