Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/215056
Authors: 
Heinrich, Markus
Reif, Magnus
Year of Publication: 
2020
Series/Report no.: 
CESifo Working Paper No. 8054
Abstract: 
This paper provides a detailed assessment of the real-time forecast accuracy of a wide range of vector autoregressive models (VAR) that allow for both structural change and indicators sampled at different frequencies. We extend the literature by evaluating a mixed-frequency time-varying parameter VAR with stochastic volatility (MF-TVP-SV-VAR). Overall, the MF-TVP-SV-VAR delivers accurate now- and forecasts and, on average, outperforms its competitors. We assess the models' accuracy relative to expert forecasts and show that the MF-TVP-SV-VAR delivers better inflation nowcasts in this regard. Using an optimal prediction pool, we moreover demonstrate that the MF-TVP-SV-VAR has gained importance since the Great Recession.
Subjects: 
time-varying parameters
forecasting
nowcasting
mixed-frequency models
Bayesian methods
JEL: 
C11
C53
C55
E32
Document Type: 
Working Paper

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