Demand Estimation in the Presence of Stochastic Trend and Seasonality: The Case of Meat Demand in the United Kingdom
用Harvey的结构时间序列方法估计英国肉类需求，发现允许随机趋势和确定性季节性的模型在诊断检验和拟合优度上表现最佳，且预测能力更强。
Abstract If budget shares have stochastic trend or seasonality or both, then demand equations based on the assumption of deterministic trend and deterministic seasonality will be mis‐specified. We test this proposition by estimating a Linearized Almost Ideal (LAI) demand system for meat demand in the United Kingdom using Harvey's structural time series methodology. We demonstrate that the model specification allowing for stochastic trend and deterministic seasonality performs best in terms of diagnostic tests and goodness of fit measures. It is also shown that the model with stochastic trend is better at out‐of‐sample forecasting.