Foreign Direct Investment from Developing Countries: A Case Study of China's Outward Investment
Bibliographic record
Abstract
This thesis presents an interpretation of foreign direct investment (FDI) by Chinese firms. The research is motivated by the phenomenon that, compared with foreign investment in China, direct investment from China has so far attracted relatively little attention from researchers. The development of China's outward direct investment exhibits distinctive features. It was expanded rapidly in a relatively short time and was directed heavily to a few developed countries, namely, the United States, Canada and Australia. In addition, it is not evident that Chinese investors possess clear international competitive advantages. Existing mainstream theories of FDI from developing countries cannot provide a ready explanation of the underlying rationale for the pattern of China's FDI. Given the difficulties in providing a convincing explanation of the pattern of China's outward FDI by using mainstream theories, this thesis develops a network model of FDI by formalising network ideas from business analysis for application to economic analysis, and interprets China's outward FDI in terms of the network model. This thesis holds that Chinese firms were engaged in FDI for various network benefits. Accordingly, the geographic distribution of China's outward FDI reflected the distribution of network benefits required by Chinese firms and the relevant cost saving effects for obtaining such benefits. As the functioning of networks relies on elements of market economies, the development of China's outward FDI was affected by the progress of marketisation in China. China's outward FDI has a very short history and comprehensive data on industrial composition and overseas subsidiaries' operation are not yet available. This has ruled out the possibility of more specific testing with formal econometric analysis. Rather, the method of approach is essentially descriptive and the interpretation is mainly based on qualitative analysis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".