Ranking Crop Yield Models Using Out‐of‐Sample Likelihood Functions
通过比较六种概率分布在样本外的预测表现，对作物产量模型进行排序，发现Goodwin和Ker提出的半参数模型预测县级平均产量效果最好。
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 ranked 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.