Agricultural Economics
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Item Technical efficiency and socioeconomic effects on poverty dynamics among cassava-based farming households in rural Nigeria(AgEcon search, 2021) Obayelu , O. A.; Obayelu, A. E.; Awoku, I.Despite the large scale public and government investment to improve the livelihoods of smallholder farmers, rural poverty remains widespread in Nigeria. However, efficiency effects on the transitory poverty has not received much attention in the poverty literature in Nigeria due to lack of nationally representative panel data that can track the poverty status of households over time. Using a two-wave panel data between 2010 and 2015, technical efficiency effects on poverty dynamics of cassava-based rural households in Nigeria was therefore investigated. Results showed that 14.9 % of the cassava farming households moved into poverty while 31.6 % exited from poverty. In the long run, the probability that rural cassava-based farmers would be non-poor (74 %) was higher than those remaining in poverty. Two out of five (42.2%) cassava-based farmers who were always poor exited technical inefficiency. A large number of farmers were actively involved in mono-cropping and mixed cropping but 29.7%, 26.0% and 16.6% of those involved in mono-cropping were always poor, entered and exited poverty, respectively. Tertiary education, marital status, access to extension farm size, membership of association, farming systems and technical efficiency were factors influencing poverty transitions in rural Nigeria.Item Nutritional Vulnerability Transitions among Rural Households in Nigeria(2023) Adepoju, A. O.Aims: It has long been considered that specific age/gender groups, such as women and children, are predisposed to nutritional vulnerability. Thus, nutritional vulnerability among agricultural households is neglected and understudied. This study aims at an empirical assessment of nutritional vulnerability dynamics among rural households in Nigeria. Study Design: Secondary data used for this study was waves 2 and 3 of the general household survey panel data. The sampling design consisted of two stages of sampling: the selection of enumeration areas based on probability proportionate to the size of the enumeration areas and the systematic random selection of ten households from each enumeration area. There were 3370 households selected in rural areas and 1630 households selected in urban areas. 2090 rural households with the required information for this study were included in the analysis. Methodology: Descriptive statistics, nutritional vulnerability score, logit regression model, Markov model, and multinomial logit regression models were used to analyse nutritional vulnerability transitions among rural households in Nigeria. Results: Nutritionally vulnerable households in rural Nigeria include those with aged heads, little or no formal education, limited assets, and no access to land or credit. Nutritional vulnerability in rural Nigeria is primarily transient, with around two-fifths of households experiencing transient nutritional vulnerability and nearly one-third experiencing chronic nutritional vulnerability. While the age of the household head, tertiary education, and access to credit all had a substantial impact on transient nutritional vulnerability, gender, tertiary education, asset value, and access to credit all had an impact on chronic nutritional vulnerability. Conclusion: Support mechanisms such as initiatives to promote access to healthy food, credit, land, and education are critical. To successfully address the issues affecting the nutrition and health of persons facing vulnerabilities, social welfare programs with interventions based on the characteristics of each vulnerable group and the predisposing factors should be adopted.