Estimation of Gas oil Demand Function in Iraninan Agriculture Sector Using Structural Time Series Approach

Abstract

The correct estimation of gas oil demand function in agriculture industry and calculation of price and income elasticities is important to adopt the price and income policies. Therefore, in the present study the price and income elasticity of gas oil demand were estimated applying non-observable component to the process and creation of a state-space pattern and using maximum likelihood method and the Kalman Filter algorithm. In order to compare the obtained coefficients, ARDL, ECM and FMOLS methods were used. In addition, the data used in this research are collected for the period between 1974 and 2010. The results indicate that the estimated process is random and nonlinear, and its modality is Local Level Model. According to the estimated demand function, the estimated price elasticity of gas oil demand in the short and long term are -0.09 and -0.13, respectively. Also, in the short and long term, the income elasticity is 0.4 and 0.57, respectively. In addition, the coefficient of tractor number in each acre of the area under cultivation, which shows the sensitivity of gas oil demand to equipment and agricultural machines changes, is obtained to be 0.34.

Keywords

• gas oil demand
• agriculture
• structural time series
• underlying trend
• kalman filter algorithm
• state-space