Financial analysts' concerns, media exposure and corporate environmental communication: accounting for simultaneous relationships in an international perspective
Bibliographic record
Abstract
The purpose of this study is to provide an integrated analysis of corporate environmental communication strategies using stakeholder theory. More precisely, we argue that there is a symbiotic relationship between managerial decisions with respect to environmental disclosure and stakeholders. On the one hand, stakeholders’ claims determine managerial decisions with respect to corporate environmental disclosure. On the other hand, managerial decisions may affect key stakeholders’ actions and decisions, more specifically financial analysts’ forecasts. We investigate three research questions: (1) What are the determinants for voluntary environmental disclosure? (2) Does voluntary environmental disclosure allow analysts to make better forecasts? (3) Is there a difference in the determination and implications from environmental disclosure between continental European and North American firms? The sample comprises continental European firms (Belgium, France, Germany, and the Netherlands) and North American firms (Canada and the United States). Our measure of environmental disclosure reflects web disclosure, which encompasses print-based documents (e.g., environmental reporting in pdf) as well as web only disclosures (e.g., html documents or videos). Through distinct determinant regressions using simultaneous equations, we find a significant relationship between business stakeholders’ concerns and environmental disclosure for North American firms, while conversely, we find a weak statistical effect for continental European firms. Environmental news exposure is a significant determinant of environmental disclosure in both continents. Findings also suggest that financial markets’ concerns are relevant as a determinant of environmental disclosure. Concerning the relevance of environmental disclosure for financial analysts’ earnings forecasts, results show that print environmental disclosure is associated with a decrease in analysts' forecast dispersion both in continental Europe and in North America. Furthermore, environmental disclosure is less important a factor in explaining forecast dispersion for those firms that are followed by many analysts. However, in North America, it appears that analysts use environmental disclosure differently depending on the diffusion media (i.e., web or paper). It seems that in North America, the more discretionary is the information disclosed, the less it is relevant for market participants. Moreover, in continental Europe, environmental disclosure increases dispersion of analysts' forecasts for firms operating in more environmentally sensitive industries. Findings also suggest that for assessing information relevance for market participants, it is important to control for the endogenous effect of a firm’s decision to disclose information as well as its exposition to media.
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".