Political Connection and Firm’s Performance Among Malaysian Firms
Bibliographic record
Abstract
The purpose of this study is to examine the influence of political connections on firms’ performance by controlling the effect of board attributes and firms’ characteristics. Specifically, it is argued that politically connected firms enjoy a lot of benefits from the government and said to provide greater chances for the firms to increase their wealth. By using 156 public listed firms between the study period of 2012 to 2017, this study maps out political connection based on the 13th Malaysian general election. The results reveal that the appearance of political connections on board gives significant and negative effect on Tobin Q, while significant and positive effect on Return on Asset (ROA) and Return on Equity (ROE). Board independence is also significant to firms’ performance. This result implies that political connection is a favour for a better firm’s performance and not to firm’s value. The findings have an important implication to investors as it suggests that firms with political connection on board perform better.
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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 | 0.001 |
| 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) | 0.000 | 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".