Streamlining time-varying VAR with a factor structure in the parameters

Simon Beyeler

I introduce a factor structure on the parameters of a Bayesian TVP-VAR to reduce the dimension of the model's state space. To further limit the scope of over-fitting the estimation of the factor loadings uses a new generation of shrinkage priors. A Monte Carlo study illustrates the ability of the proposed sampler to well distinguish between time-varying and constant parameters. In an application with Swiss data the model proves useful to capture changes in the economy's dynamics due to the lower bound on nominal interest rates.

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Year of publication:	[2019]
Authors:	Beyeler, Simon
Publisher:	Gerzensee : Study Center Gerzensee
Subject:	Bayesian VAR \| time-varying parameter \| dimension reduction \| VAR-Modell \| VAR model \| Bayes-Statistik \| Bayesian inference \| Zeitreihenanalyse \| Time series analysis \| Schätztheorie \| Estimation theory \| Schätzung \| Estimation \| Monte-Carlo-Simulation \| Monte Carlo simulation