Analysis of Factors Affecting Wheat Derived Demand and Its Forecasting with Emphasis on Consumer Preferences

Given the ever-increasing demand for wheat as an Input production in developing countries and the necessity of this product in the household basket, the accurate modeling of the Wheat demand function and determining effective factors for planning, as well as predictions for timely provision with low economic and social costs is important. In this study using underlying trend concept and creating a state - space model and kalman filter algorithms the wheat demand was estimated with emphasis on consumer preferences as a production input (derived demand) during 1982-2017. The results are non-smooth and Nonlinear trend (consumer preferences). Income and pricing elasticity of wheat derived demand less than one were estimated to be -0.0270 and 0.2148, respectively. So from one side Wheat was identified as An essential product with a high degree of urgent need and on the other hand price and income policies are not efficient enough to reduce consumption; So according to consumer preferences and the necessity of this product in the household basket, saving policy and consume right along with reducing waste it is suggested. Increasing efficiency in the conversion industry is one of the other ways to properly consume and reduce the ever-increasing demand for this product. The results of the prediction (in 2023, the projected amount is 24.48 million tons) with respect to consumer preferences in the model showed an increasing trend in wheat demand. Therefore, policymakers on the one hand can reduce demand by making decisions and the other hand provide the wheat needed for the conversion industry.