  We propose convenient inferential methods for potentially nonstationary
multivariate unobserved components models with fractional integration and
cointegration. Based on finite-order ARMA approximations in the state space
representation, maximum likelihood estimation can make use of the EM algorithm
and related techniques. The approximation outperforms the frequently used
autoregressive or moving average truncation, both in terms of computational
costs and with respect to approximation quality. Monte Carlo simulations reveal
good estimation properties of the proposed methods for processes of different
complexity and dimension.
