Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/167647
Authors: 
Neuwirth, Stefan
Year of Publication: 
2017
Series/Report no.: 
KOF Working Papers 430
Abstract: 
This paper tests the usefulness of time-varying parameters when forecasting with mixed-frequency data. For this we compare the forecast performance of bridge equations and unrestriced MIDAS models with constant and time-varying parameters. An out-of-sample forecasting exercise with US real-time data shows that the use of time-varying parameters does not improve forecasts significantly over all vintages. However, since the Great Recession, forecast errors are smaller when forecasting with bridge equations due to the ability of time-varying parameters to incorporate gradual structural changes faster.
Subjects: 
forecasting
Bayesian
mixed frequency data
time-varying parameters
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.