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This chapter reviews Bayesian methods for inference and forecasting with VAR models. Bayesian inference and, by extension, forecasting depends on numerical methods for simulating from the posterior distribution of the parameters and special attention is given to the implementation of the...
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To simultaneously consider mixed-frequency time series, their joint dynamics, and possible structural changes, we introduce a time-varying parameter mixed-frequency VAR. To keep our approach from becoming too complex, we implement time variation parsimoniously: only the intercepts and a common...
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by evaluating a mixed-frequency time-varying parameter VAR with stochastic volatility (MF-TVP-SV-VAR). Overall, the MFTVP …
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autoregression with stochastic volatility (MF-TVP-SVVAR). The latter is able to cope with structural changes and can handle …' performance during the Great Recession and find that the combination of stochastic volatility, time-varying parameters, and mixed …
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