Role of Financial Development in Economic Growth: Evidence from Savings and Credits Cooperative Societies in Tanzania
Bibliographic record
Abstract
In this paper we examine the role of Savings and Credits Cooperative Societies (SACCoS) in the economic growth of Tanzania by answering two main questions. First, are financial services in SACCoS significant factors for economic growth? Second, are financial services in SACCoS Granger causing economic growth? We use credits-real GDP per capita ratio and savings-real GDP per capita ratio as proxy measures for financial services and real GDP per capita for economic growth. We employ Newey-West standard errors regression model and Wald Granger causality tests in analysis. The sample period is 1990-2012. Data are from the Ministry of Agriculture, Food and Cooperatives, World Economic Outlook (WEO) database, International Monetary Fund (IMF). The findings show that, there is a strong positive association between the financial services and the economic growth, also there istwo-ways Granger causality between them. However, we find out that savings are much important in fostering economic growth as compared to credits/loans. These criteria make SACCoS the distinct microfinance institutions in the economic development in Tanzania and therefore should be promoted with more emphasis on the savings objective.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".