Inbound and Outbound U.S. Direct Investment With Leading Partner Countries Web version:
Bibliographic record
Abstract
This article surveys trends in U.S. inbound and outbound foreign direct investment (FDI) during 2000-2005. The article examines the major country and regional destinations for U.S. direct investment abroad (USDIA), and foreign direct investment in the United States (FDIUS). After a brief survey of total inbound and outbound FDI, trends are examined by region and by the most significant developed and developing country investment partner countries. Throughout the paper, the analysis pays particular attention to the multinational corporations that are the source of most FDI, along with particularly important mergers, acquisitions, and greenfield investments. By far the largest U.S. FDI partner is Europe, particularly the United Kingdom, Germany, and the Netherlands. Canada ranks second in terms of its overall FDI relationship with the United States. One-third of cumulative USDIA, equal to $623 billion in 2005, is invested in holding companies in a small number of countries, primarily in Europe and the Caribbean, making it difficult to track the final country and industry destinations of this capital, and limiting an understanding of the effects of U.S. FDI. Mexico is by far the most important FDI partner country among developing countries, for both USDIA and FDIUS. 2 USDIA is the value of U.S. investors ’ equity in, and net outstanding loans to, their foreign affiliates. Direct investment is considered to be “investment in which a resident of one country obtains a lasting interest in, and a degree of influence over the management of, a business enterprise in another country. ” The U.S. statistical definition, and the global standard adopted by the IMF, define such an interest as the ownership or control by one foreign resident of 10 percent or more of the equity shares in a foreign company. Ownership interest of less than 10 percent is defined as portfolio investment, and not included in the statistics
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.074 | 0.030 |
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".