Investor reactions to climate change disclosures: Joint effects of disclosure focus and controllability
Bibliographic record
Abstract
Abstract When evaluating the potential financial effects of climate change, investors demand disclosures of the climate‐related risks and opportunities that companies need to manage. We examine how and why management control over climate change performance affects investors' evaluations of such disclosures. In a series of experiments, we find that investors believe that managerial optimism is beneficial and, thus, are more willing to invest when climate‐related disclosures focus on opportunities rather than risks. This effect, however, occurs only when management has high control over the company's future climate change performance. When that control is low, investors believe that managerial realism is beneficial and, thus, are more willing to invest when these disclosures focus on risks rather than opportunities. Our study has implications for companies and standard setters considering the consequences of focusing on either risks or opportunities in climate change reporting and the conditions under which one focus or the other may be beneficial.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".