Using qualitative response models in determining rainfall rates and their impact on wheat crop productivity in Iraq for 1995-2018

This work aimed to predict the wheat crop’s productivity based on annual rainfall rates and analysis in the manner of a qualitative response model. The research sample included a time series from 1995 to 2018, including the production and productivity of wheat crops in addition to the rainfall rates in the rainy and semi-dimensional region and the reality in northern Iraq. Three models have been used for a qualitative response, the linear probabilistic, Lagat and Probet models. The best one was the linear probability model. The dependent variable is the level of rain per year and the explanatory variable is the yield of a dunum of wheat. For the level of rain in which the crop yield was more than 250kg/dunum, the value 1 was considered for it, and if the dunum yield was less than 250kg/dunum, value was zero. Based on the results, the level of the annual rainfall affected the productivity of the dunum of the wheat crop because the riparian region is greatly affected by it. An increase of 1mm of rain annually led to the possibility of increasing the productivity of wheat crops by 0.2%kg/dunum.