2. The Boundaries of the Multinational Firm: An Empirical Analysis
Bibliographic record
Abstract
Using data on U.S. intra-firm and arm’s-length imports for 5,423 products and 210 countries, we examine the determinants of the share of U.S. imports that are intra-firm. Three determinants of this share have been proposed: (1) Antras (2003) focuses on the share of inputs provided by the headquarter firm. We provide added confirmation and further strengthen the empirical findings in Antras (2003) and Yeaple (2006). (2) In a model featuring heterogeneous productivities, Antras and Helpman (2004) focus on the interaction between the firm’s productivity level and the headquarter’s input share. We find very strong support for this determinant. (3) Antras and Helpman (2006) add to this the possibility of partially incomplete contracting. We find that consistent with the novel prediction of their model, improved contracting of the supplier’s inputs can increase the share of U.S. imports that are intra-firm. In short, the data bear out the primary predictions of this class of models about the share of U.S. imports that is intra-firm trade.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".