Disclosure and Recognition Requirements: Corporate Investment Decisions with Externalities*
Bibliographic record
Abstract
Abstract This paper examines the effects of disclosure and recognition requirements on investment decisions when shareholders have limited liability. Firms' investment projects have either high initial pollution prevention costs or high subsequent clean‐up costs, and their liability for clean‐up costs may be either individual or joint and several. Even with individual liability for clean‐up costs, shareholders' limited liability creates an incentive to select the latter project type and to impose costs on the rest of the economy. This tendency is exacerbated when clean‐up liability is joint and several. We show that a disclosure requirement cannot have an unambiguous effect on the selection of the “cleaner” project. However, an accrual requirement, together with an accounting‐based dividend restriction, is shown to promote choice of the project that imposes lower expected costs on the rest of the economy. Moreover, we find that it is possible for a recognition requirement to have a greater impact in a joint‐and‐several liability regime than in an individual liability regime.
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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 | 0.004 | 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 | 0.001 | 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) | 0.000 | 0.001 |
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".