Environmental, social, and governance disclosure impact on cash holdings in OECD countries
Bibliographic record
Abstract
In this research, we investigate how cash holdings are affected by the environmental, social, and governance (ESG) disclosure practices of corporations. This research provides valuable insights into the ongoing discussion all across the world on ESG disclosure, and mainly 5 countries from the Organisation for Economic Co-operation and Development (OECD), which are the United States of America, Canada, the United Kingdom, Japan, and Australia, over the period 2012–2021. We used Refinitiv Eikon database to measure the variables. The results show there is a significantly negative relation between ESG disclosure and cash holdings in the introduction, growth, and shake-out/decline stages. Lower cash holdings are associated with higher firm performance and a positive value of cash. In spite of using different econometric parameters, other measurements, extra control variables, propensity score matching, and an instrumental variable approach, our results remained unchanged (Arayssi et al., 2020). This paper has recommendations for policymakers, investors, and business organizations. Importantly, our study reveals how higher levels of ESG disclosure lead to better cash-holding practices (Buallay, 2022).
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".