PREDICTIVE MANAGEMENT COMPONENTS ON REDUCING THE RISK AVERSION COEFFICIENT: MAIZE FARMERS OF NORTHWESTERN IRAN - Mojtaba SOOKHTANLOU; Hesamedin GHOLAMI (Scientific Papers Series : Management, Economic Engineering in Agriculture and Rural Development)
Increasing agricultural risks is a major challenge in economy and efficiency in the agricultural sector that affect income and production decisions of farmers and sometimes is a major obstacle in the sustainable development. Thus, the main purpose of study was to predict the management components in reducing the risk aversion coefficient (RAC) among maize farmers in Moghan plain (Iran). 278 farmers selected using multistage random sampling. RAC calculated through Safety First Rule model and predictive management components were determined by ordered logistic regression (OLR) by STATA software. Results revealed that the most of maize farmers (65.10%) were riskaverse. Also, results of OLR revealed that the probability of placing the farmers at higher levels of risk aversion increased significantly by increasing age, farming experience, farm input costs and facing with more agricultural risks; while increasing education level and farm income, better farm and technical infrastructure management and better risk-sharing management, the probability of placing the farmers at lower levels of risk aversion increased.