Microcredit and Poverty Reduction: A Case Study of Microfinance Fund for Community Development in Northern Vietnam
Bibliographic record
Abstract
Like other developing countries, microcredit in Vietnam has been recognized as an important credit source of the poor, who need capital but are normally by-passed by commercial banks. However, the provision of credit to the poor is challenged by the existing tradeoff between depth of outreach and financial sustainability. In this study, Principal Component Analysis and Propensity Score Matching were used to assess whether microcredit reaches the poor and its role in poverty reduction. The Microfinance Fund and Community Development (MFCD), a microfinance institution in Northern Vietnam was selected as a case study. The research has shown that microcredit successfully reaches the poor households as 67% of credit recipients belong to the last three bottom groups. The observed poverty targeting is consistent with the mission of the microfinance institution. In addition, the provision of microcredit has positive but statistically insignificant impact on household income and expenditure. This study suggests that unless access to additional resources should be made available to the poor, a small amount of credit alone could be insufficient to reduce poverty.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".