Unprofitable Affiliates and Income Shifting Behavior
Bibliographic record
Abstract
Income shifting from high-tax to low-tax jurisdictions is commonly considered a primary method of reducing worldwide tax burdens of multinational firms. Extant research generally makes the high-tax and low-tax distinctions using statutory or aggregated effective tax rates. However, current losses also affect the marginal tax rates of affiliates. In the absence of carryback or carryforward provisions, an unprofitable affiliate has a marginal tax rate of zero. Thus, an unprofitable affiliate can alter the income shifting incentives and strategy of a multinational firm. We build upon prior estimation approaches to allow for the inclusion of unprofitable affiliates and test whether the reported pre-tax income of unprofitable affiliates deviates from the negative association with statutory tax rates observed in samples of profitable affiliates. We also estimate a marginal tax rate that takes into account factors such as loss carryback and carryforward. Results suggest that multinational firms with an unprofitable affiliate adjust their transfer pricing strategies to take advantage of losses and that the marginal tax rate is a determinant of observed pre-tax income. Our point estimates imply that an average-sized affiliate facing the average statutory tax rate alters its income shifting behavior by approximately $7.8M upon a change from profitability to loss.
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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 | 0.001 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".