Determinant of Risk-Smart Options among Farming Households in Agricultural Risk Management in Imo State, Nigeria

Globally, farmers deal with a significant magnitude of uncertainty all day long. From not knowing what the vagaries of weather will be like now, to wondering if market prices will increase or decrease the next moment. Therefore farmers are compelled to make decisions based on imperfect information and knowledge. Particularly, in Imo State Nigeria, farmers are heavily exposed to risk. Regrettably, the resultant effect is low agricultural output in the State all year round. The article soughed to bring incisive clarity to this discourse by estimating the determinant of Risk-Smart options among farming households in the area. Multistage random sampling technique was used in selection of One hundred and Twenty (120) household heads from the area. Well structured questionnaire was the main tool for data collection. Descriptive statistics, Smart-Art, and Multinomial Logit Model were used for data analysis. Mean age was 45.03years. Majority (65.83%) were males. Farmers cultivated on an average farm size of 1.21Ha. The study confirmed the evidence of various agricultural risks in the area. Thus, farmers have started becoming Risk-Smart through the adoption of several Risk-Smart options to thwart the negative impacts of the risk in the area. The major Risk-Smart options farmers used were diversification of livelihood (100.00%). Unfortunately, farmers Risk-Smart options are just insufficient to prevent them from devastation. However, if farmers Risk-Smart capacity are not strongly built, agricultural production in the area may be unfavourable with time. Estimated multinomial logit model showed that socio-economic characteristics of the farmers have a significant influence on their Risk-Smart options in the area. Farmers complained of inadequate Risk-Smart adoption funds and indiscriminate grazing of arable farmland by Fulani herdsmen cow. It was therefore recommended that farmers should be encouraged to form agricultural production and marketing cooperative to enhance their risk-smart capacity in the area. Farmers on their own should also construct an improvised heavy wire mesh around their farms to check the indiscriminate grazing of their arable farmland by the Fulani herdsmen cow in the area. Keywords:Risk, Risk-Smart Options, Risk management, Socio-economic variables, Multinomial Logit Model, Barriers, Fulani Herdsmen, Imo State, Nigeri