Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Most international commerce is carried out by multinational firms, which use their foreign affiliates for the majority of their foreign sales. In this paper, I examine the determinants of multinational firms’ location and production decisions and the welfare implications of multinational production. The few existing quantitative general equilibrium models that incorporate multinational firms achieve tractability by assuming away export platforms – i.e. they do not allow foreign affiliates of multinationals to export – or by ignoring fixed costs associated with foreign investment. I develop a quantifiable multi-country general equilibrium model, which tractably handles multinational firms that engage in export platform sales and that face fixed costs of foreign investment. I first estimate the model using German firm-level data to uncover the size and nature of costs of multinational enterprise and show that fixed costs of foreign investment are large. Second, I calibrate the model to data on trade and multinational production for twelve European and North American countries. Counterfactual results reveal that multinationals play an important role in transmitting technological improvements to foreign countries as they can jump the barriers to international trade; I find that a twenty percent increase in the productivity of US firms leads to welfare gains in foreign countries an order of magnitude larger than in a world in which multinational production is disallowed. I demonstrate the usefulness of the model for current policy analysis by studying the pending Canada-EU trade and investment agreement; I find that a twenty percent drop in the barriers to foreign production between the signatories would divert about seven percent of the production of EU multinationals from the US to Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.016 |
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 it