Financial inclusion of urban agro-processors: effect of credit on poverty status of roasted plantain vendors in Calabar, Nigeria
Bibliographic record
Abstract
This study analysed the effect of credit on the poverty status of roasted plantain vendors in Calabar, Nigeria. The study described sources of credit, comparing the poverty status of credit recipients versus non-recipients, and the relationship between credit access and poverty index alongside the relationship between socioeconomic factors and poverty index. Data was collected from 110 randomly sampled roasted plantain vendors with the use of structured questionnaire. Poverty was measured with the Foster, Greer and Thorbecke (FGT) model class of weighted poverty measures. Descriptive statistics were used to examine poverty status, access to credit and the sociodemographic attributes of the roasted plantain vendors. Next, using descriptive statistics, the poverty status of the vendors who accessed credit was compared to those who did not access credit. Finally, the association between access to credit and poverty index was analyzed with logistic regression model while adjusting for the effects of sociodemographic factors. Descriptive statistics showed that 60% of the vendors were female, the average age was 35 years, and the average household size was four persons. Precisely, 91% of the roasted plantain vendors had completed primary or higher education. Exactly, 64.5% received credit, while 30.79% reported non-institutional lenders as sources of credit. The mean monthly income was N48,036.36 (US$116.89). Poverty incidence was lower among credit recipients (0.268) compared to non-recipients (0.487). Credit access (OR = .083, p<.01) and household (OR=2.496, p<.01) had statistically significant associations with the poverty index. Policies promoting structural transformation are recommended for sustainable financial inclusion. An effective economic growth and development program, for example, will increase productive capacities and reduce capital losses, increase creditworthiness, motivate capital expansion and sustainable growth. Also, it was recommended that cooperative formation among the vendors is required. Membership of such a cooperative will increase credit access through reduced transaction cost, higher group’s creditworthiness/borrowing experience and stronger negotiation capacity. A Nigerian economic transformation program to promote increased productive capacities and reduced capital losses is necessary for any financial inclusion policies to sustainably alleviate poverty among deprived agro-processors such as the roasted plantain vendors. Such programs will include financial literacy including banking and loan repayments, business innovations, and business plan development. Key words: Credit, Financial inclusion, Micro-agro-processors, Plantain roasting, Poverty, Urban agriculture
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".