Financial Inclusion and Economic Growth in Sub-Saharan Africa—A Panel ARDL and Granger Non-Causality Approach
Why this work is in the frame
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Bibliographic record
Abstract
Many earlier development finance studies have attempted to assess the relationship between financial inclusion and economic growth. However, the findings of these studies vary from economy to economy and region to region due to various social and economic factors. We, therefore, deemed it pertinent to examine the relationship between financial inclusion and economic growth while further identifying the direction of causality between the two variables in twenty-six (26) Sub-Saharan African (SSA) economies using annual secondary data over the 2000–2019 period. In our paper, we used the principal component analysis (PCA) technique to develop a single composite index to proxy financial inclusion while adopting panel unit root, system generalised method of moment (GMM), and ARDL cointegration tests to assess the stationarity properties, assess the factors that affect economic growth, and examine the long-run relationships between financial inclusion and economic growth, respectively. In addition, a Granger non-causality test is used to verify the direction and magnitude of causality. Our study revealed that financial inclusion and economic growth share a strong long-run relationship and that there is bi-directional causality, indicating synergy between these two variables. In order to ensure sustainable economic growth, we thus recommend that developing countries develop macroeconomic policies that will promote financial inclusion while enhancing the functioning and regulation of the domestic financial markets to ensure that all citizens are catered for in the available instruments, products, and service offerings. Within the same policy framework, efforts must be made to further support productive sectors of the economy to ensure economic growth.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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