Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/109051
Authors: 
Minford, Patrick
Xu, Yongdeng
Zhou, Peng
Year of Publication: 
2014
Series/Report no.: 
Cardiff Economics Working Papers E2014/11
Abstract: 
Out-of-sample forecasting tests of DSGE models against time-series benchmarks such as an unrestricted VAR are increasingly used to check a) the specification b) the forecasting capacity of these models. We carry out a Monte Carlo experiment on a widely-used DSGE model to investigate the power of these tests. We find that in specification testing they have weak power relative to an in-sample indirect inference test; this implies that a DSGE model may be badly mis-specified and still improve forecasts from an unrestricted VAR. In testing forecasting capacity they also have quite weak power, particularly on the lefthand tail. By contrast a model that passes an indirect inference test of specification will almost definitely also improve on VAR forecasts.
Subjects: 
Out of sample forecasts
DSGE
VAR
specification tests
indirect inference
forecast performance
JEL: 
E10
E17
Document Type: 
Working Paper

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