LIKELIHOOD ANALYSIS OF THE I(2) MODEL

The I(2) model is defined as a submodel of the general vector autoregr essive model, by two reduced rank conditions. The model describes stoc hastic processes with stationary second difference. A parametrization is suggested which makes Likelihood inference feasible. Consistency of the maximum Likelihood estimator is proved, and the asymptotic distri bution of the maximum likelihood estimator is given. It is shown that the asymptotic distribution is either Gaussian, mixed Gaussian or, in some cases, even more complicated.