Computationally efficient inference in large Bayesian mixed frequency VARs

Volume: 191, Pages: 109120 - 109120
Published: Jun 1, 2020
Abstract
Mixed frequency Vector Autoregressions (MF-VARs) can be used to provide timely and high frequency estimates or nowcasts of variables for which data is available at a low frequency. Bayesian methods are commonly used with MF-VARs to overcome over-parameterization concerns. But Bayesian methods typically rely on computationally demanding Markov Chain Monte Carlo (MCMC) methods. In this paper, we develop Variational Bayes (VB) methods for use with...
Paper Details
Title
Computationally efficient inference in large Bayesian mixed frequency VARs
Published Date
Jun 1, 2020
Volume
191
Pages
109120 - 109120
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