In this paper, we consider asymptotic inference in the multivariate BEKK model based on (co)variance targeting (VT). By definition the VT estimator is a two‐step estimator and the theory presented is based on expansions of the modified likelihood function, or estimating function, corresponding...

Cointegration is studied for a non-linear autoregressive process characterized by discontinuous and regime-dependent equilibrium or error correction. Here the disequilibrium, as measured by the norm of linear "stable" or cointegrating relations, determines the regime and hence the equilibrium...

The issue of including stationary explanatory variables is addressed in the vector autoregressive (VAR) model, when testing for cointegration rank. It is shown that simply in-cluding stationary explanatory variables as extra regressors will lead to nuisance parameters in the asymptotic...

This paper looks at the problem of performing likelihood inference for limited dependent processes. Throughout we use simulation to carry out either classical inference through a simulated score method (simulated EM algorithm) or Bayesian analysis. A common theme is to develop computationally...

This paper discusses and documents the algorithms of SsfPack 2.2. SsfPack is a suite of C routines for carrying out computations involving the statistical analysis of univariate and multivariate models in state space form. The emphasis is on documenting the link we have made to the Ox computing...