Determining the Factors Affecting Capital Structure Decisions of Real Sector Companies Operating in ISE
Bibliographic record
Abstract
Corporate capital structure remains a controversial issue in modern corporate finance. Since the seminal work by Modigliani and Miller (1958), a plethora of research has been undertaken in attempting to identify the determinants of capital structure. This paper analyzes the capital structure determinants of manufacturing, merchandising and service firms operating in Istanbul Stock Exchange (ISE) during the period from 2010 to 2013 comprising of 218 companies. This study addresses the following questions: Are the capital structure determinants of three types of firms in ISE driven by different factors? To answer this question, panel data methodology is applied to the sample of firms for the period from 2010 to 2013. The results show that the manufacturing and merchandising firms exhibit similarities in their capital structure choices. For those firms, size and firm growth are positively related to leverage, whereas profitability have a negative relationship with their debt to assets ratio. For service firms, size and non-debt tax shield have significant positive impact on leverage but profitability negatively related to leverage. These findings provide evidence in favour of trade off theory and pecking order theory.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".