Pre-harvest forecasting of county wheat yield and wheat quality using weather information

► We develop regression models to predict wheat yield, protein, and test weight by county. ► We use a unique dataset on grain quality collected by Plains Grain, Inc. ► Our weather data are from the Oklahoma Mesonet system. ► Out-of-sample forecasting tests show that the models provide useful forecasts. County wheat yield and wheat quality are forecast using weather information. Regression models are estimated to account for the effect of weather on county wheat yield, protein, and test weight. The explanatory variables include precipitation and temperature for growing periods that correspond to biological wheat development stages. Wheat yield, protein, and test weight are strongly influenced by weather. The forecasting power of the yield and protein models is enhanced by adding a spatial lag effect. Out of sample forecasting tests confirm the models’ usefulness in predicting wheat yield and wheat quality.