This paper aims to analyze the extent of off-farm income diversification of farm households in rural areas of Nigeria by age, gender, educational qualification, farm size, household size and across the different regions in the country. The determinants of such diversification were also identified. Data for this study were obtained from 836 rural farm households using the Nigeria General Household Survey, 2013. The Herfindahl Index was employed to analyze the share of income from different income generating activities, extent of off-farm income diversification. Tobit Regression Model was used to identify the determinants of such diversification.An estimate of 0.28 was observed for the Nigerian rural farm households with a higher extent of diversification in the Northern regions. Males, older farmers, and farmers without formal education had a higher extent of diversification. The results show that having higher landholdings, post-primary education, access to electricity and location are major factors. Identifying the extent of diversification into the different off-farm sectors is relevant to inform policy and provide opportunities for promoting the different off-farm sectors with an ultimate goal of improving rural farm households’ livelihoods. This has its resultant effect on development of the entire rural space.

Purpose The purpose of this paper is to analyze the effect of the different components of off-farm income on multi-dimensional poverty. Furthermore, the study aims to measure multi-dimensional poverty and also identify the determinants of multi-dimensional poverty in Nigeria. The paper reveals the different contributions of the dimensions of education, health and living standard. Design/methodology/approach The study focuses on rural farm households in Nigeria. Data are obtained from the Nigeria General Household Survey, 2013. The survey covers both urban and rural areas of the 36 states of Nigeria. Owing to the interest of this study in the rural farm household’s sub-sector, a nationally representative sample of 836 rural farm households are selected for the study after the data merging process. Rural farm households in this paper earn 50 percent of their total income from crop and livestock production. The paper employs the Multi-dimensional Poverty Index (MPI) to measure multi-dimensional poverty across the six different geographical zones of Nigeria. The probit regression model is used to estimate and analyze the effect of off-farm income components on multi-dimensional poverty and also to identify the determinants of multi-dimensional poverty. Findings The results of the study show that among the off-farm income components, the non-farm wage income and non-farm self-employment income have negative association with multi-dimensional poverty. Findings show that multi-dimensional poverty is high in Nigeria with deprivations in health contributing the most. Northern Regions have a higher estimate. Results reveal that sex, age, number of adults, formal credit access, access to extension services and location characteristics are key determinants of multi-dimensional poverty. The MPI for Nigeria averaged 47 percent. Across regions, deprivation in the health dimension contributes about 44 percent to multi-dimensional poverty. Deprivation in living standards contributes 40.5 percent, while deprivation in education contributes 15.5 percent to multi-dimensional poverty. Research limitations/implications Due to the nature of the data used, the health indicators (nutrition and child mortality) are absent but proxies are used instead. Future research could introduce gender dimensions. Practical implications Improving the involvement of rural farm households in non-farm self-employment sector could improve their livelihoods and prevent migration to urban centers, especially among the youths. Social implications Improving the quality of health, education and living standards will lead to lower poverty levels in Nigeria. Farmers can best reduce their multi-dimensional poverty by engaging in more off-farm jobs. Originality/value This paper provides information to policy makers on the effect of different components of income from the off-farm sector on multi-dimensional poverty alongside with the determinants of multi-dimensional poverty at a national level for the rural farm households. By using MPI, the contribution of the different dimensions used in computing the MPI across the six geographical regions within the country is revealed. This provides policy makers with more information for development purposes.