Does the presence of a sustainability committee strengthen the impact of ESG disclosure on tax aggressiveness? Insights from North America
Bibliographic record
Abstract
Abstract We investigate the influence of ESG disclosure on tax aggressiveness within the North American Travel and Leisure (T&L) sectors, specifically examining the role of sustainability committees in this relationship. Our analysis utilizes longitudinal panel data from the USA B3000 and Canadian S&P/TSX indices over the period from 2010 to 2020. Employing fixed-effects panel quantile regression with two distinct measures of tax aggressiveness, our findings indicate that firms with a focus on ESG tend to display higher levels of tax aggressiveness. This suggests that some companies might use strong ESG performance as a facade to obscure aggressive tax strategies. Moreover, our research introduces new evidence that the existence of sustainability committees can both hinder corporate tax aggressiveness and foster an ethical corporate culture, which aligns higher ESG engagement with lower tax aggressiveness. Our study underscores the importance of fostering tax compliance in T&L companies, emphasizing that individuals and corporations, which often seek direct state benefits, regard robust public services as essential for encouraging adherence to tax regulations. Furthermore, sustainability committees play a crucial role in enabling firms to address broader social issues, including tackling tax aggressiveness, thus shaping their sustainability agendas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".