Agency Costs of Permanently Reinvested Earnings
Bibliographic record
Abstract
Current U.S. tax laws create an incentive for some U.S. firms to avoid the repatriation of foreign earnings as the U.S. government charges additional corporate taxes upon repatriation of foreign earnings. Under ASC 740, the financial accounting treatment for taxes on foreign earnings exacerbates this effect and increases the incentive to avoid repatriation by allowing firms to designate foreign earnings as permanently reinvested earnings (PRE) and delay recognition of the deferred tax liability associated with the U.S. repatriation tax resulting in higher after-tax income. Prior research suggests the combined effect of these incentives leads some U.S. multinational corporations to delay the repatriation of foreign earnings and, as a result, hold a significant amount of cash overseas. In this study, we examine the potential agency costs for firms with PRE through an examination of their cash acquisitions. Consistent with expectations, we observe firms with both high levels of cash overseas and high levels of foreign earnings designated as PRE are more likely to make value-destroying acquisitions of foreign target firms. The AJCA of 2004 appears to have reduced this effect by allowing firms to repatriate foreign earnings held as cash abroad at a much lower tax cost.
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".