Evidence of Manager Intervention to Avoid Working Capital Deficits
Bibliographic record
Abstract
Abstract We study managers’ interventions in financial reporting by examining working capital deficits, measured as current ratios less than 1.0. Current ratios represent important balance sheet liquidity indicators to lenders and creditors, and have an identifiable and naturally occurring reference point at 1.0, analogous to the profit/loss income statement reference point. We find that distributions of reported current ratios of both U.S. and non‐U.S. firms exhibit a discontinuity at 1.0. For U.S. firms, we find that the discontinuity increases with exogenous increases in the cost of credit in the economy, and that determinants of the likelihood to achieve a given current ratio are diagnostic precisely at the 1.0 discontinuity location but not at other nearby locations in the current ratio distribution. U.S. firms that avoid working capital deficits report lower proportions of inventory and higher proportions of accounts receivable in current assets and, when credit is tight, higher proportions of cash, consistent with managers increasing sales volume so as to capitalize profit margins and thereby increase current assets. For non‐U.S. firms, the discontinuity is more pronounced for observations from common law countries, a proxy for jurisdictions where financial reports are more intended to provide decision‐useful information. The evidence suggests that managers intervene to achieve a balance sheet reporting objective that stems from stakeholder use of reference points.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".