The Impact of Trade Openness and Foreign Direct Investment on Economic Welfare in sub-Saharan Africa
Bibliographic record
Abstract
The sub-Saharan African region is characterized by a high relative degree of openness to trade. The region is also identified with increased inflows of foreign investments with no significant welfare improvement. Economic development emphasizes that the lack of domestic investment in the developing economies could be boosted by trade openness and inflow of Foreign Direct Investment (FDI) for impactful enhancement of capital formation. In this article, the impact of trade openness and foreign capital inflow on economic welfare was examined on a sub-regional analysis for sub-Saharan Africa. The study also appraised the effect of openness to trade and FDI inflow on the region's economic welfare. The data for 30 countries from 2000 to 2018 were collected and analyzed, with the Generalized Least Square (GLS) technique to fit the model developed. The study showed that openness to trade has a significant impact on economic welfare for all sub-Saharan Africa regions, while FDI is only significant for the Western sub-region. Hence, the study recommends that the government of the countries in the sub-Saharan Africa region should boost trade openness to enhance efficiency in productivity, and improve industrial development.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".