Forecasting Short‐Run Fed Beef Supplies with Estimated Data
估计了肉牛育肥过程中的未知汇总数据（如入栏体重、生长率、性别组成），将其纳入传统计量模型后提高了育肥牛肉供应的预测精度，为利用微观关系模拟模型估计未知数据提供了通用方法。
Abstract Unknown aggregate data series for the placement weight, growth rate, and sex composition of cattle placed on feed are estimated. The estimates are made by treating the unknown data as time‐varying parameters of a cattle‐on‐feed growth and inventory stimulation model. A nonlinear optimization algorithm is used to estimate the unknown parameter series that optimize the model's simulation accuracy. Incorporation of the estimated series into a traditional econometric fed‐beef‐supply forecast model improved the model's forecast accuracy. The methodology used provides a general procedure for estimating unknown aggregate data using simulation models based upon microrelationships.