The Deferred Tax Asset Valuation Allowance and Firm Creditworthiness
Bibliographic record
Abstract
ABSTRACT In this study, I provide evidence that the valuation allowance for deferred tax assets helps predict the future creditworthiness of a firm. Under the provisions of SFAS No. 109, a firm records a deferred tax asset provided it expects to generate sufficient taxable income to realize the asset in the form of tax savings in the future. If a firm does not expect to generate sufficient taxable income to realize the asset, then a valuation allowance is created to reduce the balance. As a result, the valuation allowance indicates management's expectation of future taxable income, which could be informative in predicting the ability of the firm to make future interest and principal payments on debt. Alternatively, the valuation allowance may not be informative regarding creditworthiness if it is a result of overly conservative accounting practices or if it is used as an earnings management tool. I document a negative association between material increases in the valuation allowance and contemporaneous and future changes in credit ratings, evidence that is consistent with the valuation allowance providing a summary measure of a decline in firms' creditworthiness. JEL Classifications: G29; H25; M41. Data Availability: Data are available from sources identified in the paper.
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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 | 0.002 | 0.136 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 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".