Forecasting Economic Activity with Mixed Frequency Bayesian Vars
43 Pages Posted: 22 Jun 2016 Last revised: 29 Apr 2020
Date Written: May, 2016
Mixed frequency Bayesian vector autoregressions (MF-BVARs) allow forecasters to incorporate a large number of mixed frequency indicators into forecasts of economic activity. This paper evaluates the forecast performance of MF-BVARs relative to surveys of professional forecasters and investigates the influence of certain specification choices on this performance. We leverage a novel real-time dataset to conduct an out-of-sample forecasting exercise for U.S. real gross domestic product (GDP). MF-BVARs are shown to provide an attractive alternative to surveys of professional forecasters for forecasting GDP growth. However, certain specification choices such as model size and prior selection can affect their relative performance.
Keywords: Mixed frequency, Bayesian VAR, Real-time data, Nowcasting
JEL Classification: C32, C53, E37
Suggested Citation: Suggested Citation