DETERMINANTS OF AGRICULTURAL RISK MANAGEMENT BEHAVIOUR OF CROP FARMERS IN NIGERIA (2014)
Agricultural risks constitute a fundamental challenge in Nigeria, leading to low productivity among farmers. Farmers risk management behaviour determines the extent to which they overcome risk types. Information on crop farmers’ risk management behaviour in Nigeria is however scanty. Therefore determinants of agricultural risk management behaviour of crop farmers in Nigeria were investigated. Multistage sampling technique was used. Of the agro-ecological zones, Coastal, Rainforest and Guinea savannah were randomly selected. Thereafter, 10% of the states in the zones (Lagos, Osun and Niger) and 10% of the Local Governments Areas (LGAs) in the states were selected. Two communities were selected from each of the LGAs and 15% of crop farmers were chosen in the selected communities to give 323 crop farmers. Interview schedule was used to collect data on respondents’ risks types, risk exposure levels and risk management strategies. Indices were used to categorise farmers on their risk types (production, marketing, financial and social) and risk behaviour (superior, active, di-function, mono-function and part-time risk managers). Data were analysed using descriptive statistics, chi-square, Pearson Product Moment Correlation, ANOVA and multinomial logistic regression at p= 0.05. Most (90.0%) respondents were males, married (89.7%), and had at least primary school education (62.3%) with farm sizes of less than 5 hectares (72.3%). Age and years of farming experience were 53.2±10.5 and 28.3±12.1 years respectively. Majority (94.2%) identified inadequate cash-flow, pests and diseases (91.3%), ill-health of farmer/farm employee (89.0%) and volatility in output price (85.5%) as types of agricultural risks. Respondents were more vulnerable to production (9.85) and financial (9.84) risks. Majority (81.3%) were moderately or highly exposed to agricultural risks. Risk management strategies highly utilised were reducing leverage (2.94), maintaining good relations with contracting partners (2.73), use of fertilizers (2.65) and use of improved seedlings (2.57), while 73.9% of the farmers that had crop insurance coverage affirmed that it was effective in managing risks. Use of risk management strategies was low for 47.1%, with marketing strategies being the least (1.17) utilised. Superior agricultural risk managers accounted for 14.2%; active (26.8%); di-function (33.2%); mono-function (21.9%) and part-timers (3.9%), with the coastal zone having the highest percentage of superior (19.0%) and active (43.1%) risk managers. There were significant relationships between level of risk management and each of sex, marital status, educational level and farm size. While the Guinea savannah zone had the highest level (259.58) of agricultural risk exposure, the coastal zone had the highest level (75.89) of agricultural risk management. Significant predictors of agricultural risk management behaviour were farm size, organization membership and risk exposure level for mono-function and active managers. Di-function and superior managers were significantly predicted by farm size and risk exposure level respectively. Crop farmers in the zones encountered more of production and financial risks and lacked adequate risk management strategies. Their low level of insurance coverage indicated that factors other than awareness determined participation in insurance. Crop farmers should utilise more risk management strategies in order to reduce their risk exposure levels.