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

Researchers E. Andreou and A. Spanos provide a further analysis of the unit root versus trend stationary debate using the data set of researchers C.R. Nelson and C.I. Plosser. They present an interesting and novel approach to the problem. The main argument of the paper is that any such analysis should be preceded by a statistical adequacy analysis. As they state, "By statistical adequacy we mean the empirical validity of the probabilistic assumptions underlying the estimated statistical model. Establishing statistical adequacy provides a sufficient condition for statistical inference because the latter presupposes the validity of the model specification." The criteria adopted to assess statistical adequacy are: normality of the process; linearity; homoskedaticity; t-invariance of the parameters; and errors are an innovation process. Conclusions are basically the same as those of researcher P. Perron except for 3 series: GNP deflator; velocity; and stock prices. All rejections, except for the unemployment rate of course, are obtained introducing breaks in the trend function as in Perron showing the importance of the feature in the data.