Comment on "Statistical Adequacy and the Testing of Trend Versus Difference Stationarity" by Andreou and Spanos (Number 2).

In the two decades since the influential paper by researchers C.R. Nelson and C.I. Plosser documented that many macroeconomic time series appear to exhibit unit roots, a large literature has investigated their data, reaching a number of potentially conflicting conclusions about various characteristics such as unit roots, structural change and linearity. For example, researcher P. Perron noted that the conclusion of difference stationarity may have been due in part to failure to account for structural change and illustrated that using a model allowing for structural change, the null of a unit root was rejected in favor of trend stationarity for 10 of the original 13 Nelson-Plosser series. Many more articles related to the difference versus trend stationarity debate have been written, most either applying existing techniques to new datasets or, like those previously mentioned, taking issue with an earlier maintained assumption to develop a modified specification in the hope of obtaining a more clear solution. In fact, what the large body of literature and the continuing debate mainly illustrates is a truth so fundamental that it is perhaps often forgotten, that inference depends crucially on model specification and the underlying assumptions inherent in the chosen model.