Statistical estimation and classification algorithms for regime-switching VAR model with exogenous variables

Abstract

We consider a vector autoregression model with exogenous variables and Markov-switching regimes to describe complex systems with cyclic changes of states. To estimate and forecast the states, we propose EM and discriminant analysis algorithms based on non-classified and classified data samples accordingly. The accuracy of the algorithms is examined by means of computer simulation experiments.