Determinants of poverty among rural farming households in Maiha Local Government Area, Adamawa State, Nigeria

Abstract

Poverty is a critical factor affecting subsistence of farmers in Nigeria, especially in rural areas. The study examined determinants of poverty among rural farming households in Adamawa State, Nigeria. Specifically, the research objectives were to: describe the socio-economic characteristics of the respondents, determine the poverty status of the respondents, and examine the determinants of poverty among the respondents. Primary data used for the studies were generated from 255 respondents, who were selected using a multi-stage random sampling technique. The analytical tools used were descriptive, Foster-Greer-Thorbecke (FGT), and Logit regression models. The findings of the study revealed that the majority (90.98 %) of rural farming household heads were men, married (90.20 %) with a mean age of 38.42 years, educated (76.48 %), with a mean farm size of 2.65 ha and mean household size of 5 people. The majority (85.88 %) of the respondents had no access to credit. The study further revealed that respondents’ distributions by poverty status were 0.42, 0.23, and 0.16 for poverty incidence (Po), poverty depth (P1), and poverty severity (P2), respectively. The result of the Logit regression model revealed that sex, formal education, primary occupation, access to credit, total income, and annual remittances had a positive influence on poverty status, while age, marital status, and household size had a negative influence on poverty status among farming households and were statistically significant at various levels. Hence the study recommends need for the farming households to have access to credit schemes. This could increase the off-farm activities that could generate more income for the household and thereby reduce their poverty.

Nexus of livelihood diversification on food security status among rural households in Agbani agricultural zone of Enugu state, Nigeria

“…This could be due to lack of capital needed for livelihood diversification. This is in line with Dia et al, (2022), where the majority of the households had low diversification, and a small percentage being highly diversified.…”