Ranking crop yield models using out-of-sample likelihood functions

There has been considerable debate regarding which probability distribution best represents crop yields. This study ranks six yield densities based on their out-of-sample forecasting performance. The forecasting ability for each density was ranking according to its likelihood function value when observed at out-of-sample observations. Results show that a semiparametric model offered by Goodwin and Ker best forecasts county average yields.