The Commitment Effect versus Information Effect of Disclosure—Evidence from Smaller Reporting Companies
Bibliographic record
Abstract
ABSTRACT We examine the commitment effect provided by mandatory disclosure and the information effect of voluntary disclosure on market illiquidity by exploring a regulatory change that allows smaller reporting companies to reduce the disclosure of certain information in their SEC filings. This regime change allows us to separate the commitment effect provided by mandatory disclosure from the information effect of voluntary disclosure. We find that firms that are eligible to reduce their disclosure, but voluntarily maintain their disclosure level, experience an increase in market illiquidity. We also find that the increase in illiquidity is more pronounced for firms with higher agency costs. These findings suggest that mandatory disclosure serves as a credible commitment mechanism and that losing such commitment by disclosure deregulation is costly in the absence of a loss of information. Our study suggests that while voluntary disclosure is effective in reducing information asymmetry, it cannot replace mandatory disclosure in addressing information problems. Data Availability: Data are available from sources identified in the text.
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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 | 0.006 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| 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".