Periodic Cointegration
Philip Hans Franses · 1996
Abstract This chapter deals with empirical periodic models for multivariate time series with one or more stochastic trends. In the previous two chapters we have seen that for univariate variables periodic time series models are most easily analysed in the vector of quarters (VQ) form. This amounts to investigating the properties of a quarterly observed time series y1via an analysis of the properties of the (4 x 1) vector process YT ‘ which contains the observations in each of the quarters. As noted in Section 7.5, the analysis of the stationarity property of a periodic VAR (PVAR) model can be quite involved, even for the simple PVAR(l) model (see equation (7.51) ). In this chapter I propose two reasonably simple alternative approaches to analysing a multivariate time series using a periodic model.