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Erscheinungsjahr: 
2014
Schriftenreihe/Nr.: 
Cardiff Economics Working Papers No. E2014/11
Verlag: 
Cardiff University, Cardiff Business School, Cardiff
Zusammenfassung: 
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.
Schlagwörter: 
Out of sample forecasts
DSGE
VAR
specification tests
indirect inference
forecast performance
JEL: 
E10
E17
Dokumentart: 
Working Paper

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