Poverty Incidence and Determinants among Smallholder Farming Households in Rural Cameroon
Nyamka Milton Kibebsii
*
Department of Agribusiness Technology, College of Technology, the University of Bamenda, P.O. Box 39, Cameroon.
Che Dimna Bih
Department of Agribusiness Technology, College of Technology, the University of Bamenda, P.O. Box 39, Cameroon.
Tsi Evaristus Angwafo
Department of Agribusiness Technology, College of Technology, the University of Bamenda, P.O. Box 39, Cameroon.
Bime Mary Juliet Egwu
Department of Agribusiness Technology, College of Technology, the University of Bamenda, P.O. Box 39, Cameroon.
Balgah Roland Azibo
Department of Agribusiness Technology, College of Technology, the University of Bamenda, P.O. Box 39, Cameroon and Sol Plaatje University, Kimberley, South Africa.
Peter Ngek Shillie
Department of Agribusiness Technology, College of Technology, the University of Bamenda, P.O. Box 39, Cameroon.
Chiatoh Fabian Ntangti
Catholic University of Cameroon (CATUC), Bamenda, Cameroon.
*Author to whom correspondence should be addressed.
Abstract
Poverty in Africa is primarily concentrated in rural areas, where agriculture serves as the main source of livelihood. However, the distribution of poverty among rural farming households and the factors that drive it remain under-researched. This study examines how poverty is distributed among smallholder farming households in rural Cameroon and identifies the key determinants shaping this distribution. Using a cross-sectional quantitative design, primary data were collected from 420 smallholder household farmers through a structured questionnaire administered to household heads. Foster-Greer-Thorbecke (FGT) poverty measures are applied to capture poverty incidence, depth, and severity, and logit and OLS-based econometric techniques to identify determinants of poverty. Descriptive results reveal that 48.1% of sampled households are classified as poor (P0), with a mean poverty gap index of 0.23 and a squared poverty gap index of 0.11, indicating that poverty is severe and unequally distributed among the households. Econometric results show that institutional quality, infrastructure development and shocks are the most consistent determinants of poverty reduction: a one-unit increase in the institutional quality index reduces the probability of being poor by 12.7 percentage points (p < 0.01), while a one-unit increase in infrastructure access reduces poverty severity by 0.08 (p < 0.01). Exposure to shocks increases the poverty gap by 0.15 (p < 0.05). Although access to credit reduces poverty incidence by 7.3 percentage points (p < 0.10) and extension services reduce the poverty gap by 0.04 (p < 0.05), their effectiveness depends on strong institutions, adequate rural infrastructure, and resilience mechanisms. We conclude that improving institutional quality, adopting integrated development strategies, and building resilience can reduce poverty among smallholder farmers in Cameroon. Accordingly, we recommend a combined strategy that strengthens agricultural institutions, enhances local governance, and boosts resilience capacity as an effective approach to reduce poverty among rural farming households in Cameroon.
Keywords: Smallholder agriculture, poverty alleviation, institutional quality, infrastructure, resilience, rural Cameroon