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Record W2597155431 · doi:10.5430/ijfr.v8n2p75

Capital Structure Choice and Firm Value: New Empirical Evidence from Asymmetric Causality Test

2017· article· en· W2597155431 on OpenAlexvenueno aff
Kartal Demirgüneş

Bibliographic record

VenueInternational Journal of Financial Research · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsCapital structureEconomicsEconometricsCausality (physics)Shock (circulatory)Value (mathematics)Enterprise valueEmpirical evidenceTurkishGranger causalityMonetary economicsDebtMacroeconomicsMathematicsStatisticsAccounting

Abstract

fetched live from OpenAlex

This study aims to analyze the possible asymmetric causal relationship between capital structure and firm value by employing the asymmetric causality test of Hatemi-J (2012), on a time series data of Turkish manufacturing industry (consisting of Borsa Istanbul listed manufacturing firms) for the period of 1990.Q1-2015.Q4. Test results point out a unidirectional asymmetric causal relationship between capital structure and firm value, indicating that capital structure Granger-cause firm value when shocks are negative, but not when shocks are positive. More explicitly, a decrease in total debt ratio leads to a decrease in the market-to-book value ratio. Considering the effect of only negative shock, this empirical finding also supports partial evidence to the validity of trade-off theory which predicts a positive relationship between debt level and firm value.

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)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0010.000
Research integrity0.0000.001
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 head0.155
GPT teacher head0.407
Teacher spread0.251 · 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.

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

Citations27
Published2017
Admission routes1
Has abstractyes

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