Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/219312 
Autor:innen: 
Erscheinungsjahr: 
2020
Verlag: 
ZBW – Leibniz Information Centre for Economics, Kiel, Hamburg
Zusammenfassung: 
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.
Schlagwörter: 
Threshold VAR
Stochastic Volatility
Forecasting
Mixed-frequency Models
Business Cycle
Bayesian Methods
JEL: 
C11
C32
C34
C53
E32
Dokumentart: 
Working Paper






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