Donor Financial Inflows and Self-Reliant Farming Among Smallholder Farmers: Evidence from Yambio County, South Sudan
DOI:
https://doi.org/10.58721/dzkt5802Keywords:
Aid dependency, Farming, Financial inflows, South SudanAbstract
Smallholder farmer groups in Yambio County, South Sudan, financed their operations through donor funding, member contributions and informal savings, in a setting where private-sector credit was only 1.7% of GDP in 2019. Whether donor financial inflows have built lasting self-reliance, or a fragile dependency, remains an open empirical question. This study determined the extent and direction of the effect of donor financial inflows on self-reliant farming, guided by the Sustainable Livelihoods Framework, Collective Action Theory and Dependency Theory. A cross-sectional research design combining quantitative and qualitative approaches was used. 1,405 registered smallholder farmers were target population. Sample size of 278 included eight extension agents, leader, secretary and accountant of the 30 farmer groups. Simple random sampling was used to choose 180 group members from the farmers, and 170 of them (94.4%) returned valid questionnaires. An analytical sample of 268 respondents was obtained by including all 98 purposively selected key informants. Thematic analysis, multiple linear regression (SPSS version 21), and descriptive statistics were used to analyse the data. Donor cash inflows significantly improved self-reliant farming after controlling for technical support, knowledge transfer, age, education, gender, and marital status (B = 0.398, p <.001). However, donor-dependent programs were deemed extremely vulnerable to funding withdrawal by 77.6% of respondents. Generalization was limited by the research design and sample size; the conditions under which funding becomes catalytic were not tested statistically. Donors ought to structure funding as catalytic rather than recurrent support in addition to local savings mechanisms, financial literacy training and exit strategies from the outset.
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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.






