Bibliographic record
Abstract
In this paper the structure of intra‐firm trade within the context of transfer price manipulation by a multinational firm is endogenized. ‘High’ and ‘low’ values of host‐country tax rates give rise to intra‐firm trade in final goods and intermediate inputs, and ‘intermediate’ values of the tax rate are associated with intra‐firm trade in either the intermediate inputs or the final goods only. Higher tariffs and stricter local content restrictions bias intra‐firm trade towards intermediate‐good trade and final‐good trade, respectively. In the presence of endogenous transfer prices host‐country sales may increase if the multinational faces stricter trade restrictions and higher host‐country tax rates. JEL Classification: F23, F12 Prix de cession interne et structure du commerce itnra‐firme. Ce mémoire endogénéise la structure du commerce intra‐firme dans le contexte d'un modèle qui permet la manipulation du prix de cession interne par une firme plurinationale. Des taux de taxation hauts et bas par le pays hôte entraînent un commerce international intra‐firme tant dans les biens finaux que dans les intrants intermédiaires; des taux moyens de taxation sont associés à un commere intra‐firme soit dans les intrants intermédiaires, soit dans les biens finaux mais pas dans les deux. Des droits de douane élevés et des restrictions sur le contenu intérieur plus importantes créent des distorsions en faveur du commerce intra‐firme dans les biens intermédiaires et dans les biens finaux respectivement. Quand il existe des prix de cession interne endogènes, les ventes de la firme nationale peuvent s'accroître si la firme plurinationale fait face à des restrictions au commerce plus importantes et à des taux de taxation plus élevés de la part du pays hôte.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".