The Relationship Between Inclusion, Financial Innovation and Economic Growth in Sub-Saharan African Countries: A PVAR Approach
Bibliographic record
Abstract
The objective of this paper is to examine the relationship between inclusion, financial innovation, and economic growth.The goal is to verify the existence of a bidirectional relationship between the three variables.For this purpose, we use the Panel Vector Autoregressive (PVAR) model in the Generalized Method of Moments (GMM) on data from 46 Sub-Saharan African countries.The results confirm the existence of a positive and unidirectional relationship between economic growth and financial innovation and the existence of a unidirectional relationship between financial inclusion and economic growth.Additionally, our results show that there is a bidirectional relationship between economic growth and investment.Regarding practical implications, this study jointly analyzes three current and interrelated topics that pose a problem for the African continent and expands the scarce literature on financial development and economic growth.As for originality, this study considers the possibility of a bidirectional relationship between inclusion, financial innovation, and economic growth using a sample of 46 sub-Saharan African countries covering the period 2005-2018, a fact that was ignored in previous studies when they examined only unidirectional causality.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".