Heliyon (Jan 2024)
Networking and training for IMPROVEMENT of farm income: A case of lifelong learning (L3F) approach in West Africa
Abstract
The lifelong learning for farmers program of the Commonwealth of Learning relies heavily on innovation platforms to address the critical information gap left by agricultural research and development, which often fails to reach the intended rural farmers. The fundamental tenet is that these activities require a space for stakeholders to collaborate, overcome obstacles, and seize opportunities for agricultural development. Therefore, this study investigated the impact of networking and training on farm income in West Africa. A multistage sampling technique was employed to select 1800 households from the study site which cuts through the Kano-Katsina axis in Nigeria and the Maradi axis in the Niger Republic. The probit and mediation models were used to analyse the data. The probit model suggested that the decision to join innovation platforms is significantly influenced by factors such as married status, education, household size, farming experience, and the proportion of males and females in the working class, and young dependents. Furthermore, the probit model shows that the decision of farmers to take part in the training offered by innovation platforms is significantly influenced by factors such as gender, age, years of education, household size, and the proportion of males and females in the working class as well as elderly dependents. The mediation analysis results showed a positive and significant correlation between farm income and membership in innovation platforms (IPs). The direct effect suggested that farm incomes rise by 77.5 % upon joining IPs. Upon breaking down the overall impact into direct and indirect effects, it became evident that participation in IP training mediated nearly 86 % of the total impact of IP membership on farm income. The study concludes that participation in innovation platforms has a positive effect on farm income when they take part in educational programs hosted on the platforms, even after adjusting for observed and unobserved covariates. Consequently, the study suggests that any policy aimed at the welfare of farmers should take participation in lifelong training programs of IPs into account.
