It is widely known that when there are negative moving average errors, a high order augmented autoregression is necessary for unit root tests to have good size, but that information criteria such as the AIC and BIC tend to select a truncation lag that is very small. Furthermore, size distortions...

We consider issues related to the order of an autoregression selected using information criteria. We study the sensitivity of the estimated order to i) whether the effective number of observations is held fixed when estimating models of different order, ii) whether the estimate of the variance...