The mediating effect of sustainability disclosure on the impact of proactive tax planning on firm value: Empirical evidence from ESG100 index
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The research aims to examine the mediating effect of sustainability disclosure on the relationship between proactive tax planning and firm value among companies listed in the ESG100 Index. The sample comprises 114 firm-year observations from ESG100 companies during the period 2020 to 2022. This study utilizes secondary data. Moreover, a statistical regression method was applied using balanced panel data analysis, integrating both cross-sectional and time-series data to test the research hypotheses. The findings indicate that proactive tax planning has no significant effect on sustainability disclosure. However, sustainability disclosure has a positive and significant effect on firm value, whereas proactive tax planning has a negative and significant effect on firm value. This suggests that proactive tax planning may reduce firm value due to associated costs, such as tax advisory fees. Executives should therefore carefully evaluate the costs and benefits of proactive tax planning and choose strategies that optimize long-term benefits for the company. Understanding the tax costs involved in business operations should be a priority for management. The study's findings also suggest that regulatory authorities should develop tax policies that are contextually appropriate for Thailand and align with current economic conditions. In addition, the study reveals that investors place a high value on sustainability disclosure.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it