Financial Sector Development and Poverty Alleviation in the SADC Region
Bibliographic record
Abstract
Financial development is widely regarded as another conduit through which poverty can be reduced.The study empirically examines the relationship between financial sector development and poverty reduction in SADC countries utilising the Generalised Method of Moments technique for the period 1980 to 2017.The empirical results indicate that the effect of the different measures of financial sector development on poverty in the SADC region is mixed.Six out of nine financial development variables have a negative effect on poverty in the SADC region.In terms of financial depth, the empirical results reveal mixed outcomes.Results on financial system stability confirm the notion that a stable financial system is beneficial to the poor.The results also reveal that financial inclusion or access to financial services significantly reduces poverty in the SADC region.The results thus suggest that financial sector development is beneficial to the poor when it is inclusive and stable.The results imply that policies aimed at ensuring a stable financial system, which is also inclusive, should be pursued if the poor are to benefit from the financial system.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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".