Dividend Policy in Indonesia Agriculture Firms: Modmed Profitability and Liquidity
Bibliographic record
Abstract
Against the backdrop of the existence of a dividend policy that can provide investors with a variety of signals, the objective of this study is to determine the dividend policy in the Indonesian agricultural sector, given the sector's pronounced volatility between 2014 and 2021.This is what causes the agricultural sector to experience the greatest volatility compared to other sectors.This research develops a dividend policy model with moderating variables, namely liquidity, and mediating variables, namely profitability, in response to a number of gaps in the existing literature.The method employed is quantitative explanation with purposive sampling technique.This study employs path analysis by means of the SEM method and STATA version 14.The results indicate that leverage and firm size have a negative impact on dividends, while profitability has no bearing on dividend policy.Other results indicate that leverage has no effect on profitability, while firm size has a negative effect.The failure of the moderation and mediation tests is caused by the absence of profitability's effect on dividends.
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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 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".