Sea‐level rise and firms' financial structure decisions
Bibliographic record
Abstract
Abstract We study how environmental risks induced by the potential inundation associated with sea‐level rise affects firms' financial structure decisions. We find that firm leverage decreases with inundation risks associated with sea‐level rise. To establish causality, we consider firms' relocation of their headquarters, a propensity score matching estimator, and a difference‐in‐differences estimator around the release of the documentary “An Inconvenient Truth” and find that our results are robust. The negative relation between inundation risks due to sea‐level rise and financial leverage is more pronounced for firms with more geographically concentrated operations, firms with more close rivals, and firms that are non‐investment grade. SLR risk‐affected firms shift more towards equity and away from debt in their capital raising efforts and have a relatively higher weight of their leverage in short‐term debt. Our findings highlight firms' proactive adjustment and adaptation to long‐term environmental risks.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".