The impact of investments in corporate social performance measured by the value of cash holdings
Bibliographic record
Abstract
Corporate investment in environmental and social initiatives has increased significantly in recent years as a response to increasingly complex and demanding socio-economic environments. Nonetheless, a question that remains unanswered is whether investments in social and environmental initiatives create firm value and, if yes, in which way value is created. The objective of this study is to fill this gap by investigating the relationship between investments in Environmental, Social and Governance (ESG) practices and firm value by comparing the market value of an extra dollar of cash for firms with high and low ESG ratings. Our results show that an extra dollar of cash is valued at a premium of $0.13 (or 13%) in high ESG firms as compared to low ESG firms. We find evidence to support the stakeholders theory and the resource based view by showing that managers who invest in ESG practices that have received the support of key stakeholders are acquiring resources that are unique and inimitable. Therefore, they create a sustainable competitive advantage for their companies, which positively affects value and reduces agency costs. We also show evidence that financial slack has value in the presence of future investment opportunities and when the cost and availability of capital is uncertain.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 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".