Financial materiality in the informativeness of sustainability reporting
Bibliographic record
Abstract
Abstract This study examines whether financial materiality in environmental, social, and governance (ESG) disclosure benefits the stock market by increasing the amount of accessible and relevant firm‐specific information. Based on the value relevance of information and the principle of financial materiality, we demonstrate that disclosing material ESG information increases stock price informativeness. We conduct an automated content analysis of 150,000 electronic documents filed by firms listed on the S&P/TSX Composite Index from 1999 to the end of 2014. Our findings show that ESG disclosure is indeed value relevant for investors and that financial materiality in ESG disclosure leads to more informative stock prices. In addition, the effect of ESG disclosure on stock price informativeness differs across the ESG components, being more sensitive to the social component. This study contributes to the literature on sustainability reporting, and in particular to the ongoing discussion about whether the financial materiality of ESG issues matters. This study also deepens the understanding of agency theory predictions about the economic effects of ESG disclosure.
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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 | 0.015 | 0.137 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".