Beyond the tipping point: The nonlinear impact of material sustainability on investment efficiency
Bibliographic record
Abstract
ABSTRACT Drawing on the shareholder viewpoint adopted by the Sustainability Accounting Standards Board (SASB) to determine materiality, we propose and test a hypothesis for the optimal level of allocating financial resources to projects prioritizing environmental, social, and governance factors, namely sustainability investment. Based on the premise that shareholders consider specific thresholds for sustainability investments, we postulate that shareholders respond positively if the firm’s sustainability investments are below the optimal level, whereas they react negatively if the investments are above the optimal level. Using a quadratic and piecewise linear regression, we demonstrate a significant inverted U-shaped linkage between materiality ratings of sustainability and capital investment efficiency for a sample of all US companies listed on ASSET4 spanning from 2008 to 2021. Upon further examination of the sensitivity of the turning point to the firm- and market-specific characteristics, we find that leveraged firms and those facing exogenous shocks have a higher optimal level. Our results remain robust across a range of sensitivity tests and offer significant policy implications for regulators and standard setters. These findings can inform the frameworks and guidelines developed by organizations such as the U.S. Securities and Exchange Commission (SEC), the SASB, and the International Sustainability Standards Board (ISSB).
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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 | 0.000 |
| 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".