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Record W4394855384 · doi:10.1080/13691066.2024.2341623

Do the relationship paths between capital structure and investment efficiency depend on information asymmetry? A comparison between emerging and developed countries

2024· article· en· W4394855384 on OpenAlexaff
Ehsan Poursoleyman, Gholamreza Mansourfar, Saeid Homayoun, Samira Joudi

Bibliographic record

VenueVenture Capital · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsLeverage (statistics)Information asymmetryEmerging marketsDebtBusinessInvestment (military)Capital structureMonetary economicsMaturity (psychological)Debt ratioFinanceEconomicsFinancial system

Abstract

fetched live from OpenAlex

This paper aims to analyze the moderating role of debt maturity and the mediating role of information asymmetry in the relationship between financial leverage and investment efficiency and to compare the results between firms domiciled in emerging and those headquartered in developed countries. Using two proxies for investment efficiency, the results showed that debt maturity moderates the association between financial leverage and investment efficiency at both levels of developed and emerging countries. This paper also confirmed that information asymmetry carries the influence of financial leverage to investment efficiency only for those enterprises headquartered in emerging countries.

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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.019
GPT teacher head0.239
Teacher spread0.220 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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