How does CEO pay slice influence corporate social responsibility? U.S.–Canadian versus Spanish–French listed firms
Bibliographic record
Abstract
Abstract Considering specific contextual differences (in laws, governance attributes, and CEO pay policies) found between the Anglo‐American and the European corporate governance models and controlling for institutional attributes, ownership structures, and firm's features characterizing the two settings, we aim to explore if there is a link between CEO pay slice (CPS) and corporate social responsibility (CSR). We follow Bebchuk et al. ( ) to measure CPS. We consider sustainability indicators as proxy to capture CSR. Sustainability indicators are gathered from Global Reporting Initiative of sustainability standards (GRI's) report. Data cover the period 2010–2017 and consist of 1,440 U.S.–Canadian and Spanish–French firm‐year observations. American and Canadian (Spanish and French) firms are considered as to refer to the Anglo‐American (European) corporate governance model. Durbin–Wu–Hausman test is ruled to address endogeneity problem of dual variables and supports consistent null hypotheses of fixed effects model. Under the agency theory's “bright side” paradigm, univariate and multivariate cross‐country analysis supports that CPS is positively associated with firm's initiatives to engage in CSR and that sustainability is more pronounced under stronger investor protection, strict law enforcement, and higher corporate governance quality. Robustness checks reveal that (a) the deferred CPS–CSR causal effect seems higher for option‐based compensation than that for stock‐based compensation and (b) within the options (stocks) rewards, unvested options (restricted stocks) are the most effective to enhance firm's CSR practices.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".