Abstract
In this paper, we incorporate a Self-organizing state-space model into the Markov-switching model, and propose the Self-organizing Markov-switching state-space (SOMS) model. The approximate Monte Carlo filter is applied for state estimation, including the latent Markov chain, of this model. The SOMS model allows us to evaluate complex systems. We apply it to an analysis of international transmission of business cycles between the U.S. and Germany.
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