Pitfalls in the Estimation of a Differenced Model

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).