The predictive ability of tax contingencies for future income tax cash outflows
Bibliographic record
Abstract
Abstract Prior research shows that contingent liabilities do not accurately predict future cash payments due to the managerial discretion afforded by accounting standards. We examine the extent to which current accounting guidance for a material contingent liability—the reserve for unrecognized tax benefits (UTBs) under Financial Interpretation No. 48 (FIN 48)—generates accruals that are predictive of future income tax cash outflows. We document that UTBs fully unwind as cash tax payments over the subsequent 5 years, suggesting that managers, on average, accurately incorporate their expectations of future tax liabilities. This result persists for firms that are (1) most affected by the implementation of FIN 48, (2) unable to impound detection risk into their reserves, (3) engaged in relatively more ex ante tax avoidance, (4) suspected to have engaged in earnings management through the tax accounts, and (5) subject to plausibly exogenous shocks to tax reporting. Overall, our results suggest that current accounting guidance under FIN 48 for contingent tax liabilities enables managers to accurately report, and financial statement users to reliably predict, future cash obligations.
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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 | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".