Microeconomics of Environmental Performance: Evidence from Firms’ Emissions Reduction Initiatives
Bibliographic record
Abstract
Using project level data that firms disclose in the Carbon Disclosure Project, we provide evidence on what firms actually do to reduce greenhouse gas emissions. The majority of initiatives that firms take on require small investments (median $127,000) and have payback periods of at most three years. These short-term initiatives mostly target energy efficiency in buildings or production and generate more monetary and CO2e savings. Firms experiencing short-term performance pressure, smaller firms, and those granting themselves less time to achieve their own emissions targets are more likely to implement such initiatives. A greater share of short-term initiatives predicts better environment-related ESG ratings but no superior firm performance, consistent with the small size of investment. Overall, the evidence suggests that firms do not act according to the common view that investments in the environment are, or should be, long-term oriented. Firms tend to mitigate rather than adapt to climate change.
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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) | 0.001 | 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 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".