Corporate Governance and Capital Structure:Evidence from Taiwan SMEs
Bibliographic record
Abstract
This study examines the effects of corporate governance on capital structure, using the data of 145 small and medium-sized enterprises (SMEs) listed on the Taiwan Stock Exchange over the period 2000-2007. The results show that, when there is a high divergence between shareholdings and director seats, conventional industries prefer to use long-term debt financing, while high-tech industries prefer the opposite. For large firms, block-holders and independent directors prefer lower long-term debt financing, but family shareholders and managerial directors prefer lower short-term debt financing. We also find that family shareholding ratio and family directors are the two most important factors that affect the SMEs¡¯ debt ratio. The higher the family shareholding ratio is, the more short-term debt financing will be. However, family directors can reduce the incidence of using short-term debt to support long-term financial needs.
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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 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".