Cost and performance of carbon risk in socially responsible mutual funds
Bibliographic record
Abstract
Investors and other financial actors are attracted by the role of socially responsible (SR) mutual funds in the transition to a low-carbon economy. In response to the demand for more information, Morningstar reported the level of carbon risk of funds by using the following indicators: Carbon Risk, Carbon Management, Carbon Operations risk and Carbon Exposure. Dealing with a sample of 3370 equity SR mutual funds worldwide from 2017 to 2021, this study analyzes the relationships between these indicators and the expense ratio and performance of the funds. In general, the results point to funds with lower carbon scores that have lower fees and perform better than those with higher scores. Considering the effects of the COVID-19 crisis, this evidence holds true for most of the sample period analyzed. With a spatial analysis, although the evidence generally holds, regional differences are found. Thus, funds that invest in the USA and Canada are on average cheaper and show lower carbon scores, while funds that are oriented to other areas, such as emerging markets, are more expensive and show higher scores. In summary, there is good news for the utility function of the investor and the planet: Green investing is cheaper and better.
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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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| 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".