Corporate Taxes and Financing Methods for Taxable Acquisitions*
Bibliographic record
Abstract
Abstract We examine the influence of corporate taxes on U.S. firms' financing methods for taxable acquisitions of 100 percent of a target corporation's stock. We conduct tests of acquirer firms' use of debt or internal funds as the funding source for these acquisitions over the period 1987‐97. Our results provide the first empirical evidence that U.S. firms' use of debt to fund acquisitions significantly declines as foreign tax credit limitations reduce the marginal tax benefits received from borrowing. This finding is consistent with earlier speculation that U.S. foreign tax credit provisions could materially affect the capital costs of U.S. companies in debt‐financed acquisitions. We also find that these firms are generally high‐tax‐rate corporations whose financing choices are not significantly influenced by whether they acquire target‐firm tax loss carryovers. Our findings contribute to the accounting literature on the influence of taxes on the structure and financing of corporate acquisitions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 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".