Effects of corporate governance on high growth rate: evidence from Vietnamese listed companies
Bibliographic record
Abstract
High-growth firm is the research object of economic and business studies, because of its important influence on job creation, innovation, and tax revenues increase for the nation. This paper is designed to find some empirical evidence on the role of corporate governance on the firm's growth, thereby providing some policy implications for improving corporate governance activities in practice. Using a sample of 241 listed companies on Vietnam's stock market in the period 2008-2017, divided into 2 groups: high-growth firms and non-high-growth firms and applying a GMM regression with the dependent variable as 3-year compound growth rate, the study finds evidence of factors affecting the growing ability of corporate governance, namely: the ownership structure, the characteristics of the Board of Directors (size, independence, gender, non-executive member, experience), and the characteristics of the CEO (age, educational level, ownership, duality).
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 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".