The Use and Abuse of Real-Time Data in Economic Forecasting
区分了三种用实时数据估计预测方程的策略，指出最流行的方法应避免，并用工业产出、就业和零售数据预测GDP增长的例子证明替代方法更优。
We distinguish between three different strategies for estimating forecasting equations with real-time data and argue that the most popular approach should generally be avoided. The point is illustrated with a model that uses current-quarter monthly industrial production, employment, and retail sales data to predict real GDP growth. When the model is estimated using either of our two alternative methods, its out-of-sample forecasting performance is superior to that obtained using conventional estimation and compares favorably with that of the Blue Chip consensus. © 2003 President and Fellows of Harvard College and the Massachusetts Institute of Technology.