Marginal distribution of Markov-switching VAR processes
We make available simple and accurate closed-form approximations to the marginal distribution of Markov-switching Vector Auto-Regressive (MS VAR) processes. The approximation is built upon the property of MS VAR processes of being gaussian conditionally on any semi-innite sequence of the latent state. Truncating the semi-innite sequence and averaging over all possible sequences of that nite length yields a mixture of normals that converges to the unknown marginal distribution as the sequence length increases. Numerical experiments conrm the viability of the approach which extends to the closely related class of MS state space models. Several applications are discussed.
FIORENTINI Gabriele;
PLANAS Christophe;
ROSSI Alessandro;
2016-09-12
TAYLOR & FRANCIS INC
JRC99534
0361-0926,
http://www.tandfonline.com/doi/full/10.1080/03610926.2015.1132324,
https://publications.jrc.ec.europa.eu/repository/handle/JRC99534,
10.1080/03610926.2015.1132324,
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