Foreign Direct Investment and the Operations of Multinational Firms: Concepts, History, and Data
Bibliographic record
Abstract
The concept and measurement of foreign direct investment have changed over time, and what is measured by balance of payments flows and stocks is quite different from what is implied by theories of direct investment. The industrial distribution of stocks of FDI, the most widely available measure, is only poorly related to the distribution of FDI production, and changes in stocks are poorly related to changes in production. FDI flows have grown in importance relative to other forms of international capital flows, and the resulting production has increased as a share of world output, but it was still only about 8 per cent at the end of the 20th Century. The United States began its role as a foreign direct investor in the late 19th Century, while it was still a net importer of capital. It became the dominant supplier of direct investment to the rest of the world, accounting for about half of the world's stock in 1960. Since then, other countries have become major direct investors. The U.S. share is now less than a quarter of the world total and the United States has become a major recipient of FDI from other countries.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.011 | 0.033 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".