Tax Avoidance with Maqasid Syariah: Empirical Insights on Derivatives, Debt Shifting, Transfer Pricing, and Financial Distress
Bibliographic record
Abstract
This study analyzes and investigates how financial factors, namely, derivatives, debt shifting, and transfer pricing, influence tax avoidance, with financial distress as an interaction variable, within the framework of stakeholder theory and positive accounting theory. Adding more uniqueness, this study injected the Maqasid Syariah elements into the framework. Conventional banks and non-bank institutions listed on the Indonesia Stock Exchange (IDX) between 2017 and 2022 were selected, comprising 414 final company-year observations. The study utilized E-Views software for data processing. The findings indicate that debt shifting negatively impacts tax avoidance, while derivatives have no significant influence. Transfer pricing positively impacts tax avoidance. Financial distress does not moderate the relationship between these financial practices and tax avoidance. From an Islamic perspective, practices such as transfer pricing and debt shifting, when used to avoid tax, contradict the principles of Maqasid Syariah, which emphasize fairness, wealth distribution, and societal welfare.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".