Financial Deepening, Stock Market, Inequality and Poverty: Some African Evidence
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents evidence about the relationship between private credit, stock market indicators, income inequality and poverty, using the annual data that ranges from 1992 to 2018 on nine African economies. We applied the estimation method of Autoregressive Distributed Lag (ARDL) to model the long-run effect. In Addition, we used Dumitrescu and Hurlin Panel causality to check the direction of causality. The results of long-run estimates show that the stock market indicators have a significant positive impact on income inequalities, but have a negative and significant impact on poverty. Further, our findings show that private credit adversely reduces income inequalities. Our results also establish significant short-run causalities among stock market indicators, private credit, income inequalities, and poverty.
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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 | 0.000 |
| 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