Does improved environmental and disclosure performance payoff? Not for CA 100+ companies
Bibliographic record
Abstract
Purpose This study examines the financial performance and cost of equity estimates of firms included in Climate Action 100+ (CA 100+), a group comprising the largest global industrial emitters. The research explores how decarbonization plans and climate-related disclosures influence the cost of equity, offering insights into the complex relationship between climate risk and financial outcomes. Design/methodology/approach We analyze the stock performance of CA 100+ firms from 2016 to 2022, comparing their returns to well-known global indices. Cost of equity estimates are calculated using the Capital Asset Pricing Model (CAPM) and Dividend Discount Model (DDM). The study adjusts for country and industry influences and evaluates the impact of CA 100+ benchmark scores and Task Force on Climate-related Financial Disclosures (TCFD) quality ratings on the cost of equity. Findings CA 100+ firms outperformed major global indices in both actual and risk-adjusted returns during the study period. These firms exhibited higher average returns with lower standard deviations, suggesting first-order stochastic dominance. The information ratio (IR) for the CA 100+ portfolio relative to benchmark indices was consistently large and positive, confirming superior risk-adjusted performance. After controlling for country and industry effects, cost of equity estimates for CA 100+ firms were virtually identical to those of a corresponding benchmark. Surprisingly, firms with lower CA 100+ scores and lower-quality TCFD disclosures had lower costs of equity than firms with superior performance, indicating that markets do not penalize poor environmental performance or disclosure quality. Originality/value This study challenges conventional assumptions that superior environmental performance correlates with lower cost of equity. The unexpected finding that poorly rated firms exhibit lower financing costs underscores the complexity of the relationship between environmental disclosure, decarbonization strategies and financial performance. The results provide essential insights for institutional investors, policymakers and corporate executives navigating the transition to a low-carbon economy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".