The Impact of Anti-Thin Capitalization Rules on Capital Structure in Taiwan
Bibliographic record
Abstract
This paper investigates the impact of the enactment of the anti-thin capitalization rules on capital structure after the enactment of the anti-thin capitalization rules in Taiwan. According to the theoretical derivation, companies with lower shareholder imputed tax credits ratio tend to have greater debt-to-equity ratio, while companies with higher surtax on undistributed earnings ratio tend to have higher debt-to-equity ratio. This finding is consistent with the hypotheses of this study. However, the relationships between interest-bearing liability rate, marginal income tax rate and debt-to-equity ratios are uncertain. Using 2006–2012 sample data for the empirical study, this paper finds that enterprise’s total debt-to-equity ratios significantly decreases after the enactment of the anti-thin capitalization rules, and provisions preventing capital weakening have policy effectiveness. The shareholder imputed tax credits ratio and total debt-to-equity ratio are negatively correlated, while interest-bearing liability rate, marginal income tax rate, and surtax on undistributed earnings ratio, are positively correlated with total debt-to-equity ratio. This finding supports the hypotheses of this study. However, marginal income tax rate is lack of significance. Regardless of the enactment of the anti-thin capitalization rules, pledge ratios, investment growth opportunities, firm size and ownership of director and supervisor ratios are positively correlated with total debt-to-equity ratio; non-debt tax shields, R&D ratio and profitability are negatively correlated with total debt-to-equity ratio, which are also consistent with the expected results of this paper.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".