No. 215 - Testing Stationarity of Economie Time Series: Further Monte Carlo Evidence

Testing stationarity of economic time series has become a central issue in empirical economics. This paper evaluates, via Monte Carlo simulation, the empirical power and size of the augmented Dickey-Fuller test for a unit root (ADF test), the most used in empirical works, and of the test recently proposed by Kwiatkowski et al. (KPSS test), where the null hypothesis is one of stationarity. The evidence confirms that both procedures suffer of very low power and, in the case of the KPSS test, large size distortions, especially in samples of the sizes usually available in practical applications. Moreover, their performance is highly sensitive to the true generating process, as well as to the way one parameterizes each test. It is shown, however, that a combined ADF-KPSS procedure would allow to significantly reduce the number of erroneous conclusions, although at the cost of incurring in a fairly large amount of inconclusive answers. In the last part of the paper the various testing procedures are applied to a set of historical time series for the Italian economy. The evidence provided by the ADF test strongly supports the unit root hypothesis. However, using either the KPSS or the combined procedure, the evidence becomes less decisive.