Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach

Macroeconomic forecasting in recessions is not easy due to the inherent asymmetry of business cycle phases and the increased uncertainty about the future path of the teetering economy. I propose a mixed-frequency threshold vector autoregressive model with common stochastic volatility in mean (MF-T-CSVM-VAR) that enables to condition on the current state of the business cycle and to account for time-varying macroeconomic uncertainty in form of common stochastic volatility in a mixed-frequency setting. A real-time forecasting experiment highlights the advantage of including the threshold feature for the asymmetry as well as the common stochastic volatility in mean in MF-VARs of different size for US GDP, inflation and unemployment. The novel mixed-frequency threshold model delivers better forecasts for short-term point and density forecasts with respect to GDP and unemployment--particularly evident for nowcasts during recessions. In fact, it delivers a better nowcast than the US Survey of Professional Forecasters for the sharp drop in GDP during the Great Recession in 2008Q4.