Large Mixed-Frequency Vars with a Parsimonious Time-Varying Parameter Structure

Abstract

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 factor in the error variances vary over time. We can therefore estimate moderately large systems in a reasonable amount of time, which makes our modifications appealing for practical use. For eleven U.S. variables, we examine the performance of our model and compare the results to the time-constant MF-VAR of Schorfheide and Song (2015). Our results demonstrate the feasibility and usefulness of our method.

Keywords: Mixed Frequencies, Time-Varying Intercepts, Common Stochastic Volatility, Bayesian VAR, Forecasting

JEL Classification: C32, C51, C53