Financial Development and Poverty in Developing Countries: Evidence from Sub-Saharan Africa
Why this work is in the frame
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Bibliographic record
Abstract
The paper investigates how financial development affects poverty indicators in developing countries. We implement this analysis with a poverty model using data from 42 Sub-Saharan African countries and covering the period 1980-2012. We employ the System Generalized Method-of-Moment (GMM) that is appropriate to control country specific effects and the possible endogeneity. The empirical evidence shows that there indeed exists a financial development threshold below which financial development has detrimental effects on poor and above which financial development could be associated with less poverty. The evidence then points an inverted U curve type response and the findings are robust to changes in poverty measures and to alternative model specifications, suggesting thus the non-fragility of the linkage between financial development and poverty for sub-Saharan African countries. Our findings are then promising and support the view that the relation between financial development and poverty reduction is not linear for sub-Saharan African countries.
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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 | 0.001 |
| Open science | 0.000 | 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 it