The Impact of Financial Development on Human Well-Being in Sub-Saharan Africa: Does Institutional Quality Matter?
Bibliographic record
Abstract
This paper investigates the role of institutional quality in the effects of financial development on people's well-being in Sub-Saharan Africa. We use data from 35 countries from 2007 to 2021. The study tests for non-linearity between financial development and well-being by identifying threshold effects of financial development, using the panel smooth transition regression (PSTR) model of Gonzalez et al. (2005) and a quadratic model using the system GMM of Blundell and Bond (1998). The estimation results show that there is a non-linear relationship between financial development and well-being, conditioned by institutional quality and expressed as an inverted U-shape. There are financial development thresholds (40.217% for CRED and 49.038% for M2GDP) beyond which any improvement in the financial system leads to a loss of well-being in Sub-Saharan Africa. We show that low institutional quality reduces the positive effect of financial development on well-being. However, there are thresholds of institutional quality beyond which economic and political institutions reinforce the positive effect of financial development on well-being.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".