The Magnification Effects of Intra-firm Trade of Multinational Corporations
Bibliographic record
Abstract
The 2008 financial crisis and the credit crunch severely restrict the ability of multinational companies to invest abroad and finance cross-boarder mergers and acquisitions; yet do not impair the intra-firm trade among parent firms, subsidiaries and branches. Intra-firm trade is a complement of foreign direct investment whether it is a market-access based FDI or for considerations of factor price differential motivations. Compared with arm’s length transactions, intra-firm trade of MNCs is highly contributable to unit the global-based affiliates under one set of rationales of operation mechanism, thus reel off the substantial benefits produced within the boundaries of the host nations. The essay starts with characteristics and incentives of intra-firm trade of MNCs, then analyzes in great details the related effects from the standpoints of international trade structure, international relations and the economy perspectives of the host countries. The author concludes that the sales of affiliates of multinational firms have long dwarfed the value of FDI injection to the host countries and the transfer price system is often illegally used for tax evasion purposes, thus shortchanging the earnings of the host nations. The author proposes corresponding countermeasures by the end.
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.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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".