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is a Gaussian random walk and . is a stationary process. We then call the stochastic trend : this describes both the deterministic mean function and shocks that have a permanent effect. While this is a more realistic model than the trend stationary model, we need to extract a stationary time series from .

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Can you think of a weak stationary process that is not strong stationary? There is a special class of processes where weak and strong stationarity are equivalent: A Gaussian process is a stochastic process whose f.d.d.'s are all multivariate normal distributions.

Testing the null that y is random walk without drift: DF test with no constant or trend o Consider the AR(1) process yy vtt t 1 The null hypothesis is that y is I(1), so H0: = 1.