The relationship between Malaysian public-listed firms’ corporate governance and their capital structure
Bibliographic record
Abstract
The purpose of this paper is to investigate the relationship between corporate governance practices and capital structure of public-listed companies in Malaysia. Using the annual reports of 273 Malaysian public-listed firms on the Bursa Malaysia between 2008 and 2012, hierarchical multiple regression analysis was conducted. Corporate governance was measured by variables including board size, CEO duality, ownership structure, and board meeting. Capital structure was measured through four variables: debt-to-equity ratio, long-term debts, short-term debts, and debt ratio. The findings indicated that corporate governance practices have a positive influence on the debt-equity ratio, long-term debt, short-term debt and a debt ratio of capital structure. However, corporate governance practices’ influence on the debt ratio is found statistically insignificant. The findings also indicate that firm size moderates the relationship between corporate governance variables and capital structure. Empirically, these findings are useful for measuring and understanding financing decisions taken by the Malaysian public listed firms. It also offers insights to policymakers interested in enhancing the role of corporate governance in formulating management strategies.
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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 | 0.001 | 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".