The impact of sustainable finance on corporate greenhouse gas emissions: Evidence from North American and European firms
Bibliographic record
Abstract
This thesis examines the relationship between sustainable finance (i.e. sustainable investors’ ownership and the amount of green bonds outstanding relative to a firm’s total assets) and the North American and European firms’ different scopes of greenhouse gas (GHG) emissions, both unscaled GHG emissions and GHG emission intensities. The results suggest that sustainable finance is generally related to lower GHG emissions. The findings are more consistent for direct than indirect or total emissions. However, when comparing the relationship between sustainable finance and GHG emissions of firms from the USA and firms from Europe and Canada, the results suggest that the sustainable finance relation to lower corporate GHG emissions is mainly present in European and Canadian firms, indicating that sustainable finance itself is not the main driving factor for lower GHG emissions. Furthermore, when only non-financial firms are included in the sample, the relationship between sustainable finance and lower GHG emissions weakens but is still present in some scopes of emissions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".