Determinants of Capital Structure: Evidence From Malaysian Food and Beverage Firms
Bibliographic record
Abstract
This paper investigates the firm-specific elements, which are profitability, growth, tangible assets and liquidity in determining the capital structure of Food and Beverage (F&B) firms in Malaysia. The research employed panel data regression model based on ordinary least square (OLS) method. The sample of research consists of eight firms listed in the food producer segment in Bursa Malaysia for the period between 2013 and 2018, with a total observation of 48 firms-years. Debt to equity was chosen as dependent variable. On the other hand, profitability, asset growth, tangibility of assets, and liquidity were selected as independent variables. The findings showed that profitability and tangibility of assets are positively related to debt to equity. Meanwhile, growth of assets and liquidity were insignificant to the dependent variable. The trade-off theory of capital structure is very much applicable to the F&B firms in Malaysia due to the fact that profitability and tangibility of assets have significant relationship with debt.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".