Determining Spatial Dependency of Systematic Risk of Dryland Wheat Yield in Iran: Application of Spatial Autoregressive Models

The purpose of this study is to determine spatial dependency pattern of systematic risk of dry land wheat production in Iran، using spatial autoregressive models. To this end، spatial weighted contiguity matrix was constructed based on the Delaunay Triangularization method، and correlation coefficient among these neighbors were estimated using spatial autoregressive models. In addition، the role of precipitation and temperature variables in explaining yield variations in wheat production cities was determined. Results indicated that: First، yield risk of dry land wheat production has a systematic nature and covers a considerable numbers of wheat producing cities. Second، the intensity of spatial correlation varies among neighbor’s cities. Precipitation and temperature variations play important role in explaining these differences such that the more variation in these variables is associated with the more variations in neighbor’s wheat yields. This is a useful piece of information that can be used in developing appropriate insurance portfolio of agricultural products to reduce risk of the insurers in Iran.