The impacts of climate change on wheat production: A Stochastic production function approach

The purpose of this study was to evaluate the impacts of climate variables on yield and risk of Iran’s wheat production. In this context, crop year data were collected from 1982-83 to 2014-15. Considering crop season, monthly data were aggregated into seasonal data. Iran was divided into four climatic zones. To the optimal selection of predictor variables, Feiveson algorithm was applied. To test the effect of climate variables on wheat production, a Just-Pope stochastic production function was used for each zone. To estimate the panel with fixed effect model, considering the volume of data, Feasible Generalized Least Squares (FGLS) approach was applied. Overall, the results showed that the effects of temperature and precipitation indices are regional; these zones are differently affected by climate indices. Yearly climatic variability has created adverse conditions; However, in some zones, these impacts are negligible; Iran is in the exposure of relatively dry climate with hot summers and cold winters, and extreme temperatures annual events and irregular rainfall changes over the past years have made these farmers more resilient and adaptable.