A panel analysis of FDI inflows and poverty reduction in BRICS countries: An implication for the sustainable development goal one
Bibliographic record
Abstract
FDI inflows and poverty reduction nexus has been an ongoing global debate in the recent times. Against this backdrop, this study examined the relationship between FDI inflows and poverty reduction in this economic bloc between 1990 and 2019. Data was collected from UNCTAD and WDI respectively, and a Panel Error Correction Model and the Pairwise Dumitrescu Hurlin Panel Causality tests were respectively employed. The following findings originated from the study; firstly, the relationship between FDI inflows and human development was negative and significant in the short run. In the long run, the reverse was the case. Therefore, the study concluded that FDI inflows have a trickle-down effect on poverty reduction in BRICS countries only in the long run. Therefore, it was recommended that for the policymakers in BRICS countries to achieve the Sustainable Development Goal (SDG 1), policy that will propel massive inflows of FDI into BRICS economies should be explored.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".