The effect of corporate social responsibility transparency on corporate payout policies
Bibliographic record
Abstract
Purpose This study explores whether a firm's environmental and social (E&S) transparency affects corporate payout policies having two forms of dividend payout and stock repurchase payout. Design/methodology/approach Focusing on a large sample of S&P 500 firms, and utilizing Tobit estimators, the author examines whether a firm's environmental transparency and social transparency affect the levels of each dividend payout and stock repurchase payout. Transparency reflects comprehensive scores compiled by Bloomberg, capturing both the quantity (in terms of the number of data points) and the quality (with respect to objective and industry-relevant data points) of verified E&S information attributed to a firm's E&S practices. Findings The findings demonstrate that transparency, both environmental and social, relates to higher corporate payouts (i.e. higher dividend payout and higher stock repurchase payout). These positive relationships are magnified for firms suffering from high information asymmetry, low financial reporting quality and for those with weak governance. Moreover, the author finds that dividend payout is more stable in high E&S transparent firms than in low E&S transparent firms. The study findings continue to hold after a battery of robustness and sensitivity checks such as alternative measures, specifications, estimators, use of the instrumental variable regression approach and mitigation of omitted variable bias Research limitations/implications The study findings suggest that investors' interests (demanding for high corporate payouts) and other stakeholders' interests (demanding for high E&S transparency) are not necessarily in conflict, and investors' demands can be met while maintaining commitment to high E&S transparency. In addition, the study results imply that higher E&S transparency complements higher corporate payouts and signals to the market both a firm's commitment to E&S transparency and its ability to have high corporate payouts. In this line, the study findings clarify the high value of E&S transparency screening in investors' decision-making process as such transparency leads to higher corporate payouts for investors (i.e. facilitating wealth transfer to shareholders). Finally, the study findings are relevant to standard setters and regulators who emphasize the importance of E&S transparency. Originality/value By integrating two distinct streams of literature on corporate finance and corporate social responsibility (CSR), the author introduces E&S transparency as a novel nonfinancial driver of corporate payout policies. Finally, the study findings are in line with the notion that firm transparency (reflected in E&S transparency) can be a crucial element in justifying a firm's corporate payout policies and, in an overall view, firm policies.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".