Fiscal Dividend from Saving, Investment and Per Capita Income Growth in Sub-Saharan Africa: Panel Data Analysis
Bibliographic record
Abstract
Most of sub-Saharan Africa countries (SSA) have recorded impressive rates of growth and remained resilient to shocks especially during the recent past. Nevertheless, the status of social welfare has remained low as manifested by poor quality of standard of living and short longevity of life. In cognisance of the role of public sector to wellbeing through the fiscal arrangement, the objective of this study was to unearth the extent to which SSA have taken advantage of the achieved saving, investment and growth performance to enhance fiscal gains. Panel data analysis of 40 countries was done and results indicated that per capita income growth, total investment and gross national saving bolstered governments’ revenue and thus reduced budget deficits in SSA, except in the global economic crisis during which, only saving yielded significant fiscal dividend in terms of cushioning the revenue. In view of this, enhancing national savings (both public and private) in SSA can appropriate surpassing return to fiscal stance.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".