The Nexus between Institutional Quality & Foreign Direct Investment (FDI) in Sub-Saharan Africa
Bibliographic record
Abstract
This study analyzes the nexus between foreign direct investment and institutional quality including political stability, rules of law, government effectiveness, voice & accountability, and regulatory quality. The major aim of this study is to examine the relationship between institutional quality and foreign direct investment. This study consists of a sample of Sub-Saharan African countries. Our study employed two-panel data techniques including Random Effect Model (REM) and Vector Autoregressive Model (VAR). The study period covers from 2015 to 2019. Empirical findings of REM indicated that both rules of law and government effectiveness have positive and statistically significant influences on foreign direct investment inflow in the SSA region. Similarly, the study utilized other explanatory variables such as the trade and labor force. The result of VAR highlighted the positive and statistically significant influence of labor force and trade on foreign direct investment inflow, therefore, the effectiveness & efficiency of region institutional quality are usually dependent on the robustness of those variables. Thus, the study recommends having higher foreign direct investment inflow in the region is necessary to make policy reforms that strengthen the quality and efficiency of governance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".