Intra-SADC Foreign Direct Investment: A Gravity Approach to South Africa Outward Investment
Bibliographic record
Abstract
This paper looks at intra-SADC FDI, focusing at South Africa outward FDI into SADC countries. LSDV and GMM estimation techniques are applied in a gravity model for the period 1999 to 2010. The study finds strong evidence that intra-trade and intra-FDI are negatively related, suggestive of a substitutive relationship between intra-SADC trade and intra-SADC FDI. The study also reveals that capital account openness, bilateral investment treaties, and labour availability are key in promoting intra-SADC FDI flows. Further, the study finds evidence that agglomeration effects are important for South African investors into SADC despite the fact that they are operating in a common region. The study also finds that FDI from developed countries complement with FDI from South Africa. lts indicate that there is long-run level equilibrium relationship between the stock price of Taiwan and the NTD/USD exchange rates at lower distribution of stock prices, and at higher and lower distribution of exchange rates. The causality results show that there is unidirectional causality running from Taiwan stock price to the NTD/USD exchange rate at higher distribution of exchange rates. The result shows that there is evidence in favor of the portfolio hypothesis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".