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dynamics is estimated with Bayesian methods for euro area data from 1975-2003. This exercise provides support for our model and …
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-smoothing/sampling algorithm to infer on the latent state indicator in maximum likelihood and Bayesian estimation procedures. Emphasis is again …
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We combine the factor augmented VAR framework with recently developed estimation and identification procedures for sparse dynamic factor models. Working with a sparse hierarchical prior distribution allows us to discriminate between zero and non-zero factor loadings. The non-zero loadings...
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Two Bayesian sampling schemes are outlined to estimate a K-state Markov switching model with time-varying transition …
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