Pitfalls in the Estimation of a Differenced Model
评估了当原始线性回归模型的扰动项服从稳定AR(1)过程或固定起点随机游走过程时，采用差分模型导致的估计效率损失大小，发现损失可能很大，且受模型形式、自相关系数符号和大小以及外生变量性质的影响。
Abstract This article assesses the potential magnitude of the loss of estimation efficiency caused by the adoption of a differenced model when the disturbances of the original (levels) linear regression model follow either a stable (autoregressive) AR(1) process or a fixed start-up random-walk process (hence no filtering is necessary from the standpoint of estimation). The magnitude of the loss, which can be quite large, is found to be affected by both the form of the original model (homogeneous or nonhomogeneous) and the sign and magnitude of the autocorrelation coefficient of the AR(1) disturbance, as well as by the nature of the exogenous variable (smoothly trended or not). KEY WORDS: Loss of efficiencyTrended variables