Cointegrated VARMA Processes
So far, we have concentrated on stationary VARMA processes for I(0) variables. In this chapter, the variables are allowed to be I(1) and may be cointegrated. As we have seen in Chapter 12, one of the problems in dealing with VARMA models is the nonuniqueness of their parameterization. For inference purposes, it is necessary to focus on a unique representation of a DGP. For stationary VARMA processes, we have considered the echelon form to tackle the identification problem. In the next section, this representation of a VARMA process will be combined with the error correction (EC) form. Thereby it is again possible to separate the long-run cointegration relations from the short-term dynamics. The resulting representation turns out to be a convenient framework for modelling cointegrated variables.
KeywordsCointegration Relation Zero Restriction Echelon Form Asymptotic Normal Distribution Reduce Rank Regression
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