How do we know macroeconomic time series are stationary

It is generally accepted in macroeconomics, especially since the validation of Real Business Cycle Theory by the awarding of the Noble Prise in Economics to Edward Prescott in 2004, that macroeconomic time series data are stationary. Other time series empirical work on unit roots and co-integration indicates that most macro time series data are difference stationary. That is they follow a first order of integration (or I1) process. This paper questions whether we can be assured that this is the case by generating artificial data designed to emulate the macroeconomic data from a simulation model of general purpose technology (GPT) driven growth based on Carlaw and Lipsey (2007). The data generating process is explicitly non-stationary (trend and difference). We analyse the business cycle properties of the data by matching growth rates to actual Canadian data from the period 1961-2007 and find that the growth properties of the simulated data are consistent with the Canadian data. We then filter the simulated data using the annualized Hodric-Prescott filter and examine the data's Real Business Cycle properties. We find that the business cycle properties are a close but not exact match with those of the Canadian. We then perform a time series econometric analysis of the data to determine its time series properties and conclude that the data exhibit first order difference stationarity (i.e., the follow an I1 process). We conclude that it remains an open question as to whether real macroeconomic time series data is in fact trend or difference stationary and further empirical methodology may need to be developed to verify or refute the statement. These findings have some important implications for testing and drawing inference from macroeconomic time series data. In particular as noted by Libania (2005) the original work by Nelson and Plosser (1982) presented an empirical case that macroeconomic time series are difference stationary. This was taken as evidence in support of the RBC hypothesis that once the trend is filtered from macro data the business cycle exhibits stationarity and therefore monetary shocks can only have temporary effect. Furthermore, although Nelson and Plosser (1982) state explicitly that they assumed that the classical dichotomy held for their analysis, it has come to be generally accepted that the business cycle is stationary and therefore the dichotomy does hold.